Simple Action Research Articles

Effects of Sitting Baduanjin Exercises on Cognitive Function, Attention, and Muscle Strength among Patients with Mild Cognitive Impairment

ABSTRACT Purpose Sitting Baduanjin exercises can be effective in treating mild cognitive impairment (MCI). However, evidence on effectiveness of sitting Baduanjin exercises is lacking. This study investigated the effects of sitting Baduanjin exercises on cognitive function, attention, and muscle strength in patients with MCI. Design Quasi-experimental. Methods The participants were assigned to the experimental (n = 12) or comparison group (n = 12). The experimental group performed sitting Baduanjin exercises three times weekly for 40–50 minutes per session for 12 weeks, while the comparison group maintained their usual routine and attended health-related education. The two groups’ cognitive function and attention were assessed through a questionnaire and their muscle strength was measured at weeks 0, 9, and 13. Findings The experimental group showed significant improvements in cognitive function, attention, and muscle strength in the right shoulder anterior flexor; however, the left shoulder anterior flexor group showed no obvious improvements. Conclusion Sitting Baduanjin exercises feature simple actions, are convenient, and have positive effects on improving cognitive function, attention, and muscle strength in patients with MCI. Clinical evidence Baduanjin exercises are suitable for long-term community frontline care services. Early intervention with this exercise program may prevent healthy older people or those with health issues from progressing to dementia.

Cooperative Advisory Residual Policies for Congestion Mitigation

Fleets of autonomous vehicles can mitigate traffic congestion through simple actions, thus improving many socioeconomic factors such as commute time and gas costs. However, these approaches are limited in practice as they assume precise control over autonomous vehicle fleets, incur extensive installation costs for a centralized sensor ecosystem, and also fail to account for uncertainty in driver behavior. To this end, we develop a class of learned residual policies that can be used in cooperative advisory systems and only require the use of a single vehicle with a human driver. Our policies advise drivers to behave in ways that mitigate traffic congestion while accounting for diverse driver behaviors, particularly drivers’ reactions to instructions, to provide an improved user experience. To realize such policies, we introduce an improved reward function that explicitly addresses congestion mitigation and driver attitudes to advice. We show that our residual policies can be personalized by conditioning them on an inferred driver trait that is learned in an unsupervised manner with a variational autoencoder. Our policies are trained in simulation with our novel instruction adherence driver model, and evaluated in simulation and through a user study (N=16) to capture the sentiments of human drivers. Our results show that our approaches successfully mitigate congestion while adapting to different driver behaviors, with up to 20% and 40% improvement as measured by a combination metric of speed and deviations in speed across time over baselines in our simulation tests and user study, respectively. Our user study further shows that our policies are human-compatible and personalize to drivers.

Detection of semantic inconsistencies of motor actions: From language to praxis

Semantics of actions includes three types of knowledge: a) of the function of objects and tools, b) of the actions independently of the tools, and c) of the organization of simple actions in sequences. These types of knowledge might be structured as thematic roles into the semantics of actions. To test these hypothesis, 125 illustrations, divided into five conditions: i) Congruent (C), ii) Agent Inconsistent (AI), iii) Instrument Inconsistent (II), iv) Patient Inconsistent (PI), and v) Location Inconsistent (LI), were presented to 23 volunteers (50 % women), aged 20–25, who were asked to respond whether the image was congruent or incongruent. Electrical brain activity was recorded through 20 channels to obtain the event-related potentials (ERP) associated. Lower reaction times for II and PI than C, and a greater number of incorrect trials for C were found. A N300/N400 effect appeared for AI and LI conditions with respect to C. Finally, II and LI conditions present a deflected P600 in reference to C. These findings suggest semantic of actions is sensitive to thematic role manipulations and constitute evidence in favor of a semantic processing shared between visually observed praxis and words.

