Operational Tasks Research Articles

Особенности социально-психологической адаптации к учебно-служебной деятельности слушателей факультета профессиональной подготовки Казанского юридического института МВД России

The article presents preliminary results of an empirical study on the problems and characteristics of the socio-psychological adaptation of students of the faculty of vocational training, retraining and advanced training of the Kazan Law Institute of the Ministry of Internal Affairs of Russia to educational and service activities. The methodological basis of the study was the scientific principles of cognition: the principle of determinism, the unity of consciousness and activity (psyche and behavior), the principle of development, as well as such approaches to scientific cognition as functional, personal, systemic.
 Methods of scientific and cognitive activity: observation and experience, survey in the form of a questionnaire, description, comparison, universal analysis and synthesis, induction and deduction, abstraction, generalization and systematization.
 Professional adaptation in educational institutions of the system of the Ministry of Internal Affairs of Russia involves adaptation to the requirements of educational activities, which is aimed at improving the professionally necessary knowledge, skills, training in methods and techniques for quickly solving official problems, respectively, manifests and develops the ability of students to adapt to educational and service, and later on to professional activity, which, in turn, is a factor in the psychosomatic health of a developing subject.
 In an empirical study of the characteristics of socio-psychological adaptation of students to educational and service activities (the level achieved, characteristic difficulties in its process), a positive dynamics of the studied indicators of personality adaptability during training was revealed. Low, medium and high levels of formation of social and psychological adaptation of listeners are revealed.
 The effectiveness of students' educational and service activities depends on the individual psychological characteristics of the individual and the integrated work of the Institute's employees to provide comfortable conditions for students to assimilate knowledge, develop skills and abilities to effectively resolve operational and service tasks.

Analysis of Risk Factors for Hypertension in Ship Crews of Seaports Work Coverage for Poso Port Health Office, Bungku Working Area

Objective: Ship crew as seafarers who work or are employed on board the ship by the owner or operator of the ship to carry out their duties following their position will have limitations in accessing health education, facilities, and infrastructure that support them to maintain their health. One of the non-communicable diseases that contributes to cardiovascular diseases is hypertension. This study aims to determine the risk factors related to the prevalence of hypertension in ship crew at Seaport work coverage for Poso Port Health Office, Bungku Working Area. Methods: This was a cross-sectional study with a sample size of 385 participant involve in data analysis. Chi-square analysis was employed to assess the relationship between respondent characteristic variables and independent variables concerning the occurrence of hypertension. Multivariate analysis was conducted on variables that showed an association with hypertension to obtain independent risk values using logistic regression analysis. This research used a 95% confidence level. Results: The prevalence of hypertension in ship crew is 12.73%. Logistic regression results showed that the crew members had an overweight (AOR=15.93, 95%CI: 5.080-49.981, p=0.000) and moderate and heavy smokers among crew members (AOR=2.51, 95%CI: 1.038-6.066), p=0.021) were factors associated with the prevalence of hypertension in ships crew members of hypertension in ships crew members after controlled by aged over 45 years (AOR=22.94; 95% CI: 2.587-203.477, p=0.005) and family history of hypertension (AOR=6.01; 95% CI: 2.741-13.168, p=0.000). Conclusions: Body mass index and smoking behavior among ship crew members are significant risk factors for hypertension in this study, while alcohol consumption and workplace-related environmental stress were not found to be significant risk factors in this research Implication of the research: This research can serve as a reference for determining health programs and more specific priority groups targeted for the prevention and control of hypertension among ship crew members on board. Originality: This study was conducted on ship crew members, legally active seafarers in the operational tasks on ship, whereas most similar research uses the health data of seafarers in healthcare clinics.

Restructuring of the Mechanism for Countering Tax Evasion

Along with the advantages of the ongoing digital transformation of the economy in Russia, there are problems with the use of technology for illegal purposes. New tax evasion schemes are emerging, based on previously unused information technology solutions and income-generating activities that are gaining momentum. Rapid trends encourage government agencies to take timely measures to neutralize threats to the country's economic security. In this regard, the restructuring of the mechanism for countering tax evasion is of particular relevance. The purpose of the research is to develop an updated structure of the mechanism for countering tax evasion. The methodological basis was the methods of analysis and synthesis, induction and deduction, comparative analysis in determining the essence of the mechanism for countering tax evasion; the method of system-structural analysis in determining the constituent elements of the mechanism and the classification of tools; methods of abstraction and logical formalization in the representation of the mechanism. The result of the research is the author's structure of the mechanism for countering tax evasion. The proposed restructured version of the mechanism allows you to automatically respond to changes in factors affecting it and adjust yourself by updating operational tasks and counteraction tools included in the variable component.

