Operational Tasks Research Articles

Temporal information in the anterior cingulate cortex relates to accumulated experiences

Anterior cingulate cortex (ACC) activity is important for operations that require the ability to integrate multiple experiences over time, such as rule learning, cognitive flexibility, working memory, and long-term memory recall. To shed light on this, we analyzed neuronal activity while rats repeated the same behaviors during hour-long sessions to investigate how activity changed over time. We recorded neuronal ensembles as rats performed a decision-free operant task with varying reward likelihoods at three different response ports (n= 5). Neuronal state space analysis revealed that each repetition of a behavior was distinct, with more recent behaviors more similar than those further apart in time. ACC activity was dominated by a slow, gradual change in low-dimensional representations of neural state space aligning with the pace of behavior. Temporal progression, or drift, was apparent on the top principal component for every session and was driven by the accumulation of experiences and not an internal clock. Notably, these signals were consistent across subjects, allowing us to accurately predict trial numbers based on a model trained on data from a different animal. We observed that non-continuous ramping firing rates over extended durations (tens of minutes) drove the low-dimensional ensemble representations. 40% of ACC neurons' firing ramped over a range of trial lengths and combinations of shorter duration ramping neurons created ensembles that tracked longer durations. These findings provide valuable insights into how the ACC, at an ensemble level, conveys temporal information by reflecting the accumulation of experiences over extended periods.

Implementasi Strategi Pertahanan Laut Nusantara Dalam Rangka Deteksi Dini Pelanggaran Di Pesisir Garut Jawa Barat Guna Mendukung Pertahanan Negara Di Laut

Indonesia, with its vast maritime territory and abundant water resources, requires substantial efforts to safeguard defense and security. The effective defense strategy of the Indonesian Navy (TNI AL) involves strategically placing naval bases throughout the entire region, demonstrating a deterrent effect to potential adversaries and affirming the presence of TNI AL in the waters of the Republic of Indonesia. The aim of this research is to analyze the implementation of the Maritime Defense Strategy in early detection of threats along the coast of Garut, West Java. This qualitative research adopts a phenomenological approach, utilizing interview, observation, and documentation methods. The findings indicate that the placement of Binpotmar personnel in Cikelet Garut under the jurisdiction of Posal Pangandaran plays a crucial role in responding to the dynamics of local maritime issues. The flexibility and responsibility of Binpotmar demonstrate vital adaptability in responding to incidents at the border. Functioning as the forefront of intelligence and executing maritime operations, the presence of Binpotmar is a strategic step to enhance self-reliance in carrying out operational tasks. The research also emphasizes the optimal utilization of Cikelet Garut's potential, including the well-maintained Dutch legacy docks, through infrastructural improvements and advanced technology. The naval facility in the area can effectively respond to maritime threats, fulfill the 5R criteria in the Southern Region of Java Island, and create a deterrent effect against adversaries. The importance of collaboration with the Garut Regency Government through forkopimda is highlighted as a crucial consideration for TNI AL. Overall, the research underscores the significance of a comprehensive and collaborative approach in maintaining maritime defense and security in the region.

Implementasi Algoritma Naive Bayes Dalam Penentuan Bonus Karyawan

. CV. Aneka Kaca is a company engaged in the supply of the best glass materials, because CV. Aneka Kaca is a direct distributor from Japan. In a company like CV. Aneka Kaca, employees are one of the important assets in helping to improve and stabilize the company. Employees are people who work in a company or agency to carry out an operational task and expect remuneration in the form of a commission or salary. Usually employees will also get bonuses from the company. Bonuses that will be received by employees are one of the ways companies use to increase the motivation of their employees' performance. But giving bonuses to CV. Aneka Kaca still uses the conventional method, so it can take a long time if only managers do the math. The determination of bonuses can sometimes be missed due to one or two problems that can have an impact on awarding bonuses. The Naive Bayes algorithm is a simple probabilistic classifier that computes a probabilistic set by summing the frequencies and value combinations from a given dataset.