The Cruciality of Self-Determination on James Baldwin’s Bruce and the Spider

This paper exposes the crucial points of self-determination in the flash fiction of James Baldwin entitled Bruce and the Spider. The short story is a narrative that describes a brief moment in the life of the main character, Bruce, a Scottish king who was defeated many times by the King of England. When he saw a spider weaving its web in the corner of his retreat, this moment became symbolic of Bruce's emotional journey and self-determination within himself and the kingdom of Scotland. In this flash fiction, it is witnessed how Bruce struggles amid his repeated failures. Using qualitative research method, this article illustrates small changes in perception and courage and asks questions about how simple moments can have a profound impact on a person's life. This writing is supported by Self-Determination Theory as conceptualized by Richard M. Ryan and Edward L. Deci. Through explorative approach, the analysis includes how self-determination accompanies the reflections of the meanings behind simple actions and the importance of facing failure. In conclusion, it is self-determination through self-confidence, self-understanding, and self-reliance that directs King Bruce to defeat his despair, get back up, and beat back the English soldiers.

Multidimensional social influence drives leadership and composition-dependent success in octopus-fish hunting groups.

Collective behaviour, social interactions and leadership in animal groups are often driven by individual differences. However, most studies focus on same-species groups, in which individual variation is relatively low. Multispecies groups, however, entail interactions among highly divergent phenotypes, ranging from simple exploitative actions to complex coordinated networks. Here we studied hunting groups of otherwise-solitary Octopus cyanea and multiple fish species, to unravel hidden mechanisms of leadership and associated dynamics in functional nature and complexity, when divergence is maximized. Using three-dimensional field-based tracking and field experiments, we found that these groups exhibit complex functional dynamics and composition-dependent properties. Social influence is hierarchically distributed over multiscale dimensions representing role specializations: fish (particularly goatfish) drive environmental exploration, deciding where, while the octopus decides if, and when, the group moves. Thus, 'classical leadership' can be insufficient to describe complex heterogeneous systems, in which leadership instead can be driven by both stimulating and inhibiting movement. Furthermore, group composition altered individual investment and collective action, triggering partner control mechanisms (that is, punching) and benefits for the de facto leader, the octopus. This seemingly non-social invertebrate flexibly adapts to heterospecific actions, showing hallmarks of social competence and cognition. These findings expand our current understanding of what leadership is and what sociality is.

Rapid and Resilient LoRa Leap: A Novel Multi-Hop Architecture for Decentralised Earthquake Early Warning Systems.

We introduce a novel LoRa-based multi-hop communication architecture as an alternative to the public internet for earthquake early warning (EEW). We examine its effectiveness in generating a meaningful warning window for the New Zealand-based decentralised EEW sensor network implemented by the CRISiSLab operating with the adapted Propagation of Local Undamped Motion (PLUM)-based earthquake detection and node-level data processing. LoRa, popular for low-power, long-range applications, has the disadvantage of long transmission time for time-critical tasks like EEW. Our network overcomes this limitation by broadcasting EEWs via multiple short hops with a low spreading factor (SF). The network includes end nodes that generate warnings and relay nodes that broadcast them. Benchmarking with simulations against CRISiSLab's EEW system performance with internet connectivity shows that an SF of 8 can disseminate warnings across all the sensors in a 30 km urban area within 2.4 s. This approach is also resilient, with the availability of multiple routes for a message to travel. Our LoRa-based system achieves a 1-6 s warning window, slightly behind the 1.5-6.75 s of the internet-based performance of CRISiSLab's system. Nevertheless, our novel network is effective for timely mental preparation, simple protective actions, and automation. Experiments with Lilygo LoRa32 prototype devices are presented as a practical demonstration.

Urban design and pollution using AI: Implications for urban development in China

The primary aim of this study is to explore the role of AI in urban design and its potential to reduce pollution in Chinese cities. The study investigates how AI-driven urban planning tools can be applied to create more sustainable, efficient, and functional urban environments. PM2.5 and PM10 show high concentrations with peaks between 2014 and 2017, indicating simple pollution actions. Post-2017, there is a noticeable decline in pollution levels, possibly due to improved regulations or the global impact of the COVID-19 pandemic. Specific years, like 2016, show extreme spikes, possibly due to industrial activities or natural events. The overall trend suggests improved air quality and moderate to strong positive correlations exist between PM2.5 and PM10, NO2, SO2, and CO, indicating shared bases or co-occurrence. However, there is no significant correlation between PM2.5 and O3, suggesting different bases and behaviors. Bi-directional causality is observed between PM2.5 and PM10, PM2.5 and O3, PM2.5 and NO2, PM2.5 and SO2, and PM2.5 and CO. This mutual cause suggests interrelated impressive processes and shared bases. The results of the causality analysis suggest the existence of complex interactions, where high levels of pollution can predict changes in others. AI in urban design play vital role for identifying the most effective strategies for reducing pollution and helping to build more sustainable and functional urban environments in China.