Dynamic constraint and objective generation approach for real-time train rescheduling model under human-computer interaction

Real-time train rescheduling plays a vital role in railway transportation as it is crucial for maintaining punctuality and reliability in rail operations. In this paper, we propose a rescheduling model that incorporates constraints and objectives generated through human-computer interaction. This approach ensures that the model is aligned with practical requirements and daily operational tasks while facilitating iterative train rescheduling. The dispatcher’s empirical knowledge is integrated into the train rescheduling process using a human-computer interaction framework. We introduce six interfaces to dynamically construct constraints and objectives that capture human intentions. By summarizing rescheduling rules, we devise a rule-based conflict detection-resolution heuristic algorithm to effectively solve the formulated model. A series of numerical experiments are presented, demonstrating strong performance across the entire system. Furthermore, the flexibility of rescheduling is enhanced through secondary analysis-driven solutions derived from the outcomes of human-computer interactions in the previous step. This proposed interaction method complements existing literature on rescheduling methods involving human-computer interactions. It serves as a tool to aid dispatchers in identifying more feasible solutions in accordance with their empirical rescheduling strategies.

Pattern recognition based on statistical methods combined with machine learning in railway switches

Railway switches are critical components in the rail system. Operation and maintenance tasks are essential to ensure proper functioning and avoid any failure that can cause delays, reducing operational safety. Data from condition monitoring systems requires advanced analysis tools. This paper presents the analysis of power output data of railway switches. A novel approach is proposed based on statistical analysis techniques combined with Machine Learning techniques to classify power curves by analyzing different sections of the power curves. These curves are studied statistically to classify them into normal and non-normal curves. Then, a dataset is generated with normal and non-normal labelled curves. Shapelets and k-Nearest Neighbour classification algorithms are applied to these data with good results (accuracy, sensitivity and specificity above 88% in each case). As a further analysis, a second dataset with the sectioned curves is done to detect non-normal curves without analyzing the complete curve. For this case study, k-Nearest Neighbour algorithm is able to classify with higher accuracy on the last section of the curve.

Home cage voluntary alcohol consumption increases binge drinking without affecting abstinence-related depressive-like behaviors or operant responding in crossed high alcohol-preferring mice (cHAPs)

Chronic alcohol consumption can lead to tolerance and escalation of drinking in humans and animals, but mechanisms underlying these changes are not fully characterized. Preclinical models can delineate which mechanisms are involved. The chronic intermittent ethanol exposure (CIE) procedure uses forced exposure to vaporized alcohol that elicits withdrawal and increased responding for alcohol in operant tasks in C57BL/6J inbred mice. Chronic two-bottle choice (2BC) drinking in the same strain elicits abstinent-related depression-like behavior, suggestive of allostatic changes. Selected lines such as crossed High Alcohol Preferring (cHAP) mice voluntarily drink to blood alcohol concentrations comparable to those attained in CIE and could be used to assess how alcohol affects these same endpoints without the confounds of involuntary vapor inhalation. In three experiments, we assess how 2BC drinking in cHAP mice affects abstinence-related depressive- and anxiety-like behavior, operant responding for alcohol, and binge consumption using drinking-in-the-dark (DID). We hypothesized that cHAPs with home-cage drinking experience would exhibit more depressive behavior after abstinence, increased responding for alcohol in the operant box, and increased DID intake. Of these, a drinking history increased DID intake in female cHAPs only and increased sucrose preference and intake following abstinence, but had no effects on operant responding or NSFT latency and FST immobility following forced abstinence. These results are consistent with recent findings using slice electrophysiology showing tolerance to alcohol's actions on the dorsolateral striatum following 2BC drinking in female, but not male cHAP mice. Overall, these data suggest that cHAPs may require procedures allowing rapid intoxication, such as DID, to demonstrate changes in alcohol's rewarding effects.

