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The mean estimation task, which explicitly asks observers to estimate the mean feature value of multiple stimuli, is a fundamental paradigm in research areas such as ensemble coding and cue integration. The current study uses computational models to formalize how observers summarize information in mean estimation tasks. We compare model predictions from our Fidelity-based Integration Model (FIM) and other models on their ability to simulate observed patterns in within-trial weight distribution, across-trial information integration, and set-size effects on mean estimation accuracy. Experiments show non-equal weighting within trials in both sequential and simultaneous mean estimation tasks. Observers implicitly overestimated trial means below the global mean and underestimated trial means above the global mean. Mean estimation performance declined and stabilized with increasing set sizes. FIM successfully simulated all observed patterns, while other models failed. FIM's information sampling structure provides a new way to interpret the capacity limit in visual working memory and sub-sampling strategies. As a model framework, FIM offers task-dependent modeling for various ensemble coding paradigms, facilitating research synthesis across different studies in the literature. [ABSTRACT FROM AUTHOR]

Although it is often assumed that spatial attention exists in the form of a unitary focus, the split-attention hypothesis proposes that attention can be simultaneously divided into two spatially noncontiguous positions and that the space in between can be ignored. However, whether split attention occurs directly based on the generation of attentional benefit or whether it requires a gradual divide from a unitary focus over time has not been clarified. In the present study, by using two spatial salient cues to direct the attention allocation of participants, we aimed to investigate whether attention requires time to divide from a unitary focus and whether the appearance time of split attention varies when the task difficulty level increases between experiments. The results showed that attention required time to divide from a unitary focus, and the position between the two cued positions was not excluded by attention when the stimulus-onset asynchrony (SOA) was 60 ms. However, as the task difficulty increased between experiments, the appearance time of split attention was earlier. These findings suggest that the appearance time of split attention has a certain flexibility and can be changed according to the task requirement, thus implying that split attention and unitary attention present some common attention mechanisms and that a split or unitary mode can be flexibly selected for an attention system. [ABSTRACT FROM AUTHOR]

At least three processes determine whether information we encounter is attended to or ignored. First, attentional capture occurs when attention is drawn automatically by "bottom up" processes, to distinctive, salient, rewarding, or unexpected stimuli when they enter our sensory field. Second, "top down" attentional control can direct cognitive processing towards goal-relevant targets. Third, selection history, operates through repeated exposure to a stimulus, particularly when associated with reward. Attentional control is measured using tasks that require subjects to selectively attend to goal-relevant stimuli in the face of distractions. In the Eriksen flanker task, human participants report which direction a centrally placed arrow is facing, while ignoring "flanking" arrows that may point in the opposite direction. Attentional control is evident to the extent that performance reflects only the direction of the central arrow. We describe four experiments in which we systematically assessed attentional control in rhesus monkeys using a flanker task. In Experiment 1, monkeys responded according to the identity of a central target, and accuracy and latency varied systematically with manipulations of flanking stimuli, validating our adaptation of the Eriksen flanker task. We then tested for converging evidence of attentional control across three experiments in which flanker performance was modulated by the distance separating targets from flankers (Experiment 2), luminance differences (Experiment 3), and differences in associative value (Experiment 4). The approach described is a new and reliable measure of attentional control in rhesus monkeys that can be applied to a wide range of situations with freely behaving animals. [ABSTRACT FROM AUTHOR]

Three studies were conducted to develop primes that activate differing beliefs about God and to determine if these activated beliefs impact scrupulosity symptoms. In Study 1, potential positive, negative, and neutral primes were created from Bible verses and rated on arousal, valence, familiarity, and complexity. In Study 2, the selected primes were tested to determine if they differentially activated positive and negative beliefs about God. In Study 3, participants were randomly assigned to read one of three primes (positive, negative, or neutral). Participants then completed a thought-induction task and measures of scrupulosity and thought-action fusion. There were no significant differences in reactions to the thought-induction task or self-report measures of scrupulosity or thought-action fusion between conditions. An exploratory analysis revealed that participants in the negative condition had higher state anxiety following the prime compared to participants in the positive condition. Results demonstrate the potential of the primes to activate negative beliefs about God and highlight the possible detrimental impact negative beliefs about God may have on state anxiety. However, they do not suggest that the primes impact scrupulosity and related constructs. [ABSTRACT FROM AUTHOR]

