Search Results (104)

Artificial general intelligence (AGI) is often depicted as a transformative breakthrough, yet debates persist on whether current advancements truly represent general intelligence or remain limited to domain-specific applications. This study empirically maps AGI-related research across subject areas, geographies, and United Nations Sustainable Development Goals (SDGs) via machine learning-based analysis. The findings reveal that while the AGI discourse remains anchored in computing and engineering, it has diversified significantly into human-centered domains such as healthcare (SDG 3), education (SDG 4), clean energy (SDG 7), industrial innovation (SDG 9), and public governance (SDG 16). Geographically, research remains concentrated in the United States, China, and Europe, but emerging contributions from countries such as India, Pakistan, and Costa Rica suggest a gradual democratization of AGI exploration. Thematic expansion into legal systems, governance, and environmental sustainability points to AGI’s growing relevance for systemic societal challenges, even if true AGI remains aspirational. Funding patterns show strong private and public sector interest in general-purpose AI systems, whereas institutional collaborations are increasingly global and interdisciplinary. However, challenges persist in cross-sectoral data interoperability, infrastructure readiness, equitable funding distribution, and regulatory oversight. Addressing these issues requires anticipatory governance, international cooperation, and capacity-building strategies to ensure that the evolving AGI landscape aligns with inclusive, sustainable, and socially responsible futures. Full article

Concurrent cognitive tasks, such as avoiding visual, auditory, chemical, and electrical hazards, and concurrent motor tasks, such as load carriage, are prevalent in ergonomic settings. Trips are extremely common in the workplace, leading to fatal and non-fatal fall-related injuries. Intrinsic factors, such as attention, fatigue, and anticipation, as well as extrinsic factors, including tasks at hand, affect trip recovery responses. Objective: The purpose of this study was to investigate the ankle joint kinematics in unexpected and expected trip responses during single-tasking (ST), dual-tasking (DT), and triple-tasking (TT), before and after a physically fatiguing protocol among young, healthy adults. Methods: Twenty volunteers’ (10 females, one left leg dominant, age 20.35 ± 1.04 years, height 174.83 ± 9.03 cm, mass 73.88 ± 15.55 kg) ankle joint kinematics were assessed using 3D motion capture system during unperturbed gait (NG), unexpected trip (UT), and expected trip (ET), during single-tasking (ST), cognitive dual-tasking (CDT), motor dual-tasking (MDT), and triple-tasking (TT), under both PRE and POST fatigue conditions. Results: Greater dorsiflexion angles were observed during UT compared to NG, MDT compared to ST, and TT compared to ST. Significantly greater plantar flexion angles were observed during ET compared to NG and during POST compared to PRE. Conclusions: Greater dorsiflexion angles during dual- and triple-tasking suggest that divided attention affects trip recovery. Greater plantar flexion angles following fatigue are likely an anticipatory mechanism due to altered muscle activity and increased postural control demands. Full article

Study Design: Prospective observational study. Background: Lumbar spinal stenosis (LSS) impairs balance and gait function, increasing fall risk and limiting quality of life. Although postoperative recovery of balance is clinically important, longitudinal data using multidimensional balance assessments are limited. Methods: A prospective cohort study was conducted in 101 patients (mean age 74.9 ± 6.9 years) undergoing surgery for LSS. The Brief Balance Evaluation Systems Test (Brief BESTest), Oswestry Disability Index (ODI), Modified Falls Efficacy Scale (MFES), Zurich Claudication Questionnaire (ZCQ), and Visual Analog Scales (VAS) for pain/numbness were evaluated preoperatively and at 6 and 12 months postoperatively. Changes over time and correlations between Brief BESTest and PROMs were analyzed. Results: The total Brief BESTest score significantly improved from 13.3 ± 5.3 preoperatively to 16.1 ± 5.1 at 6 months and 16.0 ± 5.1 at 12 months (p < 0.01). Subdomains including Anticipatory Adjustments, Postural Responses, Sensory Orientation, and Stability in Gait improved significantly, while Stability Limits did not. At 12 months postoperatively, ODI decreased by 19.1%, ZCQ symptom and function scores improved by 0.8 and 0.9 points, respectively, and VAS scores improved by 17.1 mm for low back pain, 26.5 mm for lower limb pain, and 19.5 mm for numbness, all showing marked improvements from baseline. MFES also increased significantly postoperatively. The Brief BESTest score correlated significantly with MFES and ZCQ-PFS at baseline, and with ODI, ZCQ, and VAS scores at 12 months. Conclusions: Balance ability in LSS patients improved after surgery, as measured by the Brief BESTest, with clinically meaningful changes maintained for 12 months. Improvements in balance were significantly associated with reductions in pain, disability, and fear of falling, suggesting the Brief BESTest is a comprehensive indicator of postoperative recovery. Full article