Application of Learning Vector Quantization and Trajectory Planning On a 4-DoF Robotic Arm to Move the Object

The robotic arm is a type of statistical robot with a limited range of movement. Robotic arms are generally within the scope of Cartesian coordinates, according to the specified link length. The development of robot technology leads us to continue to upgrade soft computing. Intelligent systems in robots can improve good navigation detection systems or carry out the operator's tasks. On the other hand, using a camera is an important part of finding clear information about objects or capturing the environment around the robot. In this research, we implemented an intelligent system and computer-based camera on a 4-DoF robotic arm system. This robotic arm consists of a computer as the main processor, a microcontroller to adjust the joint angle, additional electronics, and a camera to detect objects and classify them by color. The colors used are red, green, and blue. The learning process uses these colors using Learning Vector Quantization (LVQ). The implementation of LVQ also carries out pre-processing, training, and testing stages. In the experiments that have been carried out, the robotic arm successfully navigates toward the target object and moves the object using the Trajectory Planning method. This computing process is done on a computer and connected to the robot arm's microcontroller. The experiment was carried out 60 times, and the success rate was 95%. Overall, the robot successfully picked up objects and grouped them by color.

Operator visual attention allocation prediction in a robotic arm teleoperation interface

AbstractIn digital interactive interfaces with high visual workloads, it is important for operators to allocate their limited attentional resources appropriately to ensure efficient information collection. The salience, effort, expectancy, value (SEEV) model, which combines top‐down and bottom‐up attention mechanisms for predicting attention allocation, has been validated in research areas such as piloting, driving, and surgical operations. However, the validity of the SEEV model in the field of robotic arm teleoperation has not yet been thoroughly studied. The primary purpose of this study was to confirm the feasibility of the SEEV model for operator visual attention allocation prediction in a robotic arm teleoperation scenario. The improved ITTI algorithm, distance‐measuring tool, Delphi method, and lowest ordinal algorithm were adopted to qualify the four factors of the SEEV model, which also contributed to salience and expectancy quantification methods. Accordingly, an attention allocation prediction model in a robotic arm teleoperation scene was constructed. To verify the validity of the prediction model, 20 participants were recruited to control the robotic arm using V‐REP simulation software, and their fixation durations were recorded using an eye tracker as an attention allocation indicator. Participants controlled the robotic arm according to the experimental requirements and operational tasks, such as grasping and placing the target. The results demonstrated that the theoretical data based on the SEEV prediction model are significantly related to the proportion of fixation durations. The experiment verifies the suitability of the SEEV prediction model, and it is anticipated to be utilized in the optimization of interactive interfaces for robotic arm teleoperation.

Timed Sequence Task: A New Paradigm to Study Motor Learning and Flexibility in Mice.

Motor learning and flexibility allow animals to perform routine actions efficiently while keeping them flexible. A number of paradigms are used to test cognitive flexibility, but not many of them focus specifically on the learning of complex motor sequences and their flexibility. While many tests use operant or touchscreen boxes that offer high throughput and reproducibility, the motor actions themselves are mostly simple presses of a designated lever. To focus more on motor actions during the operant task and to probe the flexibility of these well trained actions, we developed a new operant paradigm for mice, the "timed sequence task." The task requires mice to learn a sequence of lever presses that have to be emitted in precisely defined time limits. After training, the required pressing sequence and/or timing of individual presses is modified to test the ability of mice to alter their previously trained motor actions. We provide a code for the new protocol that can be used and adapted to common types of operant boxes. In addition, we provide a set of scripts that allow automatic extraction and analysis of numerous parameters recorded during each session. We demonstrate that the analysis of multiple performance parameters is necessary for detailed insight into the behavior of animals during the task. We validate our paradigm in an experiment using the valproate model of autism as a model of cognitive inflexibility. We show that the valproate mice show superior performance at specific stages of the task, paradoxically because of their propensity to more stereotypic behavior.

Точки кипения в университетах – новый инструмент развития инновационного потенциала регионов России

To successfully solve the problem of accelerated development of innovative technological entrepreneurship, new tools and approaches are needed in organizing the training of innovative entrepreneurs, primarily in the fields of digital economy technologies, the development of means of production, and artificial intelligence. The aim of the work is to study the possibilities of entrepreneurial boiling points created at universities for the development of the innovation potential of the regions of Russia. The possibilities of providing the regional economy with professional personnel prepared for specific production infrastructure, equipment and technologies, and teams of employees are considered. Different technologies of professional personnel training are studied in the context of actual operational and tactical tasks of the regional economy, taking into account the strategic vision of future industries and technologies. Various forms of conducting classes and meetings with representatives of science, education, and business have been widely tested, which allow forming an individual track for each participant and determining the optimal trajectory of his development, taking into account individual characteristics and developing knowledge, skills, and abilities in modern science, technology, and production. It is shown that boiling points in regional technical universities open up new opportunities to increase the innovative potential of regions by training young innovators adapted to the regional economy in an unstable environment.