Navigating ‘feel’: When hands touch sound effects

Holding and moving objects to create a sound effect requires a performer to navigate by feel, directing their listening from the solid (dried peas on a drumhead) to the imaginary (sea waves). The illusory properties of sound have long been exploited by sound effects performers for the purposes of Foley, silent cinema and theatre. While sound may provoke the imagination or emotional response of the audience, it also does its affective work on the performer operating the effect. In the moment of practice itself, sound binds to the object being manipulated, blurring the known boundaries of its physical properties. The Foley artist crosses a threshold between the tactility of the material and the dissolved representations of the intangible, as the sound itself feels like it is the material being manipulated. Simple hand actions become a gateway to the imaginary. This article considers the affective experience of creative bodily guided soundmaking, and how the successful operation of a sound effect requires the performer to deliberately navigate between modes of listening, attuning their movements and engaging with a perceptual space where things, while making sound, are no longer what they seem to be. Focusing on sound effects beyond the screen allows for an exploration of the aesthetic, dramatic and syncretic in real-world experiences of sound and movement.

Dynamic risk assessment of Uncertain Random System considering operator's simple emergency-stop action in short time window

Human-machine systems can be considered as typical Uncertain Random Systems (URS). In human-machine systems, operator's simple emergency-stop actions act as a vital soft barrier. Conventional Human Reliability Analyses face challenges in evaluating operator's simple emergency-stop action due to their static characteristics, incompatibility with short time windows, and problems posed by small samples. This paper provides a novel solution to risk assessment of human-machine systems involving operator's simple emergency-stop mechanism. Specifically, an evaluation method of operator's simple emergency-stop action is established, where human cognition is decomposed according to its temporal and logical dimensions, key indicators of human sub-cognition are evaluated, and uncertainty theory is used to integrate these indicators. The output of proposed method is uncertainty of operator's behavior (UOB), which can offer more information than traditional Human Error Probability (HEP) and can be readily converted into uncertainty of human error. Further, a precise simulation method for dynamic risk assessment of Uncertain Random Systems is developed, in which the integration of the UOB is achieved. A case study demonstrates the effectiveness of the proposed methods, and its results show that the proposed methods can clearly reflect the differences in system risk under short time window conditions that have minor distinctions.

Bionic light-responsive hydrogel actuators with multiple-freedom motions in water environments

Soft actuators with biomimetic behavior have widely been utilized in intelligent robotics and artificial muscles. Herein, tannic acid (TA) non-covalently modified and γ-methacrylic trimethoxysilane (MPS) covalently modified MXene (MPS-TA-MXene) are incorporated into a poly(n-isopropylacrylamide-polyacrylamide) (PNIPAM-PAM) copolymer hydrogel to yield a light-responsive hydrogel nanocomposite, denoted as MNA. TA effectively preserves the surface characteristics of MXene while the double bonds in MPS form covalent bonding between MXene and PNIPAM-PAM copolymer, ensuring uniform dispersion of MPS-TA-MXene in MNA hydrogel. Under exposure to ultraviolet light, the resulting MNA hydrogel actuators with nematode- or starfish-shaped exhibit not only bending capabilities in various directions and angles but also demonstrate remarkable multiple-freedom rolling behavior in water environments due to their volume shrinkage induced by the phase transition of MNA hydrogel. Overall, the proposed simply assembled MNA hydrogel actuators with multiple and continuous bionic motions, distinguishing them from conventional single soft actuators limited to bending in one specific direction or performing a simple singular action of rolling, look promising for use in underwater exploration.

Anticipation, agency and aging-conditions for making movement irresistible.