Background/Objectives: Grief in cancer patients represents a multidimensional psychological response encompassing anticipatory, existential, and identity-related distress. While the recent literature has examined grief in caregivers, family members, and even healthcare professionals, the psychological grief experienced by patients themselves following a cancer diagnosis remains comparatively understudied and insufficiently characterized in empirical research. This systematic review aims to evaluate observational studies that used validated psychometric instruments to measure grief in adult cancer patients and to synthesize findings on the significance of grief in this population. Methods: Following PRISMA 2020 guidelines, a systematic search of PubMed, CINAHL, and PsycINFO was conducted to identify observational studies that employed validated tools to assess grief among adult cancer patients. The inclusion criteria required the use of psychometrically validated grief instruments and the collection of quantitative data. Fifteen studies met eligibility criteria and were included in the final analysis. Results: Grief symptoms were consistently present at moderate to high levels across diverse cancer types, care settings, and geographic regions. Preparatory Grief in Advanced Cancer (PGAC) scores often exceeded thresholds associated with clinical concern, with correlations observed between grief and psychological variables such as anxiety (r = 0.63), depression (r = 0.637), hopelessness (r = 0.63), and dignity (r = 0.654). Demographic factors (e.g., younger age, female gender) and illness perceptions (e.g., identity centrality, stigma) further intensified grief. Grief was a predominant psychological concern even when general distress measures failed to capture its presence. Conclusions: Future research is essential to identify an effective public health strategy for addressing grief through structured screening conducted in primary care and outpatient medical settings, coupled with accessible referral pathways to community-based support groups and coordinated follow-up services to facilitate grief management. Full article

Urban traffic congestion poses persistent challenges to mobility, public safety, and governance efficiency in metropolitan areas. This study proposes an intelligent traffic flow forecasting framework based on an extended Long Short-Term Memory (xLSTM) model, specifically designed for real-time congestion prediction and proactive police dispatch support. Utilizing a real-world dataset collected from over 300 vehicle detector (VD) sensors, the proposed model integrates vehicle volume, speed, and lane occupancy data at five-minute intervals. Methodologically, the xLSTM model incorporates matrix-based memory cells and exponential gating mechanisms to enhance spatio-temporal learning capabilities. Model performance is evaluated using multiple metrics, including congestion classification accuracy, F1-score, MAE, RMSE, and inference latency. The xLSTM model achieves a congestion prediction accuracy of 87.3%, an F1-score of 0.882, and an average inference latency of 41.2 milliseconds—outperforming baseline LSTM, GRU, and Transformer-based models in both accuracy and speed. These results validate the system’s suitability for real-time deployment in police control centers, where timely prediction of traffic congestion enables anticipatory patrol allocation and dynamic signal adjustment. By bridging AI-driven forecasting with public safety operations, this research contributes a validated and scalable approach to intelligent transportation governance, enhancing the responsiveness of urban mobility systems and advancing smart city initiatives. Full article

Pedestrian flow simulations play a pivotal role in urban planning, transportation engineering, and disaster response by enabling the detailed analysis of crowd dynamics and walking behavior. While physical models such as the Social Force model and Boids have been widely used, they often struggle to replicate complex inter-agent interactions. On the other hand, reinforcement learning (RL) methods, although adaptive, suffer from limited interpretability due to their opaque policy structures. To address these limitations, this study proposes a pedestrian simulation framework based on the Anticipatory Classifier System 2 (ACS2), a rule-based evolutionary learning model capable of extracting explicit behavior rules through trial-and-error learning. The proposed model captures the interactions between agents and environmental features while preserving the interpretability of the acquired strategies. Simulation experiments demonstrate that the ACS2-based agents reproduce realistic pedestrian dynamics and achieve comparable adaptability to conventional reinforcement learning approaches such as tabular Q-learning. Moreover, the extracted behavior rules enable systematic analysis of movement patterns, including the effects of obstacles and crowd composition on flow efficiency and group alignment. The results suggest that the ACS2 provides a promising approach to constructing interpretable multi-agent simulations for real-world pedestrian environments. Full article

