Goal Of Activity Research Articles

Qualitatively Analyzing Optimization Objectives in the Design of HPC Resource Manager

A correct evaluation of scheduling algorithms and a good understanding of their optimization criteria are key components of resource management in HPC. In this work, we discuss bias and limitations of the most frequent optimization metrics from the literature. We provide elements on how to evaluate performance when studying HPC batch scheduling. We experimentally demonstrate these limitations by focusing on two use-cases: a study on the impact of runtime estimates on scheduling performance, and the reproduction of a recent high-impact work that designed an HPC batch scheduler based on a network trained with reinforcement learning. We demonstrate that focusing on quantitative optimization criterion (“our work improves the literature by X%”) may hide extremely important caveat, to the point that the results obtained are opposed to the actual goals of the authors. Key findings show that mean bounded slowdown and mean response time are hazardous for a purely quantitative analysis in the context of HPC. Despite some limitations, utilization appears to be a good objective. We propose to complement it with the standard deviation of the throughput in some pathological cases. Finally, we argue for a larger use of area-weighted response time, that we find to be a very relevant objective.

Applying Multi-Task Deep Learning Methods in Electricity Load Forecasting Using Meteorological Factors

The steady rise in carbon emissions has significantly exacerbated the global climate crisis, posing a severe threat to ecosystems due to the greenhouse gas effect. As one of the most pressing challenges of our time, the need for an immediate transition to renewable energy is imperative to meet the carbon reduction targets set by the Paris Agreement. Buildings, as major contributors to global energy consumption, play a pivotal role in climate change. This study diverges from previous research by employing multi-task deep learning techniques to develop a predictive model for electricity load in commercial buildings, incorporating auxiliary tasks such as temperature and cloud coverage. Using real data from a commercial building in Taiwan, this study explores the effects of varying batch sizes (100, 125, 150, and 200) on the model’s performance. The findings reveal that the multi-task deep learning model consistently surpasses single-task models in predicting electricity load, demonstrating superior accuracy and stability. These insights are crucial for companies aiming to enhance energy efficiency and formulate effective renewable energy procurement strategies, contributing to broader sustainability efforts and aligning with global climate action goals.

Evaluation of Teaching Performance of Dental College Lecturers in India

The actual goal of teaching dental students is to help them learn important skills and enhance their knowledge to become proficient doctors in the future and offer proper care to patients. However, dental teachers do not acquire formal training as a teacher. It is important to assess the teaching performance of the dental lecturers for their professional growth and student success. Further, peer evaluation is also significant as it provides benefits to students and lecturers as well. Hence, the study focuses on determining the teaching performance of dental lecturers in Tamil Nadu, India. The data from 20 participants has been collected using peer observation. With the help of a thematic table, significant results have been determined, indicating the different characteristics of the well-prepared, partially prepared, and not-prepared lecturers.

Practice-Based Implementation Network: Behavioral Health Technician Optimization Pilot Lessons Learned.

Between June 2021 and December 2022, the Practice-Based Implementation (PBI) Network conducted a pilot to study the optimization of behavioral health technicians (BHTs) within military behavioral health (BH) care system specialty BH clinics. Behavioral health technicians are paraprofessionals found in all branches of the military, and with training across a variety of clinic functions. Behavioral health technicians support BH specialty providers in many clinic functions (i.e., administrative, case management, clinical, and outreach). The primary aim of the BHT optimization pilot was to increase BHTs' involvement in clinical care. Four military BH outpatient clinics participated in the BHT optimization pilot. Participants from the 4 clinics included 12 BHTs, 3 providers, 3 internal facilitators, and 3 dual-role providers/internal facilitators. The pilot asked each clinic to assess their BHT utilization needs, and then barriers and facilitators to BHT optimization were addressed by creating site-specific BHT optimization plans. The degree to which clinic optimization of BHTs impacts provider workload, clinic capability or capacity, and patient access to evidence-based care could not be determined during the BHT optimization pilot. However, individualized clinic BHT optimization plans and strategies appeared to be feasible and acceptable methods for military health system BH clinics to optimize BHTs' clinical skills. Lessons learned from this pilot included that: (1) clinics should consider establishing and maintaining action plans with specific, actionable goals for use of BHTs, and (2) BHT supervision, training, and clinic processes supporting optimization should be prioritized despite time constraints. Overall, individualized clinic BHT optimization plans and strategies appear to be feasible and acceptable methods for military health system BH clinics to optimize BHTs' clinical skills.