As an emerging computing model, edge computing greatly expands the collaboration capabilities of the servers. It makes full use of the available resources around the users to quickly complete the task request coming from the terminal devices. Task offloading is a common solution for improving the efficiency of task execution on edge networks. However, the peculiarities of the edge networks, especially the random access of mobile devices, brings unpredictable challenges to the task offloading in a mobile edge network. In this paper, we propose a trajectory prediction model for moving targets in edge networks without users' historical paths which represents their habitual movement trajectory. We also put forward a mobility-aware parallelizable task offloading strategy based on a trajectory prediction model and parallel mechanisms of tasks. In our experiments, we compared the hit ratio of the prediction model, network bandwidth and task execution efficiency of the edge networks by using the EUA data set. Experimental results showed that our model is much better than random, non-position prediction parallel, non-parallel strategy-based position prediction. Where the task offloading hit rate is closed to the user's moving speed, when the speed is less 12.96 m/s, the hit rate can reach more than 80%. Meanwhile, we we also find that the bandwidth occupancy is significantly related to the degree of task parallelism and the number of services running on servers in the network. The parallel strategy can boost network bandwidth utilization by more than eight times when compared to a non-parallel policy as the number of parallel activities grows. [ABSTRACT FROM AUTHOR]

Supervised learning with the restriction of a few existing training samples is called Few-Shot Learning. FSL is a subarea that puts deep learning performance in a gap, as building robust deep networks requires big training data. Using transfer learning in FSL tasks is an acceptable way to avoid the challenge of building new deep models from scratch. Transfer learning methodology considers borrowing the architecture and parameters of a previously trained model on a large-scale dataset and fine-tuning it for low-data target tasks. But practically, fine-tuning pretrained models in target FSL tasks suffers from overfitting. The few existing samples are not enough to correctly adjust the pretrained model's parameters to provide the best fit for the target task. In this study, we consider mitigating the overfitting problem when applying transfer learning in few-shot Handwritten Character Recognition (HCR) tasks. A data augmentation approach based on Conditional Generative Adversarial Networks is introduced. CGAN is a generative model that can create artificial instances that appear more real and indistinguishable from the original samples. CGAN helps generate extra samples that hold the possible variations of human handwriting instead of applying traditional image transformations. These transformations are low-level, data-independent operations, and only produce augmented samples with limited diversity. The introduced approach was evaluated in fine-tuning the three pretrained models: AlexNet, VGG-16, and GoogleNet. The results show that the samples generated by CGAN can enhance transfer learning performance in few-shot HCR tasks. This is by achieving model fine-tuning with fewer epochs and by increasing the model's F 1 - s c o r e and decreasing the Generalization Error (E test) . [ABSTRACT FROM AUTHOR]

Obesity can result from excess intake in response to environmental food cues, and stress can drive greater intake and body weight. We used a novel fMRI task to explore how obesity and stress influenced appetitive responses to relatively minimal food cues (words representing food items, presented similarly to a chalkboard menu). Twenty-nine adults (16F, 13M), 17 of whom had obesity and 12 of whom were lean, completed two fMRI scans, one following a combined social and physiological stressor and the other following a control task. A food word reactivity task assessed subjective food approach (wanting) as well as food avoidant (restraint) responses, along with neural responses, to words denoting high energy-density (ED) foods, low-ED foods, and non-foods. A multi-item ad-libitum meal followed each scan. The obese and lean groups demonstrated differences as well as similarities in activation of appetitive and attention/self-regulation systems in response to food vs. non-food, and to high-ED vs. low-ED food words. Patterns of activation were largely similar across stress and non-stress conditions, with some evidence for differences between conditions within both obese and lean groups. The obese group ate more than the lean group in both conditions. Our results suggest that neural responses to minimal food cues in stressed and non-stressed states may contribute to excess consumption and adiposity. [ABSTRACT FROM AUTHOR]