Research on desktop object grasping based on ellipse fitting

The grasping operation task in service scenes faces several problems including too many kinds of objects and a large amount of training data. This paper focuses on the grasping strategy and pose detection in desktop object grasping tasks. A grasping strategy is given based on the combination of desktop normal vector detection, object category detection, and grasping pose detection. The grasping pose is calculated by ellipse fitting on the depth map. An optimal function is designed to evaluate the possibility of the object sliding along the ellipse axis and the stability of the grasping height. The most reliable grasping pose is selected. Finally, experiments were carried out with a six-degree-of-freedom manipulator, and the proposed grasping method achieved effective grasping of desktop objects without prior knowledge of the object.

Gripping performance of soft grippers with fingerprint-like surface texture for objects with slippery surfaces

Soft robots face challenges when gripping and manipulating objects in lubricated environments, and one of the key issues in medical lubrication conditions in particular. In this study, soft actuators with independent pneumatic driven DIP and PIP joints are designed and prepared based on the anatomy of human fingers. The soft actuators are used to mimic the tip pinch action of the index finger and thumb, achieving dexterous grasping postures adapted to daily life, primarily for fine operation tasks. The bending capability, thrusting force, and fatigue life of the soft actuators are tested. Furthermore, by mimicking the three common fingerprint patterns (i.e., whorls, loops, and arches), three macroscopic surface textures were designed and prepared on the surface of silicone rubber materials. Tribological properties of the surface textures are studied under medical lubrication conditions with hyaluronic acid solution as lubricant. Based on this, tip pinch gripping experiments are conducted on standard shape objects, common medical devices, and biological materials with surface mucus layer. The results showed that the surface of the soft actuators can fit well with the surface of the gripped objects, thereby achieving a larger contact area and enabling the gripping of standard items and common medical devices. Moreover, for biological materials with mucous layer of significant differences in physiological function, the weight that can be gripped is significantly higher than that of the gripper without surface texture.

Mining equipment diagnostics in a mine shaft dewatering system – case study

Maintenance issues in mines are particularly important due to the type and complexity of equipment in operation or working in hostile (even extreme) conditions. In this context, the need to ensure continuous/regular maintenance of machinery, identify potential hazards and ensure operational safety seems to be a challenge. Moreover, selecting an appropriate maintenance method is crucial for a mine, both economically and in technical/organizational terms. This study aims to present the preliminary results of diagnostic tests for pumps performing operational tasks in a mine shaft dewatering system. In addition, this study focused on a detailed discussion of the basic elements of the mine shaft dewatering system and the technical objects studied. A preliminary operational test plan for the investigated pumps operating in the mine shaft dewatering system is also presented. This enabled a discussion of the results obtained from the tests of the first quarter of 2023. The tests used three basic diagnostic methods: vibration analysis, thermal imaging and acoustic testing. Potential directions for further research in the analyzed area were also indicated.

서예진흥법 내실화를 위한 서예교육 전문인력 양성 방안 제언

This article suggested ways to train and promote calligraphy education professionals to internalize the basic plan for calligraphy promotion.
 First of all, the current status and necessity of training professionals, and the opinions of related institutions and individuals were comprehensively confirmed. Currently, the training of professionals in the field of calligraphy is centered on universities (graduate schools), and only one university is currently in existence, and since graduate schools assist in the role of universities, it has been confirmed that the size of training and production of calligraphy education professionals is gradually decreasing. On the other hand, most institutions and individuals are aware of the importance of fostering calligraphy education professionals, and suggested the establishment of training institutions, standard curriculum and textbook development, treatment and employment issues after completion of training.
 Next, professional manpower training and promotion measures were classified into three categories and suggested. First of all, the designation and operation of a calligraphy professional training institution were presented. The institution designation suggested cooperation and cooperation among professional educational entities, the use of local educational institutions, consultation with local governments, and operation of designated educational institutions according to the standard curriculum for training professionals.
 Second, the introduction of a qualification system for professionals in calligraphy education was suggested. Through this, the status of calligraphy education and the promotion of quality of employment, and the linkage with measures to revitalize cultural infrastructure and tourism development were described. In addition, it suggested improving operational elasticity by linking related tasks and curricula such as planning calligraphy education, establishing educational operation plans, conducting field classes, operation, and administrative tasks, establishing an organic cooperative system.
 Finally, the formation of a calligraphy promotion network and the establishment of a foundation were presented. Specifically, it was suggested to establish a comprehensive calligraphy promotion management system for long-term stabilization of calligraphy promotion policies, and to clarify and unify policies through expert forums.