Dance of two brains: Interval subdivision in alternated condition enhances resistance to interference by others

The accomplishment of interpersonal sensorimotor synchronization is a challenging endeavor because it requires the achievement of a balance between accurate temporal control within individuals and smooth communication between them. This raises a critical question: How does the brain comprehend and process the perceptual information of others to guarantee accurate temporal control of action goals in a social context? A joint synchronization - continuation tapping task was conducted together with varying relative phases (0°/180°) and intervals of tempos (400 ms/800 ms/1600 ms) while neural data was collected using fNIRS (functional near-infrared spectroscopy). Individuals showed better behavioral performance and greater interpersonal brain synchronization(IBS) in the left dorsolateral prefrontal cortex at alternated condition (180° relative phase) compared to symmetric condition (0° relative phase), suggesting that the individual can better maintain behavioral performance and show improved IBS when the partner taps between the individual's gaps. Meanwhile, in most levels of alternated condition, IBS is inversely proportional to interference from partner, implying the counteraction of IBS against interference from others. In addition, when the interval of tempo was 1600 ms, behavioral performance showed a sharp decline, accompanied by a decrease in IBS, reflecting that IBS in SMS reflects effective information exchange between individuals rather than ineffective interference with each other. This study provides insight into the mechanisms underlying sensorimotor synchronization between individuals.

Localising the Global Goal on Adaptation through intersectional thinking

This viewpoint explores how intersectional thinking can help localise the Global Goal on Adaptation (GGA) to promote equity and justice in climate adaptation. Localising the GGA is essential for translating global objectives into actionable strategies at the local level. Adaptation goalsetting and current adaptation measurement approaches are hindered by the complexity of establishing shared metrics, the myopic focus on compliance and reporting, and the neglect of the dynamic, context-specific nature of adaptation processes. By incorporating intersectional thinking, we argue for a more nuanced approach that considers the compounded sources of vulnerability, especially in urban areas, where marginalised groups are disproportionately affected by climate impacts. We apply an Intersectional Climate Justice framework to guide the localisation of the GGA throughout the adaptation policy cycle, from impact, vulnerability, and risk assessment, to planning, implementation, and measurement. Embedding intersectional thinking throughout the GGA’s adaptation policy cycle aligns global goals with local realities, enabling local actors to develop more comprehensive, context-specific strategies that address the needs and priorities of vulnerable communities. We also highlight the potential of intersectional climate justice to bridge climate action and broader development goals, ultimately fostering more equitable and just futures.

Individual differences and motor planning influence self-recognition of actions.

Although humans can recognize their body movements in point-light displays, self-recognition ability varies substantially across action types and participants. Are these variations primarily due to an awareness of visually distinct movement patterns, or to underlying factors related to motoric planning and/or individual differences? To address this question, we conducted a large-scale study in self-action recognition (N = 101). We motion captured whole-body movements of participants who performed 27 different actions across action goals and degree of motor planning. After a long delay period (~ 1 month), participants were tested in a self-recognition task: identifying their point-light action amongst three other point-light actors performing identical actions. We report a self-advantage effect from point-light actions, consistent with prior work in self-action recognition. Further, we found that self-recognition was modulated by the action complexity (associated with the degree of motor planning in performed actions) and individual differences linked to motor imagery and subclinical autism and schizotypy. Using dynamic time warping, we found sparse evidence in support of visual distinctiveness as a primary contributor to self-recognition, though speed distinctiveness negatively influenced self-recognition performance. Together, our results reveal that self-action recognition involves more than an awareness of visually distinct movements, with important implications for how the motor system may be involved.

Применение нейронных сетей в образовательном процессе студентов вуза

The article is devoted to the analysis and study of statistics on the relevance of the use of neural networks in the educational process of students. Based on the results of the survey, which was attended by 94 students of the Omsk branch of the Financial University under the Government of the Russian Federation of various training areas, the following conclusions were made: the degree of relevance of the use of neural networks in a modern university according to a 5-point system of at least 4 points was estimated by about 57.4% of respondents. The actual goals of using neural networks were: improving the quality of the workspace (60.6%), reducing the duration of the workflow (59.6%) and assistance in writing papers (48.9%). It is worth noting that according to the results of the survey, Shazam became the most popular neural network using artificial intelligence. 71.3% of respondents use this neural network to facilitate the search for the right musical composition. The results of the study allow us to conclude that it is necessary to introduce neural networks into the educational plan of universities to facilitate the educational process of students. As well as a superficial study, to understand the general structure and relevance of the use of neural networks.

Sensitivity and specificity of the action observation network to kinematics, target object, and gesture meaning.

