Unfamiliar Environment Research Articles

3-Dimensional Modelling with Visual-SLAM in Indoor Environment

Robots can now locate themselves in unfamiliar environments and concurrently create maps of their surroundings thanks to simultaneous localization and mapping (SLAM), which is utilized in various fields, including robotics and mapping. The most common SLAM methods are the LiDAR-SLAM, which uses the Light Detection and Ranging (LiDAR) sensor, and the Visual SLAM (VSLAM), which uses the camera sensor is used. VSLAM is now receiving great interest and research thanks to its advantages, such as its low cost compared to LiDAR, low energy consumption, durability, and rich environmental information. This study aims to produce a three-dimensional (3D) model of an indoor area using image data captured by the stereo camera located on the Unmanned Ground Vehicle (UGV). Easily measured objects from the field of operation were chosen to assess the generated model’s accuracy. The actual dimensions of the objects were measured, and these values were compared to those derived from the VSLAM-based 3D model. When the data were evaluated, it was found that the size of the object produced from the model could be varied by ±2cm. The surface accuracy of the 3D model produced has also been analyzed. For this investigation, areas where the walls and floor surfaces were flat in the field were selected, and the plane accuracy of these areas was analyzed. The plain accuracy values of the specified surfaces were determined to be below ±1cm.

Reducing the time to activation of the emergency call system in operating theatres: effect of installing vertical red line indicators

BackgroundThe 7th National Audit Project of the Royal College of Anaesthetists (NAP7) recommended that an emergency call system be immediately accessible in all anaesthesia locations. It is essential that all theatre team members can rapidly call for help to reduce the risk of patient harm. However, the ability of staff to activate this system in a timely manner can be affected by cluttered or unfamiliar environments and cognitive overload. One proposed strategy to enable rapid identification and activation of emergency call systems is to install a red vertical painted stripe on the wall from the ceiling to the activation button. We investigated the effect of introducing this vertical red line on activation times in operating theatres in the UK and Australia. MethodsOperating theatre team members, including anaesthetists, surgeons, anaesthetic nurses, surgical and theatre nurses, operating theatre practitioners, and technicians, were approached without prior warning and asked to simulate activation of an emergency call. Vertical red lines were installed, and data collection repeated in the same operating theatres 4–12 months later. ResultsAfter installation of vertical red lines, the proportion of activations taking >10 s decreased from 31.9% (30/94) to 13.6% (17/125, P=0.001), and >20 s decreased from 19.1% (18/94) to 4.8% (6/125, P<0.001). The longest duration pre-installation was 120 s, and post-installation 35 s. ConclusionsThis simple, safe, and inexpensive design intervention should be considered as a design standard in all operating theatres to minimise delays in calling for help.

Expatriate academics’ adjustment experience at a higher education institution in South Africa

Orientation: Expatriate academics in higher education institutions (HEIs) face several socio-cultural and integration challenges that significantly influence their adjustment. Insufficient support and a non-conducive environment hamper their well-being.Research purpose: This study aims to describe the adjustment experiences of expatriate academics at a HEI in South Africa. Recommendations are made towards creating an enabling environment in which expatriate academics can better facilitate adjustment.Motivation for the study: This study aimed to compete globally, HEIs appoint international academics with scarce skills to enhance their teaching, learning, and research. Expatriate academics are driven by push and pull factors when accepting international opportunities. Entering an unfamiliar environment, implies disruption on a psychosocial, socio-economic and job adjustment level, and if not well-supported results in maladjustment affecting expatriate well-being and job performance.Research design, approach and method: An interpretive, qualitative approach was adopted. Five purposively selected expatriate academics partook in semi-structured interviews and the data were analysed through content analysis.Main findings: A lack of employer support and cultural diversity factors impede participants’ ability to adjust at work and in the community. Having grit and being resourceful in overcoming challenges resulted in better adjustment.Practical/managerial implications: Facilitating collaborative relationships between expatriates and host country nationals, and using supportive services and resources will enable better adjustment.Contribution/value-add: Expatriate academics share their lived experiences of what hindered their adjustment and several recommendations are made to HEIs and foreign academics towards creating an enabling environment promoting adjustment.