СОВЕРШЕНСТВОВАНИЕ ПОДГОТОВКИ СПАСАТЕЛЕЙ-ПОЖАРНЫХ МЧС РОССИИ НА СОВРЕМЕННОМ ЭТАПЕ

Statistical data on the increase in the scale of emerging forest fires and the number of floods on the territory of Russia are presented. The problem of improving the training of firefighters and rescuers is considered in connection with the growing tasks of eliminating the consequences of emergency situations, extinguishing fires and carrying out emergency rescue and other urgent work at the present stage. It is proposed to improve their training by including in the training programs both in fire and rescue units and in the university of State fire service of EMERCOM of Russia sections on the study of the damaging factors of modern means of destruction and the organization of protection against them, strengthening the practical development of the organization of protection and tactics of actions of fire and rescue units 
 in the performance of their operational and service tasks.

Exploring the New Mode of Cooperation between Applied Undergraduate Education and Enterprises-Taking Logistics Engineering Major as an Example

With the continuous development of the global economy and the rapid growth of the logistics industry, the demand for logistics engineering majors is increasing day by day. The traditional theoretical teaching mode can no longer meet the actual needs of the industry, and students, can not adapt to the complex logistics operation and management tasks with theoretical knowledge alone. Therefore, more and more colleges and universities have begun to explore the innovative path of undergraduate education. This paper explores the application of the new mode of cooperation between applied undergraduate education and enterprises in the logistics engineering specialty. It analyzes the current situation of the education model of logistics engineering, discusses the significance of establishing cooperation between applied undergraduate education and enterprises, elaborates on the challenges faced during the implementation of the model, and puts forward corresponding countermeasure points. It includes practices such as establishing cooperation frameworks and mechanisms, strengthening internships and practical training, integrating curricula with industry needs, promoting the combination of industry, academia, and research, as well as establishing incentive mechanisms and win-win cooperation models, aiming to provide more practice-oriented education and to cultivate professionals adapted to the industry's development.

Visual-Aided Shared Control of Semi-Autonomous Underwater Vehicle for Efficient Underwater Grasping

Human intelligence has the advantage for making high-level decisions in the remote control of underwater vehicles, while autonomous control is superior for accurate and fast close-range pose adjustment. Combining the advantages of both remote and autonomous control, this paper proposes a visual-aided shared-control method for a semi-autonomous underwater vehicle (sAUV) to conduct flexible, efficient and stable underwater grasping. The proposed method utilizes an arbitration mechanism to assign the authority weights of the human command and the automatic controller according to the attraction field (AF) generated by the target objects. The AF intensity is adjusted by understanding the human intention, and the remote-operation command is fused with a visual servo controller. The shared controller is designed based on the kinematic and dynamic models, and model parameter uncertainties are also addressed. Efficient and stable control performance is validated by both simulation and experiment. Faster and accurate dynamic positioning in front of the target object is achieved using the shared-control method. Compared to the pure remote operation mode, the shared-control mode significantly reduces the average time consumption on grasping tasks for both skilled and unskilled operators.