Task representations are critical for cognitive control and adaptive behavior. The hierarchical organization of task representations allows humans to maintain goals, integrate information across varying contexts, and select potential responses. In this study we characterized the structure and interactive dynamics of task representations that facilitate cognitive control. Human participants (both males and females) performed a hierarchical task that required them to select a response rule while considering the contingencies from different contextual inputs. By applying time- and frequency-resolved representational similarity analysis to human electroencephalography data, we characterized properties of task representations that are otherwise difficult to observe. We found that participants formed multiple representations of task-relevant contexts and features from the presented stimuli, beyond simple stimulus–response mappings. These disparate representations were hierarchically structured, with higher-order contextual representations dominantly influencing subordinate representations of task features and response rules. Furthermore, this cascade of top-down interactions facilitated faster responses. Our results describe key properties of task representations that support hierarchical cognitive control. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel two-stage transformer with GhostNet, which improves the performance of the small object detection task. Specifically, based on the original Deformable Transformers for End-to-End Object Detection (deformable DETR), we chose GhostNet as the backbone to extract features, since it is better suited for an efficient feature extraction. Furthermore, at the target detection stage, we selected the 300 best bounding box results as regional proposals, which were subsequently set as primary object queries of the decoder layer. Finally, in the decoder layer, we optimized and modified the queries to increase the target accuracy. In order to validate the performance of the proposed model, we adopted a widely used COCO 2017 dataset. Extensive experiments demonstrated that the proposed scheme yielded a higher average precision (AP) score in detecting small objects than the existing deformable DETR model. [ABSTRACT FROM AUTHOR]

Fog computing is one of the major components of future 6G networks. It can provide fast computing of different application-related tasks and improve system reliability due to better decision-making. Parallel offloading, in which a task is split into several sub-tasks and transmitted to different fog nodes for parallel computation, is a promising concept in task offloading. Parallel offloading suffers from challenges such as sub-task splitting and mapping of sub-tasks to the fog nodes. In this paper, we propose a novel many-to-one matching-based algorithm for the allocation of sub-tasks to fog nodes. We develop preference profiles for IoT nodes and fog nodes to reduce the task computation delay. We also propose a technique to address the externalities problem in the matching algorithm that is caused by the dynamic preference profiles. Furthermore, a detailed evaluation of the proposed technique is presented to show the benefits of each feature of the algorithm. Simulation results show that the proposed matching-based offloading technique outperforms other available techniques from the literature and improves task latency by 52% at high task loads. [ABSTRACT FROM AUTHOR]

Mobile edge computing (MEC), which sinks the functions of cloud servers, has become an emerging paradigm to solve the contradiction between delay-sensitive tasks and resource-constrained terminals. Task offloading assisted by service caching in a collaborative manner can reduce delay and balance the edge load in MEC. Due to the limited storage resources of edge servers, it is a significant issue to develop a dynamical service caching strategy according to the actual variable user demands in task offloading. Therefore, this paper investigates the collaborative task offloading problem assisted by a dynamical caching strategy in MEC. Furthermore, a two-level computing strategy called joint task offloading and service caching (JTOSC) is proposed to solve the optimized problem. The outer layer in JTOSC iteratively updates the service caching decisions based on the Gibbs sampling. The inner layer in JTOSC adopts the fairness-aware allocation algorithm and the offloading revenue preference-based bilateral matching algorithm to get a great computing resource allocation and task offloading scheme. The simulation results indicate that the proposed strategy outperforms the other four comparison strategies in terms of maximum offloading delay, service cache hit rate, and edge load balance. [ABSTRACT FROM AUTHOR]