IT-2 Fuzzy Control and Behavioral Approach Navigation System for Holonomic 4WD/4WS Agricultural Robot

In contemporary agriculture, researchers are focusing on precision farming and environmentally conscious techniques, leading to the advancement of autonomous agricultural mobile robots. Consequently, A navigation system using TSK Interval Type-2 fuzzy logic has been developed and, for the first time, applied to a holonomic mobile agricultural robot equipped with four-wheel drive and steer. This system employs a behavioral approach to accomplish the robot’s primary objective in unfamiliar environments. It comprises four controllers: one exclusively dedicated to goal-seeking behavior, with the remaining controllers responsible for obstacle avoidance. Supervision of these controllers is conducted through the Mandani fuzzy logic approach, which combines the outputs of all four controllers, robot wheel velocities and steering angles, using a proposed equations. Various case studies were examined and simulated utilizing MATLAB and VREP software platform to assess the navigator system’s performance. The simulation outcomes showcase the efficiency of the proposed equations and the system’s navigation capabilities. The stability of the entire system was thoroughly examined and confirmed, employing the Lyapunov function, in environments with and without obstacles.

A Multi-Modal Foundation Model to Assist People with Blindness and Low Vision in Environmental Interaction.

People with blindness and low vision (pBLV) encounter substantial challenges when it comes to comprehensive scene recognition and precise object identification in unfamiliar environments. Additionally, due to the vision loss, pBLV have difficulty in accessing and identifying potential tripping hazards independently. Previous assistive technologies for the visually impaired often struggle in real-world scenarios due to the need for constant training and lack of robustness, which limits their effectiveness, especially in dynamic and unfamiliar environments, where accurate and efficient perception is crucial. Therefore, we frame our research question in this paper as: How can we assist pBLV in recognizing scenes, identifying objects, and detecting potential tripping hazards in unfamiliar environments, where existing assistive technologies often falter due to their lack of robustness? We hypothesize that by leveraging large pretrained foundation models and prompt engineering, we can create a system that effectively addresses the challenges faced by pBLV in unfamiliar environments. Motivated by the prevalence of large pretrained foundation models, particularly in assistive robotics applications, due to their accurate perception and robust contextual understanding in real-world scenarios induced by extensive pretraining, we present a pioneering approach that leverages foundation models to enhance visual perception for pBLV, offering detailed and comprehensive descriptions of the surrounding environment and providing warnings about potential risks. Specifically, our method begins by leveraging a large-image tagging model (i.e., Recognize Anything Model (RAM)) to identify all common objects present in the captured images. The recognition results and user query are then integrated into a prompt, tailored specifically for pBLV, using prompt engineering. By combining the prompt and input image, a vision-language foundation model (i.e., InstructBLIP) generates detailed and comprehensive descriptions of the environment and identifies potential risks in the environment by analyzing environmental objects and scenic landmarks, relevant to the prompt. We evaluate our approach through experiments conducted on both indoor and outdoor datasets. Our results demonstrate that our method can recognize objects accurately and provide insightful descriptions and analysis of the environment for pBLV.

Disruption of sleep by one night of in-home polysomnographic recording: a longitudinal actigraphy study of patients with chronic musculoskeletal pain and pain-free controls

BackgroundPatients with chronic pain frequently have comorbid sleep disturbances. Since improvement of sleep may alleviate both sleep problems and to some extent pain, sleep studies in this group becomes relevant. Polysomnography (PSG) is considered the gold standard for characterizing sleep; however, it is resource-demanding and may itself disrupt sleep due to the use of inconvenient equipment in unfamiliar sleep environments. To circumvent disruptive first night effect that may occur, sleep protocols may prescribe several nights of PSG to facilitate adaptation despite the equipment may still influence sleep on all nights. Moreover, the disruptive effects of polysomnography may vary between patient groups and healthy persons, yet have not previously been studied in patients with chronic pain. The present study aimed to assess whether sleep disruption during one night of in-home PSG was more severe in patients with chronic musculoskeletal pain compared to pain-free controls.MethodSleep was assessed by self-reported sleep quality and actigraphy measured sleep onset latency, sleep duration, wake after sleep onset and sleep efficiency during one night of in-home PSG and the following six nights in 56 patients and 53 pain-free participants. Additionally, sleep schedule was assessed by sleep onset time, wake up time and time in bed. The repeated sleep measures were analysed with mixed model regressions, comparing mean score changes between and within groups.ResultsA disruptive effect of PSG was evident for self-reported sleep quality and actigraphy measured sleep onset latency in both groups. These effects were however not significantly different between the groups, indicating comparable sensitivity to a single night of PSG between pain patients and pain-free controls.ConclusionThese findings suggest that a singlenight in-home PSG protocol may be considered for case–control studies of patients with chronic pain.