Hierarchical models have been proposed to explain how the brain encodes actions, whereby different areas represent different features, such as gesture kinematics, target object, action goal, and meaning. The visual processing of action-related information is distributed over a well-known network of brain regions spanning separate anatomical areas, attuned to specific stimulus properties, and referred to as action observation network (AON). To determine the brain organization of these features, we measured representational geometries during the observation of a large set of transitive and intransitive gestures in two independent functional magnetic resonance imaging experiments. We provided evidence for a partial dissociation between kinematics, object characteristics, and action meaning in the occipito-parietal, ventro-temporal, and lateral occipito-temporal cortex, respectively. Importantly, most of the AON showed low specificity to all the explored features, and representational spaces sharing similar information content were spread across the cortex without being anatomically adjacent. Overall, our results support the notion that the AON relies on overlapping and distributed coding and may act as a unique representational space instead of mapping features in a modular and segregated manner.

초등학생 방과 후 학교 영어교육 참여자 특성이 교육 목표에 미치는 영향 연구

This study aims to empirically examine the impact of after-school English education on elementary school students' self-concept, emotional intelligence, and self-expression concerning the objectives of after-school education. The analysis revealed that the self-concept and emotional intelligence of elementary students participating in after-school English education programs had a meaningful impact on the actual after-school education goals. Students with high self-concept and emotional intelligence were more successful in achieving English education goals through enhanced self-expression abilities. These findings indicate that psychological factors should be considered when designing after-school English education programs to boost students’motivation and achievement in learning English. The study demonstrates that self-concept and emotional intelligence can help achieve educational goals through the mediating effect of self-expression, indicating the importance of developing more in-depth educational strategies in the educational field. This study analyzes the effects of after-school English education on elementary school students in China. As the research was conducted within a specific educational environment in China, there are limitations in generalizing the results to other regions or educational contexts.

The importance of road safety inspection for the improvement of pedestrian safety in traffic

Road safety inspection is a modern tool for improving road safety, that is, a preventive tool that is applied on roads in use. The goal of preventive action in road safety is to improve road safety, through reducing the number and consequences of traffic accidents. The road safety inspection involves the analysis of general data about the section, the analysis of traffic accidents, but also the analysis of specific road defects. 11 specific elements are analyzed, including vulnerable road users, including pedestrians, cyclists and motorcyclists. Vulnerable road users are particularly at risk because in the event of a traffic accident, they suffer more severe consequences because their body is not physically protected. This paper shows the importance of road safety inspections for the improvement of pedestrian safety in traffic.

Two distinct networks for encoding goals and forms of action: An effective connectivity study

Goal-directed actions are characterized by two main features: the content (i.e., the action goal) and the form, called vitality forms (VF) (i.e., how actions are executed). It is well established that both the action content and the capacity to understand the content of another's action are mediated by a network formed by a set of parietal and frontal brain areas. In contrast, the neural bases of action forms (e.g., gentle or rude actions) have not been characterized. However, there are now studies showing that the observation and execution of actions endowed with VF activate, in addition to the parieto-frontal network, the dorso-central insula (DCI). In the present study, we established-using dynamic causal modeling (DCM)-the direction of information flow during observation and execution of actions endowed with gentle and rude VF in the human brain. Based on previous fMRI studies, the selected nodes for the DCM comprised the posterior superior temporal sulcus (pSTS), the inferior parietal lobule (IPL), the premotor cortex (PM), and the DCI. Bayesian model comparison showed that, during action observation, two streams arose from pSTS: one toward IPL, concerning the action goal, and one toward DCI, concerning the action vitality forms. During action execution, two streams arose from PM: one toward IPL, concerning the action goal and one toward DCI concerning action vitality forms. This last finding opens an interesting question concerning the possibility to elicit VF in two distinct ways: cognitively (from PM to DCI) and affectively (from DCI to PM).

Promoting collective precycling behavior: results from a group intervention with Berlin households in Germany.