Mobile Crowd Sensing (MCS) involves allocation of sensing tasks associated with an area of interest to a crowd of participants over time. Consequently, the collective amount of time and energy spent on sensing can be quite large. Sparse Mobile Crowd Sensing (Sparse-MCS) aims at reducing this overhead by reducing the number of sensing tasks, which results in obtaining sensed values from only some portions of the area or time. For those portions which are not thus covered, their corresponding values can be inferred from the collected sensed values. Hence, missing data inference is an integral part of Sparse-MCS. This study is divided into two phases: First, we explore the viability of using machine learning, viz., regression for missing data inference in Sparse-MCS. Hence, we explore several representative regression algorithms such as Linear Regression, LASSO, Elastic Net, Ridge, Decision Tree (DT), Random Forest (RF) and KNN. Using two real data-sets, we conclude that some algorithms such as DT and RF exhibit good performance (giving normalized mean absolute error much less than 0.1 most of the time) whereas the rest do not. Moreover, we compare these techniques with a state-of-the-art missing data inference method known as Compressing Sensing with the help of simulation results. Next, we propose a divide-and-conquer polynomial-time algorithm for task reduction which is based on the proposed inference approach. We also present the results of the analysis of the algorithm in terms of: (i) its time complexity, and (ii) lower and upper bounds on task reduction. [ABSTRACT FROM AUTHOR]

Recently, wide-area distributed computing environments have become popular owing to their huge resource capability. In a wide-area distributed computing environment, joint scheduling of tasks and data is the main strategy to improve system performance. However, the geographically distributed diverse resources exhibit high variations, making it challenging to design efficient joint scheduling of tasks and data. To accurately adapt to the dynamic variations of geographically distributed diverse resources and achieve a high system performance, this study proposes a hypergraph-partitioning-based online joint scheduling method. The proposed method constructs a hypergraph of geographically distributed tasks, data, and diverse resources to clearly describe the correlation among the three elements and quantitatively reflect the time cost of different process in the environment. The hypergraph is dynamically updated according to the generated scheduling scheme and the collected information to reflect the dynamic variations of resource states. Then, a hypergraph partition optimization mechanism is proposed to generate efficient joint scheduling schemes, thus reducing the overall completion time in the system. The experimental results indicate that compared with the state-of-the-art joint scheduling methods, the proposed method reduces the overall completion time by up to 25.67% and significantly reduces the task waiting time, although it makes a concession in the data migration time. [ABSTRACT FROM AUTHOR]

Reliability and energy efficiency are two hostile objectives considered in designing task scheduling in most real-time multiprocessor systems on chip (MPSoC). Addressing and improving one of them may affect and degrade the efficiency of the other one and vice versa. In this paper, we intend to examine these challenges and ultimately achieve an optimal energy consumption and reliability state. This paper presents a novel scheduling technique that can adapt to the limitations of real-time systems and have optimal energy consumption and reliability. This is done by minimizing the overlap of tasks, adjusting the speed of processors and the number of backups of each task. The proposed scheme reduces energy consumption on average by 11% to 42% compared to the previous state-of-the-art techniques and keeps the reliability at a high level. [ABSTRACT FROM AUTHOR]

Effective human–robot collaboration requires the appropriate allocation of indivisible tasks between humans and robots. A task allocation method that appropriately makes use of the unique capabilities of each agent (either a human or a robot) can improve team performance. This paper presents a novel task allocation method for heterogeneous human–robot teams based on artificial trust from a robot that can learn agent capabilities over time and allocate both existing and novel tasks. Tasks are allocated to the agent that maximizes the expected total reward. The expected total reward incorporates trust in the agent to successfully execute the task as well as the task reward and cost associated with using that agent for that task. Trust in an agent is computed from an artificial trust model, where trust is assessed along a capability dimension by comparing the belief in agent capabilities with the task requirements. An agent's capabilities are represented by a belief distribution and learned using stochastic task outcomes. Our task allocation method was simulated for a human–robot dyad. The team total reward of our artificial trust-based task allocation method outperforms other methods both when the human's capabilities are initially unknown and when the human's capabilities belief distribution has converged to the human's actual capabilities. Our task allocation method enables human–robot teams to maximize their joint performance. [ABSTRACT FROM AUTHOR]