Recruitment of hippocampal and thalamic pathways to the central amygdala in the control of feeding behavior under novelty.

It is adaptive to restrict eating under uncertainty, such as during habituation to novel foods and unfamiliar environments. However, sustained restrictive eating can become maladaptive. Currently, the neural substrates of restrictive eating are poorly understood. Using a model of feeding avoidance under novelty, our recent study identified forebrain activation patterns and found evidence that the central nucleus of the amygdala (CEA) is a core integrating node. The current study analyzed the activity of CEA inputs in male and female rats to determine if specific pathways are recruited during feeding under novelty. Recruitment of direct inputs from the paraventricular nucleus of the thalamus (PVT), the infralimbic cortex (ILA), the agranular insular cortex (AI), the hippocampal ventral field CA1, and the bed nucleus of the stria terminals (BST) was assessed with combined retrograde tract tracing and Fos induction analysis. The study found that during consumption of a novel food in a novel environment, larger number of neurons within the PVTp and the CA1 that send monosynaptic inputs to the CEA were recruited compared to controls that consumed familiar food in a familiar environment. The ILA, AI, and BST inputs to the CEA were similarly recruited across conditions. There were no sex differences in activation of any of the pathways analyzed. These results suggest that the PVTp-CEA and CA1-CEA pathways underlie feeding inhibition during novelty and could be potential sites of malfunction in excessive food avoidance.

Dopamine encoding of novelty facilitates efficient uncertainty-driven exploration.

When facing an unfamiliar environment, animals need to explore to gain new knowledge about which actions provide reward, but also put the newly acquired knowledge to use as quickly as possible. Optimal reinforcement learning strategies should therefore assess the uncertainties of these action-reward associations and utilise them to inform decision making. We propose a novel model whereby direct and indirect striatal pathways act together to estimate both the mean and variance of reward distributions, and mesolimbic dopaminergic neurons provide transient novelty signals, facilitating effective uncertainty-driven exploration. We utilised electrophysiological recording data to verify our model of the basal ganglia, and we fitted exploration strategies derived from the neural model to data from behavioural experiments. We also compared the performance of directed exploration strategies inspired by our basal ganglia model with other exploration algorithms including classic variants of upper confidence bound (UCB) strategy in simulation. The exploration strategies inspired by the basal ganglia model can achieve overall superior performance in simulation, and we found qualitatively similar results in fitting model to behavioural data compared with the fitting of more idealised normative models with less implementation level detail. Overall, our results suggest that transient dopamine levels in the basal ganglia that encode novelty could contribute to an uncertainty representation which efficiently drives exploration in reinforcement learning.

Creation of a Patient Information Video to Improve the Patient Experience of the Surgical Assessment Unit.

Patients who attend emergency surgical services are entering an unfamiliar environment whilst often being unwell and in pain. Patient satisfaction in emergency surgical units is often low due to poor communication with attendees and long wait times. A pilot patient questionnaire identified areas where patient satisfaction was low during attendance at the surgical assessment unit (SAU). The aim of this intervention was to improve patient satisfaction with their experiencewhilst attending the SAU. An education video was filmed to address the areas where services were falling short of expectations, and this was played in the waiting room. Further questionnaire results tailored the frequency of the video to achieve maximum impact. Data were collected at three time points: firstly, prior to the introduction of the video (n=34); secondly, with the video played hourly (n=15); and finally with the video played every 30 minutes at a higher volume (n=15). Mean satisfaction scores after the final cycle improved to 7.3 from 4.9 (p=0.0009). Additionally, 94% of patients agreed that the video was in keeping with their personal experience of the SAU and agreed that the video improved their understanding of what to expect from the visit. Interventions that improve communication with patients and adjust their expectations play an important role in improving patient satisfaction and their overall perception of care. This can be achieved with a simple patient information video.