To tackle the global waste crisis, there is an urgent need for decisive and joint action at multiple levels. The collective behavior of a community could make a significant contribution. This paper presents the results of a field experiment designed to promote packaging waste prevention - called precycling - in a newly formed community setting, in Berlin, Germany. The aim was to examine the effect of the intervention on precycling and to examine the underlying social identity processes. Over a four-week period, 132 participants from 96 different households digitally received a combination of different interventions, that were theoretically informed by the Social Identity Model of Pro-Environmental Action (SIMPEA). Households were assigned to two intervention groups and a waiting control group. Data was collected before, immediately after and four months after the intervention to assess the impact of the intervention using multilevel models. After the intervention, the overall precycling behavior increased significantly, but not as a result of the different group conditions. In the more comprehensive intervention group, which included social interaction and behavioral experimentation, the community identification was strengthened and the reuse behavior, as a subset of precycling, increased. While a number of social identity processes (collective efficacy beliefs, having a precycling action goal, crisis appraisal, and sufficiency attitudes) were found to positively predict the precycling behavior, surprisingly, the predictive power of social norms and ingroup identification could not be confirmed. Overall, the presented community intervention promoted precycling. However, in this dynamic real-world setting, not all intervention elements worked as expected. The pitfalls and opportunities of this intervention are discussed, and ideas for translating the results into everyday precycling activities are presented.

Developing an Online Health Community Platform for Facilitating Empowerment in Chronic Disease Prevention and Health Promotion.

This study aimed to develop an online health community platform for facilitating the empowerment of people with chronic diseases dwelling in the community regarding disease prevention and health promotion. The user-centered design approach included four main steps: (1) identifying the health problems and needs of target users, (2) developing the content of the platform, (3) constructing the platform, and (4) pilot testing, refinement, and finalization. An online health community platform available both in a mobile application and a Web-enabled application has been launched to facilitate empowerment and self-management by people with chronic conditions. The main components of the application comprised (1) screening for chronic diseases and health problems, (2) setting personal goals for health promotion and action planning to achieve the goals themselves, (3) offering an online health community with shared group goals that help users engage with their peers to attain their goals, and (4) creating one's own online health community and inviting others to participate. The platform has the potential to encourage people with chronic conditions to proactively engage in their own health promotion. Future studies are needed to determine the impact of the application on self-management and empowerment for its users.

Health and Safety Education for Painting Workers in Small Companies to Make Them Aware That Paint Is "Dangerous and Harmful".

Workers in painting companies may be unaware that the paints they handle have adverse health effects. The present study explored the factors associated with workers' perception of paints as "dangerous and harmful". A questionnaire survey and interviews were conducted with workers engaged in painting operations in small-sized painting companies (fewer than 50 employees) in northern Kyushu and Yamaguchi prefectures. Safety and health education methods making workers perceive paint as "dangerous and harmful" were clarified. Fisher's exact test and logistic regression analysis were used for the survey and hierarchical cluster analysis for the interviews. The factor "Hazard prediction activity (KY Activity)", gender, and job position were identified as factors that make workers perceive paint as "dangerous and harmful". Based on the interview results, "KY Activity" was a keyword and a standardized safety and health activity. Before work, workers gather in a small group to discuss the dangers and hazards of paint, share information, establish action goals, and confirm safety measures. The questionnaire identified "KY Activity" as a factor influencing the workers' perception of paint as "dangerous and harmful". "KY Activity," also extracted from the interviews, is an effective health and safety education method for teaching workers in small-sized painting companies that paint is "dangerous and harmful".

Market or Community? An Institutional Logics Interpretation of how MNE Subsidiaries Respond to Mandated Social Innovation in India

Despite growing concern in the social innovation (SI) literature about the tackling of grand challenges, our understanding of the role of multinational enterprises (MNEs) remains in its infancy. This article examines foreign MNE subsidiaries’ SI investments focusing on United Nations’ Sustainable Development Goals (UNSDGs) in host countries. Using financial data from large, listed subsidiaries of foreign MNEs operating in India, along with hand-collected data from firms’ disclosures of corporate social responsibility (CSR) activity for five years starting in 2015, we utilise the externalities framework propounded by Montiel et al. (2021). This neatly translates the 17 UNSDGS into actionable goals to examine the efforts of foreign MNE subsidiaries in increasing positive externalities as opposed to reducing negative externalities via SI-related investment in host countries. The study also evaluates the effects of the local embeddedness of the foreign MNE subsidiaries on SI investment. We find that MNE subsidiaries tend to favour increasing positive externalities as compared to reducing negative externalities through their SI investments. Also, older subsidiaries tend to prioritize greater investments in SI projects related to reducing negative externalities and subsidiaries with higher MNE ownership tend to reduce investments in SI projects related to increasing positive externalities. We discuss possible interpretations of the exploratory results using the institutional logics perspective and conclude with implications for policy and future research.