This article describes an approach to developing and maintaining interpersonal agency through guided movement and responsive technologies. Making Movement Irresistible (MMI), considered conditions for developing a digital, online and wearable intervention that could make the act of movement irresistible for older residents in care, and encourage improvisational and social interactions. Working within a co-design framework, we combined making material objects and moving together as a method of examining the efficacy of human to human, and human to technology relationships to cultivate agency. Given that movement as performance is frequently not practiced or uncomfortable, we invited a variety of experts as our co-designers to notice the nuances of movement that interested them and to document these using drawing, writing and visuals. This documentation was gathered regularly in journals as the workshops progressed, leading to a coherent capture of data as it emerged. This data allowed us to attribute value to how simple actions could become a conduit for more ambitious, exploratory interactions. Our playful methods afforded the participation of co-designers, enabling us to situate our proposed intervention within a relational and social, rather than medical model, of ageing. Making movement do-able and relational, so that it can be shared and extended with a partner or carer, informed the idea to design a wearable device that could detect movement variability, resulting in a prototype, named emitts®. The device makes use of the hand as way in to accessing whole body interaction. Our work with responsiveness of visual feedback avoided deterministic targets, as with no two movements being identical, the reported problem of compliance with repetitive tasks could be reduced. The technology foregrounded movement that was capricious and improvisational, offering new modes of artistic practice and engagement through play and performance. The case we describe highlights the importance of understanding the conditions that augment social interaction, rather than specifying design criteria for determining interaction. The longer-term health benefits of our intervention have yet to be measured, however, our collaboration has revealed how interpersonal agency emerges when we socially, aesthetically, and physiologically stimulate movement, making it irresistible where there may otherwise be resistance.

Agroecology, slow food and sustainable development goals (SDGs): resilience of agro-food systems, combat hunger, and local governance

The Sustainable Development Goals (SDGs), transcending their prescribed targets and actions, propose a critical reflection on global food production and consumption patterns. These inquiries foster the promotion of resilient agri-food systems, with Agroecology identified as a pragmatically viable alternative for achieving the advocated goals. The scope of this article is to discuss these intersections, demonstrating that simple actions such as valuing local products, as advocated by Slow Food, can strengthen relationships and networks around food, promoting food security, preservation of knowledge, practices, traditions, and biodiversity, as well as the sense of belonging, improvement of quality of life, sustainable development, and local governance. Methodologically, this research is qualitative, adopting a bibliographical approach and employing a literature review to contextualize and reflect the problem, anchored in the Agroecology domains, SDGs, and the paradigm proposed by the Slow Food movement. This study substantially contributes to understanding the intricate relationships between the SDGs, agri-food systems, and Agroecology. By emphasizing the importance of seemingly simple practices, such as valuing local products, the article highlights the imperative of holistic and sustainable approaches to achieve broader sustainable development goals guided by the principles of “well-being.”

Students’ Grammatical Mistakes on the Use of Language Features in Composing Narrative Text

A narrative text with several grammatical and linguistic aspects is one of the texts learned in senior high school. In fact, according to the researcher's prior observation, students faced numerous challenges when attempting to write it, especially grammatical mistakes in using language features. This study aims to detect grammatical errors in the utilization of language elements in narrative texts produced by students, as well as to determine the underlying reasons contributing to these errors. The recent research employed a descriptive qualitative methodology. Eight of the eleventh-grade students studying Online Business and Marketing major in SMK Negeri 1 Kota Sorong have been selected as the participants in this research. Due to the COVID-19 pandemic situation which restricted social interactions, only those students than could be reached out to gather data. The data was derived from a writing exam and a semi-structured interview. Upon analyzing the student's writing, it was discovered that they made errors in utilizing the simple past tense and action verbs. Simultaneously, the interview data indicated that the causes contributing to grammatical errors in using language features in this study were limitations, lack of attention, and carelessness. This research finding implied that the teacher must identify the most effective technique to engage the student's attention and enable them to concentrate on acquiring language skills for future use in creating narrative texts.