Inside Production Data Science: Exploring the Main Tasks of Data Scientists in Production Environments

Modern production relies on data-based analytics for the prediction and optimization of production processes. Specialized data scientists perform tasks at companies and research institutions, dealing with real data from actual production environments. The roles of data preprocessing and data quality are crucial in data science, and an active research field deals with methodologies and technologies for this. While anecdotes and generalized surveys indicate preprocessing is the major operational task for data scientists, a detailed view of the subtasks and the domain of production data is missing. In this paper, we present a multi-stage survey on data science tasks in practice in the field of production. Using expert knowledge and insights, we found data preprocessing to be the major part of the tasks of data scientists. In detail, we found that tackling missing values, finding data point meanings, and synchronization of multiple time-series were often the most time-consuming preprocessing tasks.

Examining drivers’ distracted driving behaviour using the extended norm activation model

A driving distraction is any external or internal stimulus that diverts a driver’s attention away from the primary task of safe vehicle operation, potentially increasing the risk of accidents. Drivers often get involved in distractions such as phone calls, text messaging, interacting with in-vehicle technology, roadside advertisements, roadside accident sites, and chatting with passengers, etc. In previous research, the antecedents of distraction behaviour have primarily been investigated through the theory of planned behaviour (TPB). Refraining from distracted driving can be considered a pro-social behaviour and can be modelled using the norm activation model (NAM). Therefore, this study aimed to evaluate the potential of pro-social behaviour in explaining drivers’ distracted driving behaviour using the NAM theory. In addition to the conventional factors of the NAM model – awareness of consequences (AC), ascription of responsibility (AR), and personal norms (PN) – this study presents a novel element that examines how technology can mitigate distractions. The data was collected in Lahore city through a questionnaire survey. The results indicate that AC and AR have positive associations with PN, however, PN has also been found to have a positive association with the distraction behaviour. This study provides insights into the utilisation of the NAM theory to evaluate the potential of altruistic behaviour in preventing individuals from engaging in distracted driving.

Resilience of Army Soldiers Who are Carrying Out Operational Tasks in the Papua Region

Resilience of Army Soldiers Who are Carrying Out Operational Tasks in the Papua Region

Rats Lacking the Dopamine Transporter Display Inflexibility in Innate and Learned Behavior.

Playing a key role in the organization of striatal motor output, the dopamine (DA)-ergic system regulates both innate and complex learned behaviors. Growing evidence clearly indicates the involvement of the DA-ergic system in different forms of repetitive (perseverative) behavior. Some of these behaviors accompany such disorders as obsessive-compulsive disorder (OCD), Tourette's syndrome, schizophrenia, and addiction. In this study, we have traced how the inflexibility of repetitive reactions in the recently developed animal model of hyper-DA-ergia, dopamine transporter knockout rats (DAT-KO rats), affects the realization of innate behavior (grooming) and the learning of spatial (learning and reversal learning in T-maze) and non-spatial (extinction of operant reaction) tasks. We found that the microstructure of grooming in DAT-KO rats significantly differed in comparison to control rats. DAT-KO rats more often demonstrated a fixed syntactic chain, making fewer errors and very rarely missing the chain steps in comparison to control rats. DAT-KO rats' behavior during inter-grooming intervals was completely different to the control animals. During learning and reversal learning in the T-maze, DAT-KO rats displayed pronounced patterns of hyperactivity and perseverative (stereotypical) activity, which led to worse learning and a worse performance of the task. Most of the DAT-KO rats could not properly learn the behavioral task in question. During re-learning, DAT-KO rats demonstrated rigid perseverative activity even in the absence of any reinforcement. In operant tasks, the mutant rats demonstrated poor extinction of operant lever pressing: they continued to perform lever presses despite no there being reinforcement. Our results suggest that abnormally elevated DA levels may be responsible for behavioral rigidity. It is conceivable that this phenomenon in DAT-KO rats reflects some of the behavioral traits observed in clinical conditions associated with endogenous or exogenous hyper-DA-ergia, such as schizophrenia, substance abuse, OCD, patients with Parkinson disease treated with DA mimetics, etc. Thus, DAT-KO rats may be a valuable behavioral model in the search for new pharmacological approaches to treat such illnesses.