This paper introduces the Integrated Model for Sustainable Development (IMSD), a theory-driven governance framework that embeds Corporate Diversity Responsibility (CDR) into climate and energy policy to advance systemic equity, institutional resilience, and inclusive innovation. Grounded in Institutional Theory, the Resource-Based View (RBV), and Intersectionality Theory, IMSD unifies fragmented sustainability efforts across five pillars: Climate Sustainability, Social Sustainability (CDR), Governance Integration, Collaborative Partnerships, and Implementation and Monitoring. Aligned with SDGs 7, 10, and 13, IMSD operationalizes inclusive leadership, anticipatory adaptation, and equity-centered decision-making. It addresses the compounded climate vulnerabilities faced by women and marginalized groups in the Global South, integrating insights from Indigenous resilience and intersectional adaptation strategies. Unlike conventional CSR or ESG models, IMSD institutionalizes diversity as a strategic asset and governance principle. It transforms DEIB from symbolic compliance into a catalyst for ethical leadership, legitimacy, and performance in turbulent environments. The model’s modular structure supports cross-sector scalability, making it a practical tool for organizations seeking to align ESG mandates with climate justice and inclusive innovation. Future empirical validation of the IMSD framework across diverse governance settings will further strengthen its applicability and global relevance. IMSD represents a paradigm shift in sustainability governance—bridging climate action and social equity through theory-based leadership and systemic institutional transformation. Full article

Daytime-restricted feeding (TRF) exerts outstanding effects on circadian physiology, nutrient utilization, and energy metabolism. Limiting feeding access to two hours during the daytime (12:00–14:00 h) for three weeks promotes food-anticipatory activity (FAA). FAA encompasses not only behaviors related to meal expectations but also includes diurnal fluctuations in liver metabolic responses, including distinct redox handling. Hepatic microarray profiles of genes associated with redox response processes were analyzed at three crucial time points: at the beginning of the light period or before FAA (08:00 h), during the expression of FAA (11:00 h), and after feeding (14:00 h). Data on fasting and nutrient processing were integrated, whereas circadian implications were extrapolated by comparing the TRF transcriptional output with a one-day fasting group. Transcripts of redox reactions, such as reactive oxygen species (ROS) generation, antioxidant defenses, NAD⁺/NADH equilibrium, and glutathione, hydrogen peroxide (H₂O₂), arginine, nitric oxide (NO), and hydrogen sulfide (H₂S) metabolism, were analyzed. Results showed a decline in antioxidant defenses at 08:00 h, followed by a burst of pro-oxidant reactions, preparation of glutathione metabolism factors, and a tendency to decrease H₂O₂ and increase NO and H₂S during the FAA. Most of the findings observed during the FAA were absent in response to one-day fasting. Hence, TRF involves concerted and sequential responses in liver pro-oxidant and antioxidant reactions, facilitating a redox-related circadian control that optimizes the metabolic utilization of nutrients, which differs from a response to a simple fast-feed cycle. Full article

To unravel the mechanisms underpinning salt tolerance, different studies have attempted to determine the physiological and genetic variations behind the difference in salt tolerance between Arabidopsis thaliana and the salt-tolerant Thellungiella salsuginea (halophila). Most of these studies were limited to a specific duration of salt treatment and neglected the time response as a possible contributing factor to the higher salt tolerance exhibited by T. salsuginea. In this work, a comprehensive and detailed comparison of the response of the two species to high salinity was conducted at different times for up to ten days of salt treatment. T. salsuginea responded more rapidly and to a higher extent to adjust its metabolism and showed constitutive levels of anticipatory metabolism to salinity. T. salsuginea responded more rapidly in terms of maintaining light use efficiency, limiting the uptake of Na⁺, and increasing the accumulation of sugars and proline when exposed to salinity. T. salsuginea had much higher constitutive levels of metabolites, including malate, proline, and inositol, in comparison to A. thaliana. Interestingly, T. salsuginea showed a reduction in malate levels under salt treatment in contrast to A. thaliana. These results suggest that constitutive levels and the rapidity of the deployment of resistance mechanisms, together with metabolic plasticity, in response to salt stress are important adaptive traits for salt tolerance in plants. Full article