Investigating the impact of early deafness on learned action-effect contingency for action linked to peripheral sensory effects

Investigating peripheral visual processing in individuals with early auditory deprivation is a critical research area in the field of neuroscience, since it helps understanding the phenomenon of sensory adaptation and brain plasticity after sensory loss. Prior research has already demonstrated that the absence of auditory input, which is crucial to detect events occurring out of the central egocentric visual space, leads to an improved processing of visual and tactile stimuli occurring in peripheral regions of the sensory space. Nevertheless, no prior studies have explored whether such enhanced processing also takes place within the domain of action, particularly when individuals are required to perform actions that produce peripheral sensory outcomes. To test this hypothesis, we recruited 15 hearing (31 ± 3.3 years) and 15 early deaf adults (42 ± 2.6 years) for a neuro-behavioral experiment involving: 1) a behavioral task where participants executed a simple motor action (i.e., a button press) and received a visual feedback either in the center or in a peripheral region of the visual field, and 2) the electrophysiological recording of brain electrical potentials (EEG). We measured and compared neural activity preceding the motor action (the readiness potentials) and visual evoked responses (the N1 and P2 ERP components) and found that deaf individuals did not exhibit more pronounced modulation of neural responses when their motor actions resulted in peripheral visual stimuli compared to their hearing counterparts. Instead they showed a reduced modulation when visual stimuli were presented in the center. Our results suggest a redistribution of attentional resources from center to periphery in deaf individuals during sensorimotor coupling.

Innovative strategy for the facile construction of active multifunctional coating on inert thermal insulation surface

Ethylene propylene diene monomer rubber is highly attractive as a thermal insulation material for solid rocket motors but is plagued by its inherent low wettability. Existing methods have been used to solve this problem by manually or mechanically sanding the surface, which is environmentally hazardous. Herein, a multifunctional composite coating is constructed on the surface of inert thermal insulation materials using a two-step low temperature plasma surface treatment via an efficient hydrogen-bonding assembly strategy. The resultant composite coating exhibits excellent adhesion to the inert thermal insulation substrate. Benefitting from this, the coating retained its superhydrophilicity after 80 abrasion cycles and 12 h of agitation scrubbing with saturated salt water. Due to the superhydrophilicity of the coating, a self-cleaning effect for oils of different viscosities on the surface can be achieved by the simple action of water. Besides the adiabatic performance tests showed that the average top surface temperature of the coated thermal insulation was 30.9 °C lower than that of the original thermal insulation. Char residue analysis showed that the coating formed a more complete char layer at high temperatures, resulting in improved adiabatic performance. Our work would afford a new frontier to fabricate solid rocket motor thermal insulation materials with excellent surface comprehensive properties in a simple, eco-friendly and sustainable way, opening new possibilities for the advancement of high-performance inert materials.

Discrete Space Deep Reinforcement Learning Algorithm Based on Support Vector Machine Recursive Feature Elimination

Algorithms for training agents with experience replay have advanced in several domains, primarily because prioritized experience replay (PER) developed from the double deep Q-network (DDQN) in deep reinforcement learning (DRL) has become a standard. PER-based algorithms have achieved significant success in the image and video domains. However, the exceptional results observed in images and videos are not as effective in many domains with simple action spaces and relatively small states, particularly in discrete action spaces with sparse rewards. Moreover, most advanced techniques may improve sampling efficiency using deep learning algorithms rather than reinforcement learning. However, there is growing evidence that deep learning algorithms cannot generalize during training. Therefore, this study proposes an algorithm suitable for discrete action space environments that uses the sample efficiency of PER based on DDQN but incorporates support vector machine recursive feature elimination (SVM-RFE) without enhancing the sampling efficiency through deep learning algorithms. The proposed algorithm exhibited considerable performance improvements in classical OpenAI Gym environments that did not use images or videos as inputs. In particular, simple discrete space environments with reflection symmetry, such as Cart–Pole, exhibited a faster and more stable learning process. These results suggest that the application of SVM-RFE, which leverages the orthogonality of support vector machines (SVMs) across learning patterns, can be appropriate when the data in the reinforcement learning environment demonstrate symmetry.

Higher Onset of Periprosthetic Joint Infections in Patients With Teeth Compared to Those Without Teeth.