Determining the location of the arsenal in an effort to increase the carrying capacity of marine forces in the critical area of the North Natuna sea

Strategic environmental dynamics in the North Natuna Sea area raises potential threat spots to the territory of the Republic of Indonesia where the Indonesian Navy needs to determine a maritime security strategy where one of the things that must be prepared is the distribution of logistics in the form of ammunition and weapons through development warehouse Arsenal. Through this research, an alternative strategic location was determined as an Arsenal warehouse as a storage place for ammunition supplies used to support the KRI carrying out operational tasks. Alternative construction locations for Arsenal are Lanal Bintan, Lanal Ranai, Lanal Bangka Belitung and Lantamal IV Pontianak. Based on Perkasal No. 17 of 2008 The criteria used and the absolute requirements for determining the location are security, transportation access and supporting facilities. Data collection for this research was carried out using the method of distributing questionnaires and conducting interviews expert. The Delphi method was used in this research to determine and agree on relevant and valid criteria and sub-criteria to be researched at the next stage. Next Method Analytic Network Process (ANP) is used to determine the best alternative with pdata processing process uses Software Super Decision. Then the structure of complex cause and effect relationships is visualized using a matrix and images using the method Decision Making Trial And Evaluation Laboratory (DEMATEL). The results of this research show that the priority of the alternative Arsenal warehouse location is Lanal Bintan with a weight value of 0.536308. Security criteria and sub-criteria for being safe from enemy attacks are the most dominant criteria in determining Arsenal warehouse location decisions.

Combat actions of the 11th Artillery Division of the Supreme High Command Reserve during the liberation of Romania (April–October 1944)

In the world wars of the 20th century, artillery became the branch of the armed forces whose actions inflicted the greatest damage on the enemy. During the Great Patriotic War, the specific weight and significance of the Soviet artillery of the Supreme High Command Reserve grew continuously, solving not only tactical but also operational combat tasks and, during the third period of the war, ensuring a breakthrough of the enemy defense in the offensive operations of the Red Army. The first European country liberated by Soviet troops was Romania. The main role in this was played by the troops of the 2nd Ukrainian Front, which in March–October 1944 carried out the Uman-Botoşani, Jassy-Kishinev, Bucharest-Arad and Debrecen offensive operations. They included the 11th artillery division of the Supreme High Command Reserve, which was operationally subordinate first to the 7th Guards and then to the 27th Army. The combat actions of the soldiers and officers of the 11th Artillery Division were distinguished by skill, courage and high efficiency. During the Jassy-Kishinev Operation, the fire of their guns crushed the Romanian defense and ensured its rapid breakthrough by infantry and tanks. The 11th Artillery Division acted just as effectively in defense during the September battles in Northern Transylvania during the Bucharest-Arad Operation. In both defensive and offensive combat actions during all four operations of the 2nd Ukrainian Front, which resulted in the complete liberation of Romania from the Nazis, the 11th Artillery Division of the Supreme High Command Reserve demonstrated firepower and high maneuverability, thereby making a significant contribution to the success of the front's troops.

ВИКОРИСТАННЯ КОМП’ЮТЕРНИХ ТЕСТ-ТРЕНАЖЕРІВ ДЛЯ ВИЗНАЧЕННЯ І РОЗВИТКУ ПСИХОФІЗІОЛОГІЧНИХ ЯКОСТЕЙ ЮНИХ СПОРТСМЕНІВ

The current task for coaches nowadays is to choose an adequate method for assessing psychophysiological abilities, diagnosing, and further developing the psychophysiological qualities of young athletes to organize and correct training and competitive processes. The purpose of the study was to evaluate the effectiveness of computer test simulator programs for developing the psychophysiological qualities of young athletes, individualizing, and optimizing their training process. Using computer test simulators with the programs "MY_TIMER" and "FISHKI.INI", psychophysiological indicators were measured before and after training in five repetitions among 14 schoolchildren aged 12-14 from a secondary education institution. Statistical data processing was conducted using Microsoft Excel. Results: Unreliable differences (p ≥ 0.5) were found between the psychophysiological parameters of young swimmers before and after training. During the computer testing process, increases were observed in the total working time for each of the five tasks (indicating improved speed of thinking) by 18.5%, and in minimum, average, and maximum movement time by 14.3%, 11.1%, and 8.3%, respectively. However, the thinking factor decreased by 16% after training, which impedes the ability to perform operational tasks impromptu. Exercising in areas of high and moderate power leads to fatigue in the cortex of the large hemispheres of the brain, where operational control is carried out. Consequently, young athletes experience both physical and mental fatigue after training. The use of computer test simulators for determining and developing the psychophysiological indicators of young athletes is relevant, promising, and effective. These tools allow for the scientific substantiation of individualized training loads and the rapid assessment of athletes' current functional states. The "FISHKI.INI" program should be used for diagnosing and further developing psychophysiological qualities such as attention, operational thinking, and the dominance of figurative or visual-action thinking. This program enables the quantitative assessment of young athletes' characteristics and improves these qualities with high efficiency through the use of computer test simulators.