Prolonged grief disorder, also known as post-loss grief, was officially recognized in the International Classification of Diseases (ICD-11) after years of debate within the mental health community. However, while post-loss grief gained recognition, anticipatory and preparatory grief, which occur before a loss, have remained underexplored. Preparatory grief affects individuals nearing the end of life, while anticipatory grief impacts the loved ones of those who are about to die. These grief types are particularly prevalent among women, who are more vulnerable to their emotional and psychological challenges. The primary aim of this study was to investigate preparatory grief in women diagnosed with cancer and anticipatory grief in their loved ones, with the goal of developing management guidelines. The secondary objective was to identify protective factors, such as psychotherapeutic interventions and systemic support, to alleviate grief-related distress. This review synthesized evidence from the PubMed and Cochrane databases, covering studies from 1968 to 2020 and after the COVID-19 pandemic in 2023. The results revealed that anticipatory grief was common among loved ones, leading to increased emotional distress, while cancer patients experienced preparatory grief, facing both emotional and practical challenges. Both types of grief were associated with altered stress responses, such as lower diurnal cortisol levels. Psychotherapeutic interventions, particularly early and systemic psychotherapy, were found to effectively reduce symptoms of both anticipatory and preparatory grief, improving coping strategies and emotional well-being. The study concluded that empowering coping strategies and social support played key roles in enhancing emotional outcomes for both patients and their families. Full article

This paper proposes a theoretical model of meaning-making grounded in proprioceptive awareness and embodied imagination, arguing that human cognition is inherently multimodal, anticipatory, and sensorimotor. Drawing on Peircean semiotics, Lotman’s model of cultural cognition, and current research in neuroscience, we show that readiness to act—a proprioceptively grounded anticipation of movement—plays a fundamental role in the emergence of meaning, from perception to symbolic abstraction. Contrary to traditional approaches that reduce language to a purely symbolic or visual system, we argue that meaning arises through the integration of sensory, motor, and affective processes, structured by axial proprioceptive coordinates (vertical, horizontal, sagittal). Using Peirce’s triadic model of interpretants, we identify proprioception as the modulatory interface between sensory stimuli, emotional response, and logical reasoning. A study on skilled pianists supports this view, showing that mental rehearsal without physical execution improves performance via motor anticipation. We define this process as proprioceptive resonance, a dynamic synchronization of embodied states that enables communication, language acquisition, and social intelligence. This framework allows for a critique of linguistic abstraction and contributes to ongoing debates in semiotics, enactive cognition, and the origin of syntax, challenging the assumption that symbolic thought precedes embodied experience. Full article

Ethiopian pastoralist communities are facing a recurrent drought crisis that significantly affects the availability of water and pasture resources for communities dependent on livestock. The increasing intensity, duration and frequency of droughts in the pastoral community in Ethiopia have drawn the attention of multiple stakeholders and increased stakeholder debates on the role of early warning systems (EWSs) for anticipatory action to build climate resilience in the pastoral community. The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT), in collaboration with various partners, has developed an interactive web-based digital EWS to provide near real-time information on water and pasture conditions in pastoral and agro-pastoral regions of Ethiopia. In this study, a stakeholder analysis was conducted to identify key stakeholders, understand stakeholder needs, and facilitate collaboration towards sustaining the EWS. The stakeholder analysis revealed the roles and information needs of key actors engaged in livestock water and pasture monitoring and early warning systems aimed at improving the pastoral communities’ resilience. The analysis showed a pressing need for access to real-time information on water and pasture availability and seasonal climate forecasts by local communities for effective and optimal resources management. Local and national governments need similar data for evidence-based decision-making in resource allocation and policy development. International and non-governmental organizations (INGOs) require the same information for efficient humanitarian responses and targeted development interventions. The private sector seeks insights into market dynamics to better align production strategies with community needs. An EWS serves as a vital tool for development partners, facilitating improved planning, coordination, and impact assessment. It also emphasizes the importance of proactive collaboration among stakeholders, including local communities, government bodies, INGOs, and academic and research institutions. Enhanced communication strategies, such as partnerships with local media, are essential for timely information dissemination. Ultimately, sustained collaboration and adaptive strategies are crucial for optimizing the impact of an EWS towards improving the livelihoods and resilience of pastoral communities amid climate variability. Full article