Visionary Audio Hub using Machine Learning

Image-to-text-to-speech conversion, powered by machine learning, is an emerging field to transform how we access and engage with information. By integrating optical character recognition (OCR) and text-to-speech (TTS) technologies, machine learning enables the extraction of text from images and its conversion into speech with greater accuracy and efficiency than ever before. This technology holds immense potential to enhance accessibility for a broad spectrum of users, including those with visual impairments, students, tourists, researchers, and musicians. For instance, individuals with visual impairments can use image-to-text-to-speech conversion to access scanned textbooks and course materials in speech format, facilitating easier comprehension and study. Similarly, tourists can leverage this technology to translate foreign language signs and text into speech, aiding navigation in unfamiliar environments. Researchers can benefit from image-to-text-to-speech conversion by extracting data from scientific papers and documents, simplifying analysis and synthesis processes. Moreover, musicians can explore new creative avenues by converting text to speech and manipulating the audio output to innovate musical compositions. Machine learning algorithms play a crucial role in improving the quality and naturalness of synthesized speech in these systems. By considering factors such as language, accent, and prosody, machine learning algorithms generate speech that closely resembles human speech patterns, enhancing clarity and understanding. Keywords— Image-to-text-to-speech conversion, Machine learning, Optical character recognition (OCR), Text-to-speech (TTS) technologies, Accessibility, Naturalness of synthesized speech.

The potential influence of genome-wide adaptive divergence on conservation translocation outcome in an isolated greater sage-grouse population.

Conservation translocations are an important conservation tool commonly employed to augment declining or reestablish extirpated populations. One goal of augmentation is to increase genetic diversity and reduce the risk of inbreeding depression (i.e., genetic rescue). However, introducing individuals from significantly diverged populations risks disrupting coadapted traits and reducing local fitness (i.e., outbreeding depression). Genetic data are increasingly more accessible for wildlife species and can provide unique insight regarding the presence and retention of introduced genetic variation from augmentation as an indicator of effectiveness and adaptive similarity as an indicator of source and recipient population suitability. We used 2 genetic data sets to evaluate augmentation of isolated populations of greater sage-grouse (Centrocercus urophasianus) in the northwestern region of the species range (Washington, USA) and to retrospectively evaluate adaptive divergence among source and recipient populations. We developed 2 statistical models for microsatellite data to evaluate augmentation outcomes. We used one model to predict genetic diversity after augmentation and compared these predictions with observations of genetic change. We used the second model to quantify the amount of observed reproduction attributed to transplants (proof of population integration). We also characterized genome-wide adaptive divergence among source and recipient populations. Observed genetic diversity (HO=0.65) was higher in the recipient population than predicted had no augmentation occurred (HO=0.58) but less than what was predicted by our model (HO=0.75). The amount of shared genetic variation between the 2 geographically isolated resident populations increased, which is evidence of periodic gene flow previously assumed to be rare. Among candidate adaptive genes associated with elevated fixation index (FST) (143 genes) or local environmental variables (97 and 157 genes for each genotype-environment association method, respectively), we found clusters of genes with related functions that may influence the ability of transplants to use local resources and navigate unfamiliar environments and their reproductive potential, all possible reasons for low genetic retention from augmentation.

Autistic Spectrum disorder and Anaesthesia

One of the groups of patients which may require the greatest flexibility of approach is those with autistic spectrum disorder (ASD). ASD is a lifelong developmental disability, affecting four times as many males than females, which affects how a person communicates with, and relates to, other people and the world around them. Challenging behaviors may be triggered by the unfamiliar perioperative environment and may make anesthesia related procedures difficult or impossible. Children with more severe ASD may exhibit verbal or physical aggression, antisocial or disruptive behavior, temper tantrums, screaming, panic attacks, and self-injurious behavior, and may have aberrant responses to sensory stimuli. Although anaesthesia and sedation do not present a problem for most children with ASD, unpredictable regression in skills and behaviour is noted in a small number of patients after general anaesthesia. A 10-year-old child, 53 kg, with autism under treatment, came for a dental abscess and related dental work under general anaesthesia. The pediatric neurological assessment indicated hyperactivity and lack of cooperation. Post-operatively, during resuscitation, the child showed agitation and an attempt to withdraw oxygen, with the physical presence of his family environment.