Enterprise cloud resource optimization and management based on cloud operations

The so-called automated operation and maintenance refers to a large number of repetitive tasks in daily IT operations (from simple daily checks, configuration changes and software installation to organizational scheduling of the entire change process) from manual execution in the past to standardized, streamlined and automated operations. This article delves into the realm of enterprise cloud resource optimization and management, leveraging automated operations (autoOps) as a fundamental strategy. As industries like banking witness exponential growth and innovation in IT systems, the complexity of managing resources escalates. Automated operations have emerged as a critical component, transitioning from manual interventions to encompass standardization, workflow optimization, and architectural enhancements. Through real-world deployments and theoretical frameworks, it elucidates effective strategies for optimizing and governing enterprise cloud resources, thereby enhancing efficiency, security, and resilience in IT operations.

Enterprise cloud resource optimization and management based on cloud operations

The so-called automated operation and maintenance refers to a large number of repetitive tasks in daily IT operations (from simple daily checks, configuration changes and software installation to organizational scheduling of the entire change process) from manual execution in the past to standardized, streamlined and automated operations. This article delves into the realm of enterprise cloud resource optimization and management, leveraging automated operations (autoOps) as a fundamental strategy. As industries like banking witness exponential growth and innovation in IT systems, the complexity of managing resources escalates. Automated operations have emerged as a critical component, transitioning from manual interventions to encompass standardization, workflow optimization, and architectural enhancements. Through real-world deployments and theoretical frameworks, it elucidates effective strategies for optimizing and governing enterprise cloud resources, thereby enhancing efficiency, security, and resilience in IT operations.

The neuropharmacological profile of interval responding during operant tasks.

Responses occurring during intervals of operant tasks have been subdivided as interim, facultative, and terminal, depending on the time between response onset and reward. Although interval responses, also known as adjunctive responses, have been described in pigeons, rats, mice, monkeys, and humans, most experiments have been conducted in rats. We review the neurochemical basis of interval responses and examine the hypothesis that these responses modulate operant performance. Preliminary experiments indicate the involvement of biogenic amines, acetylcholine, and GABA during interval responding associated with operant tasks. In particular, catecholaminergic deafferentation of the basal ganglia modulated interval responses as did the peripheral injection of catecholamine reuptake blockers. Under the influence of amphetamine, interval responding may either increase or decrease, so that a wide range of responses must be selected to gauge drug effects. In non-drugged pigeons and rats, the expression of interval responses facilitates operant training.

Reconfigurable modular soft robots with modulating stiffness and versatile task capabilities

Soft robots have revolutionized machine interactions with humans and the environment to enable safe operations. The fixed morphology of these soft robots dictates their mechanical performance, including strength and stiffness, which limits their task range and applications. Proposed here are modular, reconfigurable soft robots with the capabilities of changing their morphology and adjusting their stiffness to perform versatile object handling and planar or spatial operational tasks. The reconfiguration and tunable interconnectivity between the elemental soft, pneumatically driven actuation units is made possible through integrated permanent magnets with coils. The proposed concept of attaching/detaching actuators enables these robots to be easily rearranged in various configurations to change the morphology of the system. While the potential for these actuators allows for arbitrary reconfiguration through parallel or serial connection on their four sides, we demonstrate here a configuration called ManusBot. ManusBot is a hand-like structure with digits and palm capable of individual actuation. The capabilities of this system are demonstrated through specific examples of stiffness modulation, variable payload capacity, and structure forming for enhanced and versatile object manipulation and operations. The proposed modular, soft robotic system with interconnecting capabilities significantly expands the versatility of operational tasks as well as the adaptability of handling objects of various shapes, sizes, and weights using a single system.