This study introduces a novel framework with the use of extended reality (XR) systems in hydrology, particularly focusing on immersive visualization of hydrologic data for enhanced environmental planning and decision making. The study details the shift from traditional 2D data visualization methods in hydrology to more advanced XR technologies, including virtual and augmented reality. Unlike static 2D maps or charts that require cross-referencing disparate data sources, this system consolidates real-time, multivariate datasets, such as streamflow, precipitation, and terrain, into a single interactive, spatially contextualized 3D environment. Immersive information systems facilitate dynamic interaction with real-time hydrological and meteorological datasets for various stakeholders and use cases, and pave the way for metaverse and digital twin systems. This system, accessible via web browsers and XR devices, allows users to navigate a 3D representation of the continental United States. The paper addresses the current limitations in hydrological visualization, methodology, and system architecture while discussing the challenges, limitations, and future directions to extend its applicability to a wider range of environmental management and disaster response scenarios. Future application potential includes climate resilience planning, immersive disaster preparedness training, and public education, where stakeholders can explore scenario-based outcomes within a virtual space to support real-time or anticipatory decision making. Full article

Given the understandable patient and caregiver distress that often fluctuates across treatment, especially at diagnosis and with major disease milestones, it is important to prioritize interventions that are known to best support families during these key times of transition. Individualized and time-sensitive psychoeducation and anticipatory guidance are effective interventions in reducing distress and fostering adaptive coping across the cancer trajectory and are a standard for the psychosocial care of children with cancer and their families. Patient education materials have proven to be a flexible, accessible, cost-effective, and easily adaptable tool for delivering these interventions to this population. Moreover, within the field, there has been a call to action for the inclusion of patients and families in the development of research study design and clinical programming, recognizing them as the experts of their own experiences. This commentary aims to explore how patients and families can be actively involved in the creation, assessment, and implementation of patient education materials, fostering a collaborative partnership between families and clinicians. We provide detailed examples of this collaboration in the creation of patient education materials focused on promoting coping at diagnosis, supporting siblings and assisting with social reintegration at the end of treatment, promoting responsive caregiving for young children, and supporting caregiver coping through the creation of a podcast. Ultimately, this commentary seeks to emphasize the importance of partnering with patients and families to ensure their voices remain central to intervention development and implementation. Full article

Firearm shooting performance training rightfully focuses on shooting accuracy; however, additional foci should include decision processing speed and reaction time associated with decision making to avoid reaction-only based shooting responses. While advancements in realistic training environments attempt to mimic “real-world” situations, many remain largely anticipatory or subject to a speed–accuracy trade-off (SAT). The purpose of this brief field trial was to demonstrate the feasibility of a random-action target system (RATS) on participants’ shooting performance (i.e., accuracy, omission, and commission rates) among a convenience sample of six retired police officers and competitive shooters (age range: 45–58 years, mean age = 52.5 ± 5.89). Observational data were gathered from a single-day, three-round trial to test shooting accuracy and shooting errors when shooters were unable to anticipate target appearance location and target exposure speed. In Trial 1, the target exposure time was 0.5 s, which increased to 0.7 s in Trial 2, and decreased back to 0.5 s in Trial 3. Shooting accuracy generally increased, while omission and commission generally decreased, when shooters were presented with targets exposed for longer durations. From Trial 1 to Trial 3 (both trials with 0.5 s target exposures), shooters showed higher median accuracy rates, lower median omission rates, and lower median commission rates. Findings suggest that a non-anticipatory, RATS holds promise for improving shooting performance and offset SAT among shooters with firearm experience. However, additional trials are needed with the RATS to replicate these findings among a larger and more diverse set of participants, who train with the RATS consistently, over longer durations. Full article