Assembling Collections: Isabella Parry and the Distribution of Aboriginal Material Culture at the Port Stephens Australian Agricultural Company Settlement, 1830–1834

This article revisits a suite of Worimi objects in the British Museum whose collection is attributed to Sir Edward Parry, Australian Agricultural Company commissioner from 1830–1834, and brings into view the oft-overlooked diaries and letters of his wife, Lady Isabella Parry. By foregrounding Lady Parry as the primary distributor of material, I shed light on her circulation of objects from Port Stephens to her family estate in Cheshire. Finding herself isolated in an unfamiliar environment, Parry wrote letters and assembled collections in an attempt to exert control over her surroundings and reassert connections to England. While Parry never achieved a sense of belonging within the colony, her material legacy illustrates the importance of collecting and gift-giving to imperial women’s identity formation. Her archive speaks to the value ascribed to colonial material culture within British families, generating knowledge about some of the many Aboriginal objects housed in museums throughout Britain.

Multi-input mutual supervision network for single-pixel computational imaging

In this study, we propose a single-pixel computational imaging method based on a multi-input mutual supervision network (MIMSN). We input one-dimensional (1D) light intensity signals and two-dimensional (2D) random image signal into MIMSN, enabling the network to learn the correlation between the two signals and achieve information complementarity. The 2D signal provides spatial information to the reconstruction process, reducing the uncertainty of the reconstructed image. The mutual supervision of the reconstruction results for these two signals brings the reconstruction objective closer to the ground truth image. The 2D images generated by the MIMSN can be used as inputs for subsequent iterations, continuously merging prior information to ensure high-quality imaging at low sampling rates. The reconstruction network does not require pretraining, and 1D signals collected by a single-pixel detector serve as labels for the network, enabling high-quality image reconstruction in unfamiliar environments. Especially in scattering environments, it holds significant potential for applications.

Indoor 2D Autonomous Exploration with an Omnidirectional Robot: A Strategy Based on Rapidly-Exploring Random Trees

An essential characteristic of a fully autonomous robot is the capability to examine an unfamiliar environment and construct a representation of it. The challenge of autonomous exploration involves overcoming various sub-problems, including Simultaneous Localization and Mapping (SLAM), motion planning, target identification, and informed decision-making for target selection. This paper presents a frontier-based methodology to identify potential navigation targets for the autonomous exploration of unknown environments by an omnidirectional robot. Permanent and temporary Rapidly-exploring Random Tree (RRT)-based structures are used to search the map and detect frontier points. A novel temporary RRT-based structure, Frontier Temporary Tree, is introduced in this study. It is noteworthy that RRT is solely used to search the explorable space for frontier points and does not contribute to motion planning. A cost-benefit analysis, taking into account path cost, heading cost, and information gain, is used to evaluate the frontier points and determine the best target among them. The proposed method is subjected to rigorous testing through both simulation and experimental studies with an omnidirectional robot under real-world scenarios. Comparative results from simulation studies show that our method consistently outperforms, demonstrating its robustness and efficacy.

Antidepressant effects of esketamine via the BDNF/AKT/mTOR pathway in mice with postpartum depression and their offspring

Postpartum depression (PPD) is a serious mental health problem that can negatively affect future generations. BDNF/AKT/mTOR signaling in the frontal lobe and hippocampus in mice is associated with depression, but its role in mice with PPD and their offspring is unknown. This study was aimed at investigating the effects of esketamine (ESK), a drug approved for treatment of refractory depression, on the BDNF/AKT/mTOR pathway in mice with PPD and their offspring. A model of chronic unpredictable mild stress with pregnancy was used. ESK was injected into postpartum mice, and behavioral tests were conducted to predict the severity of symptoms at the end of lactation and in the offspring after adulthood. Both mice with PPD and their offspring showed significant anxiety- and depression-like behaviors that were ameliorated with the ESK intervention. ESK enhanced exploratory behavior in unfamiliar environments, increased the preference for sucrose, and ameliorated the impaired BDNF/AKT/mTOR signaling in the frontal and hippocampal regions in mice. Thus, ESK may have great potential in treating PPD and decreasing the incidence of depression in offspring.