ФОРМУВАННЯ ЛОКАЛЬНИХ ЕЛЕКТРОЕНЕРГЕТИЧНИХ СИСТЕМ В СКЛАДІ ОБ’ЄДНАНОЇ ЕЛЕКТРОЕНЕРГЕТИЧНОЇ СИСТЕМИ

At present, renewable sources of energy (RSE) are geographically diffused in energy supply systems, which complicates the formation of local electric energy systems (LEES), which operating in normal modes in parallel with the energy system as balancing groups, in extreme cases can operate in isolation in autonomous mode. However, the diffuse distribution of RSE does not allow for the effective formation of LEES in such a way that they ensure the required level of reliability of electricity supply to electricity consumers. The article proposes to integrate RSE into distribution power grids in the form of separate microgrid (MG), which is a key part of the transition to a power grid operating on the principles of SMART Grid. Local MGs, in addition to generation sources and consumers, also have the means to accumulate a certain amount of energy. To ensure the technical and economic efficiency, MGs are combined into an intelligent control system, which allows for more rational use of MG resources, efficient interaction with the distribution grid, and the use of active electricity consumers in the process of balancing the LEES mode. The paper proposes a hierarchical structure of the intellectual system of LEES. Thus structured, LEES with intelligent power grids can not lose RSE during the limitation of centralized power supply, but fully use their advantages together with energy storage systems for reliable power supply to consumers. Thanks to the intelligent system proposed in this paper, the LEES implements the principles of SMART Grid and functions as an informative energy system. The LEES formed in this way can operate as a balancing group within the ESS, performing the tasks of the distribution system operator depending on the voltage and power of its MG components. Since LEES are a part of the ESS, they operate under the conditions and according to the rules, without disrupting the functioning of the ESS, which currently provides a stable power supply. This applies to all modes of operation of LEES.

SleepSync: Early Testing of a Personalised Sleep-Wake Management Smartphone Application for Improving Sleep and Cognitive Fitness in Defence Shift Workers.

Shift work, long work hours, and operational tasks contribute to sleep and circadian disruption in defence personnel, with profound impacts on cognition. To address this, a digital technology, the SleepSync app, was designed for use in defence. A pre-post design study was undertaken to examine whether four weeks app use improved sleep and cognitive fitness (high performance neurocognition) in a cohort of shift workers from the Royal Australian Air Force. In total, 13 of approximately 20 shift-working personnel from one base volunteered for the study. Sleep outcomes were assessed using the Insomnia Severity Index (ISI), the Patient-Reported Outcomes Measurement Information System (PROMIS), Sleep Disturbance and Sleep-Related Impairment Scales, the Glasgow Sleep Effort Scale, the Sleep Hygiene Index, and mental health was assessed using the Depression, Anxiety, and Stress Scale-21. Sustained attention was measured using the 3-min Psychomotor Vigilance Task (PVT) and controlled response using the NBack. Results showed significant improvements in insomnia (ISI scores 10.31 at baseline and 7.50 after app use), sleep-related impairments (SRI T-scores 53.03 at baseline to 46.75 post-app use), and healthy sleep practices (SHI scores 21.61 at baseline to 18.83 post-app use; all p < 0.001). Trends for improvement were recorded for depression. NBack incorrect responses reduced significantly (9.36 at baseline; reduced by -3.87 at last week of app use, p < 0.001), but no other objective measures improved. These findings suggest that SleepSync may improve sleep and positively enhance cognitive fitness but warrants further investigation in large samples. Randomised control trials with other cohorts of defence personnel are needed to confirm the utility of this intervention in defence settings.

Evaluating the influencing factors and effects of the digitalization of management control

Purpose This study aims to investigate the influences on the digitalization of management control and the effects of this digitalization on management control tasks performed, management control instruments used and the organization of management control. Design/methodology/approach This empirical analysis is based on a survey of 189 management accountants and managers responsible for management control in Germany, Austria and Switzerland. Logistic regression analyses were used to test the investigated effects. Findings This study finds that digital competencies, standardization of processes and data management contribute to the digitalization of management control. This study further finds that digitalization significantly increases the coverage of strategic and operational management control tasks and the use of operational management control instruments but not of strategic instruments. Originality This study investigates the influence of digitalization in management control on strategic and operational management control tasks, instruments and organizations. In contrast, prior research has focused on single aspects of management control or analyzed the impact on the entire company. This is also the first study, to the best of the authors’ knowledge, to systematically identify potential influences on the digitalization of management control and analyze them empirically.