Celebrating International Year of Millet 2023: Analysing Sustainable Food Security in India Since Independence to the Amrit Kaal from the Lens of Millets

While the world is grappling with adversities caused by climate change, the agricultural sector has been the hardest hit, posing a new set of challenges for food security. As the developing world is still struggling with rampant poverty and malnutrition, an alternative framework that could promote climate-resilient and water-saving agriculture emerges as an exigency. In this context, climate-resilient crops like millets acquire the greatest significance as they are not only sustainable and low on climate-critical resources like water but also add to the diversity of the nutritional basket of farmers in rain-fed regions. In this light, the adoption of the India-sponsored resolution declaring 2023 as the International Year of Millets by the United Nations General Assembly is extremely crucial and needs to be analysed with reference to its potentiality to ensure sustainable food security in India in sync with UN Sustainable Development Goals on Poverty and Food Security. Given the potential of millets, this article aims to analyse innovative and sustainable pathways to agriculture from Indian Independence to Amrit Kaal, in alignment with goals of productivity enhancement, energy transition and climate action of the Government of India. It examines the policies and programmes of the government implemented to achieve the goal of Viksit Bharat (Developed India) during the Amrit Kaal.

Coherence‐based automatic short answer scoring using sentence embedding

AbstractAutomatic essay scoring (AES) is an essential educational application in natural language processing. This automated process will alleviate the burden by increasing the reliability and consistency of the assessment. With the advances in text embedding libraries and neural network models, AES systems achieved good results in terms of accuracy. However, the actual goals still need to be attained, like embedding essays into vectors with cohesion and coherence, and providing student feedback is still challenging. In this paper, we proposed coherence‐based embedding of an essay into vectors using sentence‐Bidirectional Encoder Representation for Transformers. We trained these vectors on Long short‐term memory and bidirectional long short‐term memory to capture sentence connectivity with other sentences' semantics. We used two datasets: standard ASAP Kaggle and a domain‐specific dataset with almost 2500 responses from 650 students. Our model performed well on both datasets, with an average quadratic weighted kappa score of 0.76. Furthermore, we achieved good results compared to other prescribed models, and we also tested our model on adversarial responses of both datasets and observed decent outcomes.

Information-based TMS to mid-lateral prefrontal cortex disrupts action goals during emotional processing

The ability to respond to emotional events in a context-sensitive and goal-oriented manner is essential for adaptive functioning. In models of behavioral and emotion regulation, the lateral prefrontal cortex (LPFC) is postulated to maintain goal-relevant representations that promote cognitive control, an idea rarely tested with causal inference. Here, we altered mid-LPFC function in healthy individuals using a putatively inhibitory brain stimulation protocol (continuous theta burst; cTBS), followed by fMRI scanning. Participants performed the Affective Go/No-Go task, which requires goal-oriented action during affective processing. We targeted mid-LPFC (vs. a Control site) based on the individualized location of action-goal representations observed during the task. cTBS to mid-LPFC reduced action-goal representations in mid-LPFC and impaired goal-oriented action, particularly during processing of negative emotional cues. During negative-cue processing, cTBS to mid-LPFC reduced functional coupling between mid-LPFC and nodes of the default mode network, including frontopolar cortex—a region thought to modulate LPFC control signals according to internal states. Collectively, these results indicate that mid-LPFC goal-relevant representations play a causal role in governing context-sensitive cognitive control during emotional processing.

Choosing to End African American Health Disparities in Patients With Systemic Lupus Erythematosus.

Systemic lupus erythematosus (SLE) is three times more common and its manifestations are more severe in African American women compared to women of other races. It is not clear whether this is due to genetic differences or factors related to the physical or social environments, differences in health care, or a combination of these factors. Health disparities in patients with SLE between African American patients and persons of other races have been reported since the 1960s and are correlated with measures of lower socioeconomic status. Risk factors for these disparities have been demonstrated, but whether their mitigation improves outcomes for African American patients has not been tested except in self-efficacy. In 2002, the first true US population-based study of patients with SLE with death certificate records was conducted, which demonstrated a wide disparity between the number of African American women and White women dying from SLE. Five years ago, another study showed that SLE mortality rates in the United States had improved but that the African American patient mortality disparity persisted. Between 2014 and 2021, one study demonstrated racism's deleterious effects in patients with SLE. Racism may have been the unmeasured confounder, the proverbial "elephant in the room"-unnamed and unstudied. The etymology of "risk factor" has evolved from environmental risk factors to social determinants to now include structural injustice/structural racism. Racism in the United States has a centuries-long existence and is deeply ingrained in US society, making its detection and resolution difficult. However, racism being man made means Man can choose to change the it. Health disparities in patients with SLE should be addressed by viewing health care as a basic human right. We offer a conceptual framework and goals for both individual and national actions.