Study protocol for a systematic review of the social determinants of mental health and well-being of older migrants aged 50 years and above

Background Migration is a milestone event in a person’s life, bringing with it the challenges of settling down in an unfamiliar environment. The age at which migration takes place and the way migrants negotiate their old and new world significantly impacts their mental health. Thus, this systematic review seeks to analyse and summarize existing research detailing the contexts in which people migrate later in life and the associations between these contexts and social determinants of their mental health and well-being. Methods Seven databases including PsycINFO, Web of Science, PubMed, Applied Social Sciences Index, Abstracts: ASSIA, Ageline, CINAHL, and Informit will be searched systematically for original journal articles published in English. In the first screening stage, the first reviewer (PB) will screen all titles and abstracts and mark all potentially eligible texts for full-text screening. The second reviewer (HM) will review the decisions made. Any potential conflicts will be resolved with discussion. Afterward, full texts of potentially eligible studies will be assessed for eligibility by two reviewers (PB and HM). The methodological quality (or risk of bias) of individual studies will be appraised using the Mixed Method Appraisal Tool. The thematic synthesis of the data will be performed using a hybrid approach incorporating deductive (framed against a customised social determinants of health framework) and inductive data-driven processes. The review protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) (Reg: CRD42022359881).

Relevance of sleep for wellness: New trends in using artificial intelligence and machine learning

Sleep and well-being have been intricately linked, and sleep hygiene is paramount for developing mental well-being and resilience. Although widespread, sleep disorders require elaborate polysomnography laboratory and patient-stay with sleep in unfamiliar environments. Current technologies have allowed various devices to diagnose sleep disorders at home. However, these devices are in various validation stages, with many already receiving approvals from competent authorities. This has captured vast patient-related physiologic data for advanced analytics using artificial intelligence through machine and deep learning applications. This is expected to be integrated with patients’ Electronic Health Records and provide individualized prescriptive therapy for sleep disorders in the future.

Between life course regimes and biographical orientations: labour market trajectories of refugee mothers in Germany from a gendered perspective

Abstract After arrival, refugees face the challenge of reordering their biographies in new social contexts that are framed by certain life course policies, institutionalised bureaucratic processes and norms. How do processes of adherence to and adaptation of familiar routines and orientations take shape among refugee women with care responsibilities in Germany? Following on from existing literature on life course, refugee and biographical research, this article enriches current research by adding a gender-sensitive analysis of the labour market trajectories of refugee mothers in Germany. Based on biographically oriented interviews with 22 women with children who fled to Germany from predominantly Arab countries between 2015 and 2020, two findings are presented and discussed: a) different phases of arrival framed by different life course policies and norms unfold in various bureaucratic settings, and b) three different labour market orientations and strategies depending on the women’s biographical orientations, their renegotiation in unfamiliar environments and the life stage the women currently find themselves in. The results provide new insights into the biographical trajectories of refugee women’s labour market participation and challenge a predominantly static view of this group as homogeneous in terms of qualifications, care responsibilities and employment aspirations.

‘We Are Managing’: Challenges and Coping Strategies of Family Caregivers in a Short Term Hospitalization in the Eastern Region of Ghana

Caring for a sick relative is not without challenges. Family members who leave their homes to care for a sick relative in an unfamiliar hospital environment encounter more challenges than those who provide care in their familiar home environment. This hospital ethnography was carried out in one of the secondary hospitals in Ghana. Thirty-two caregivers were sampled using the purposive sampling technique. Data was collected through the semi structured interview guide. Using the qualitative exploratory case study, the study revealed that the challenges facing family caregivers are multidimensional. These challenges are classified into three major groups: institutional, environmental, and financial. In response to these challenges, caregivers developed different strategies such as denying themselves some pleasures of life, developing faith in God through prayers and giving the identification card given them by the hospital authority to other relatives who are not recognised by the health professionals as caregivers.