Hybrid Detection Technique for IP Packet Header Modifications Associated with Store-and-Forward Operations

The detection technique for IP packet header modifications associated with store-and-forward operation pertains to a methodology or mechanism utilized for the identification and detection of alterations made to packet headers within a network setting that utilizes a store-and-forward operation. The problem that led to employing this technique lies with the fact that previous research studies expected intrusion detection systems (IDSs) to perform everything associated with inspecting the entire network transmission session for detecting any modification. However, in the store-and-forward process, upon arrival at a network node such as a router or switch, a packet is temporarily stored prior to being transmitted to its intended destination. Throughout the duration of storage, IDS operation tasks would not be able to store that packet; however, it is possible that certain adjustments or modifications could be implemented to the packet headers that IDS does not recognize. For this reason, this current research uses a combination of a convolutional neural network and long short-term memory to predict the detection of any modifications associated with the store-and-forward process. The combination of CNN and LSTM suggests a significant improvement in the model’s performance with an increase in the number of packets within each flow: on average, 99% detection performance was achieved. This implies that when comprehending the ideal pattern, the model exhibits accurate predictions for modifications in cases where the transmission abruptly increases. This study has made a significant contribution to the identification of IP packet header modifications that are linked to the store-and-forward operation.

Метод нахождения динамических приоритетов грузовых операций для оптимизации работы самоходных подвижных единиц в железнодорожных промышленных транспортно-технологических системах

The application of fuzzy logic is considered in optimizing the sequence of operations that involve the use of self-propelled units in industrial railway transportation. The consequences of using constant values calculated analytically as operation priorities have been analyzed. The type of queue discipline and the specifics of constraints on the stay of requests in the queue, characteristic of railway industrial transport and technological systems, are described. The advantages and disadvantages of existing methods for queuing freight operations specified in the daily work plan in railway industrial transport and technological systems are investigated. Limitations arising from the use of classical scheduling theory methods have been identified. Finding the optimal sequence of operations in railway industrial transport and technological systems involves simultaneous movement planning for multiple mobile units, which is not considered in classical graph theory. The classical problem of finding the shortest path and its known solving algorithms only work with static graphs, while railway industrial transport and technological systems are characterized by rapid changes in the graph's state. The problems caused by the dynamic nature of the graph's state in railway industrial transport and technological systems have been analyzed. The application of fuzzy logic methods will enable the construction of an optimal sequence of operations based on incomplete and imprecise information and address several operational planning tasks for freight operations without precise calculations. The expected result of applying the method for determining dynamic operation priorities implemented in the neuro-fuzzy module is an increase in the adaptability of operational planning for freight operations and a reduction in the time of engagement and the required number of self-propelled mobile units.

Negative Emotions Recruit the Parabrachial Nucleus Efferent to the VTA to Disengage Instrumental Food Seeking.

The parabrachial nucleus (PBN) interfaces between taste and feeding systems and is also an important hub for relaying distress information and threats. Despite that the PBN sends projections to the ventral tegmental area (VTA), a heterogeneous brain region that regulates motivational behaviors, the function of the PBN-to-VTA connection remains elusive. Here, by using male mice in several behavioral paradigms, we discover that VTA-projecting PBN neurons are significantly engaged in contextual fear, restraint or mild stress but not palatable feeding, visceral malaise, or thermal pain. These results suggest that the PBN-to-VTA input may relay negative emotions under threat. Consistent with this notion, optogenetic activation of PBN-to-VTA glutamatergic input results in aversion, which is sufficient to override palatable feeding. Moreover, in a palatable food-reinforced operant task, we demonstrate that transient optogenetic activation of PBN-to-VTA input during food reward retrieval disengages instrumental food-seeking behaviors but spares learned action-outcome association. By using an activity-dependent targeting approach, we show that VTA DA neurons are disengaged by the PBN afferent activation, implicating that VTA non-DA neurons may mediate PBN afferent regulation. We further show that optogenetic activation of VTA neurons functionally recruited by the PBN input results in aversion, dampens palatable feeding, and disengages palatable food self-administration behavior. Finally, we demonstrate that transient activation of VTA glutamatergic, but not GABAergic, neurons recapitulates the negative regulation of the PBN input on food self-administration behavior. Together, we reveal that the PBN-to-VTA input conveys negative affect, likely through VTA glutamatergic neurons, to disengage instrumental food-seeking behaviors.SIGNIFICANCE STATEMENT The PBN receives multiple inputs and thus is well positioned to route information of various modalities to engage different downstream circuits to attend or respond accordingly. We demonstrate that the PBN-to-VTA input conveys negative affect and then triggers adaptive prioritized responses to address pertinent needs by withholding ongoing behaviors, such as palatable food seeking or intake shown in the present study. It has evolutionary significance because preparing to cope with stressful situations or threats takes priority over food seeking to promote survival. Knowing how appropriate adaptive responses are generated will provide new insights into circuitry mechanisms of various coping behaviors to changing environmental stimuli.