Bacteria can enter the bloodstream through simple actions such as brushing teeth, flossing, and even chewing food, increasing the chance of hematogenous seeding of prosthetic joints. Antibiotics before dental work in patients with orthopedic hardware is a topic of debate because of concerns for antibiotic resistance. Patients with dentures theoretically avoid this risk due to the lack of teeth and their maintenance. Most periprosthetic joint infections (PJIs) that occur in the first six months after surgery are due to wound infection, whereas late PJIs are more commonly caused by hematogenous seeding. Charts from patients who received primary total joint arthroplasty were interrogated for the condition of their teeth at the time of operation. If the patient had a PJI, the time from surgery and the organism responsible were noted. Multivariate linear regressions were performed for statistical analysis to compare rates of dental status, infection, comorbidities, and demographics. From the 1,500 charts reviewed, patients with teeth and edentulous had similar rates of comorbidities. PJI patients had higher rates of chronic kidney disease than patients who did not have the infection. The overall rate of infections in patients with teeth was 2.14%, close to the national average. The rate of infection in patients without teeth was 0.78%. Patients with teeth have a higher rate of infection one month or longer from surgery than edentulous patients. There was an increased infection rate in patients with teeth at six months and greater since the primary total joint arthroplasty. The organisms responsible for many of the PJIs are commonly found in the mouth of humans. Having teeth is a potential risk factor for late PJI.

A sensory-motor theory of the neocortex.

Recent neurophysiological and neuroanatomical studies suggest a close interaction between sensory and motor processes across the neocortex. Here, I propose that the neocortex implements active predictive coding (APC): each cortical area estimates both latent sensory states and actions (including potentially abstract actions internal to the cortex), and the cortex as a whole predicts the consequences of actions at multiple hierarchical levels. Feedback from higher areas modulates the dynamics of state and action networks in lower areas. I show how the same APC architecture can explain (1) how we recognize an object and its parts using eye movements, (2) why perception seems stable despite eye movements, (3) how we learn compositional representations, for example, part-whole hierarchies, (4) how complex actions can be planned using simpler actions, and (5) how we form episodic memories of sensory-motor experiences and learn abstract concepts such as a family tree. I postulate a mapping of the APC model to the laminar architecture of the cortex and suggest possible roles for cortico-cortical and cortico-subcortical pathways.

Visual detection of misfolded alpha-synuclein and prions via capillary-based quaking-induced conversion assay (Cap-QuIC)

Neurodegenerative protein misfolding diseases impact tens of millions of people worldwide, contributing to millions of deaths and economic hardships across multiple scales. The prevalence of neurodegenerative disease is predicted to greatly increase over the coming decades, yet effective diagnostics for such diseases are limited. Most diagnoses come from the observation of external symptoms in clinical settings, which typically manifest during relatively advanced stages of disease, thus limiting potential therapeutic applications. While progress is being made on biomarker testing, the underlying methods largely rely on fragile and expensive equipment that limits their point-of-care potential, especially in developing countries. Here we present Capillary-based Quaking Induced Conversion (Cap-QuIC) as a visual diagnostic assay based on simple capillary action for the detection of neurodegenerative disease without necessitating expensive and complex capital equipment. We demonstrate that Cap-QuIC has the potential to be a detection tool for a broad range of misfolded proteins by successfully distinguishing misfolded versus healthy proteins associated with Parkinson’s disease (α-synuclein) and Chronic Wasting Disease (prions). Additionally, we show that Cap-QuIC can accurately classify biological tissue samples from wild white-tailed deer infected with Chronic Wasting Disease. Our findings elucidate the underlying mechanism that enables the Cap-QuIC assay to distinguish misfolded protein, highlighting its potential as a diagnostic technology for neurodegenerative diseases.

The Einstein–Hilbert action for entropically dominant causal sets

In the path integral formulation of causal set quantum gravity, the quantum partition function is a phase-weighted sum over locally finite partially ordered sets, which are viewed as discrete quantum spacetimes. It is known, however, that the number of ‘layered’ sets—a class of causal sets that look nothing like spacetime manifolds—grows superexponentially with the cardinality n, giving an entropic contribution that can potentially dominate that of the action. We show here that in any dimension, the discrete Einstein–Hilbert action for a typical K-layered causal set reduces to the simple link action to leading order in n. Combined with earlier work, this completes the proof that the layered sets, although entropically dominant, are very strongly suppressed in the path sum of causal set quantum gravity whenever the discreteness scale is greater than or equal to a (mildly dimension-dependent) order one multiple of the Planck scale.