Methodology for determining the durability of soil-cultivating machines working bodies of parts

The development and creation of high-performance machines for agricultural production is in many cases limited by the insufficient wear resistance of individual parts and assemblies. Russian scientists, engineers and technicians working on the problem of increasing the durability of machines have achieved significant results. However, theoretical conclusions and prerequisites for increasing durability and the method of calculating parts of agricultural machines for durability are not enough. The durability calculations of agricultural machine parts used in some cases during their design are imperfect. In addition, in most cases, there are no reasonable calculations of allowable wear that would ensure high quality machine operation, i.e. these calculations are not related to the tasks of preventive maintenance and operation of machines. A number of scientists have been studying the abrasive wear of working parts of soil-cultivating and seeding machines for decades, but this issue has not yet been finally resolved. Until now, there is no clear understanding of the essence of abrasive wear and the factors that determine it. Most of the work carried out on the study of abrasive wear of parts of working bodies of soil-cultivating machines is of a private nature. There are no works covering the study of the complex set of phenomena that occur during abrasive wear. At present, very little has been studied about the wear capacity of soils, there is no criterion that determines it, and there is no connection between the phenomena of wear of the working parts of soil-cultivating machines and the basic theoretical principles of agricultural mechanics. The study of the wear capacity of soils, as well as the determination of the magnitude of pressures that arise during the interaction of the working parts of agricultural machines with the soil, can be used when calculating the working parts of these machines for durability.

Applications and Performance of Machine Learning Algorithms in Emergency Medical Services: A Scoping Review.

The aim of this study was to summarize the literature on the applications of machine learning (ML) and their performance in Emergency Medical Services (EMS). Four relevant electronic databases were searched (from inception through January 2024) for all original studies that employed EMS-guided ML algorithms to enhance the clinical and operational performance of EMS. Two reviewers screened the retrieved studies and extracted relevant data from the included studies. The characteristics of included studies, employed ML algorithms, and their performance were quantitively described across primary domains and subdomains. This review included a total of 164 studies published from 2005 through 2024. Of those, 125 were clinical domain focused and 39 were operational. The characteristics of ML algorithms such as sample size, number and type of input features, and performance varied between and within domains and subdomains of applications. Clinical applications of ML algorithms involved triage or diagnosis classification (n = 62), treatment prediction (n = 12), or clinical outcome prediction (n = 50), mainly for out-of-hospital cardiac arrest/OHCA (n = 62), cardiovascular diseases/CVDs (n = 19), and trauma (n = 24). The performance of these ML algorithms varied, with a median area under the receiver operating characteristic curve (AUC) of 85.6%, accuracy of 88.1%, sensitivity of 86.05%, and specificity of 86.5%. Within the operational studies, the operational task of most ML algorithms was ambulance allocation (n = 21), followed by ambulance detection (n = 5), ambulance deployment (n = 5), route optimization (n = 5), and quality assurance (n = 3). The performance of all operational ML algorithms varied and had a median AUC of 96.1%, accuracy of 90.0%, sensitivity of 94.4%, and specificity of 87.7%. Generally, neural network and ensemble algorithms, to some degree, out-performed other ML algorithms. Triaging and managing different prehospital medical conditions and augmenting ambulance performance can be improved by ML algorithms. Future reports should focus on a specific clinical condition or operational task to improve the precision of the performance metrics of ML models.

A Unified Review of Deep Learning for Automated Medical Coding

Automated medical coding, an essential task for healthcare operation and delivery, makes unstructured data manageable by predicting medical codes from clinical documents. Recent advances in deep learning and natural language processing have been widely applied to this task. However, deep learning-based medical coding lacks a unified view of the design of neural network architectures. This review proposes a unified framework to provide a general understanding of the building blocks of medical coding models and summarizes recent advanced models under the proposed framework. Our unified framework decomposes medical coding into four main components, i.e., encoder modules for text feature extraction, mechanisms for building deep encoder architectures, decoder modules for transforming hidden representations into medical codes, and the usage of auxiliary information. Finally, we introduce the benchmarks and real-world usage and discuss key research challenges and future directions.