According to the sequential stage model, the selection and the execution of a motor response are two distinct independent processes. Here, we propose a new adaptive paradigm for identifying the individual duration of the response preparatory period based on the motor reaction time (RT) data. The results are compared using the paradigm with constant values of the preparatory period. Two groups of participants performed on either an easy (Group 1) or a hard (Group 2) response selection task with two types of stimuli based on the preparatory period parameters: (1) stimuli with a constant preparatory period duration of 0 or 1200 ms and (2) stimuli with adaptive preparatory period durations. Our analysis showed an increase in the duration of the response selection process as a function of increasing task complexity when using both paradigms with constant and adaptive values of the preparatory period duration. We conclude that the adaptive paradigm proposed in the current paper has several important advantages over the constant paradigm in terms of measuring the response accuracy while being equally efficiently in capturing other critical response parameters. [ABSTRACT FROM AUTHOR]

Our world is full of uncertainty. Animals, including humans, need to behave flexibly to adjust to ever-changing environments. Reversal learning tasks have been used to assess behavioral flexibility in many species. However, there are some limitations in the traditional free-moving methodology, including (1) sessions to train the animals, (2) within-session number of trials associated with reversals, (3) factors of physical movement unrelated to the task in the maze or operant box, and (4) incompatibility with techniques, such as two-photon imaging. Therefore, to address these limitations, we established a novel spatiotemporal Pavlovian head-fixed reversal learning task for mice. Six experimentally naive adult C57BL/6J mice were used in this study. First, we trained head-fixed mice on a fixed-time schedule task. Sucrose solution was delivered every 10 s with a single drinking spout placed within the licking distance of the mice. After the mice showed anticipatory licking toward the timing of sucrose solution delivery, we began training the mice on the fixed-time schedule reversal learning task with two licking spouts. In this task, sucrose solution was delivered through one of the two drinking spouts. The rewarding spout was switched every 10 trials. Mice quickly learned to switch anticipatory licking to the rewarding side of the spouts, suggesting that they learned this head-fixed reversal learning task. Using the head-fixed experimental design, behavioral measures can be simplified by eliminating the complex behavioral sequences observed in free-moving animals. This novel head-fixed reversal learning task is a useful assay for studying the neurobiological mechanism of behavioral flexibility that is impaired in various psychopathological conditions. [ABSTRACT FROM AUTHOR]

Objective assessment of near viewing behaviours performed in a laboratory setting showed that children demonstrate differing viewing distances and angles based on the type of task. Findings will contribute to our understanding of how near work influences myopia. Evidence suggests that near working distance and viewing breaks are associated with myopia. The purpose of this study was to use an objective, continuously measuring range finding device to examine these viewing behaviours in children. Viewing distance, number of breaks, and head and eye angles were assessed in 16 non-myopic and 19 myopic children (ages 13.38 ± 4.14 years) using the Clouclip, an objective rangefinder, during five 15-minute near tasks, including (a) passive reading and (b) active writing on printed material, (c) passive viewing and (d) active engagement on an iPad, and (e) active engagement on a cell phone. Height and Harmon distance were measured. Viewing behaviours were analysed by task, refractive error group, and gender. Mean viewing distances significantly differed by task (P < 0.001) and were highly correlated with children's Harmon distance and height for all near tasks (P < 0.05), except for the active printed task (P > 0.05). Viewing distances did not differ by gender or refractive error group. During each task, mean number of viewing breaks was 2.6 ± 4.1 and did not vary between task (P = 0.92) or refractive error group (P = 0.65). Head declination and total viewing angle varied by type of near task (P < 0.001 for both). Children demonstrated differing viewing distances and viewing angles based on the type of near task they were performing. Viewing behaviours did not vary between myopic and non-myopic children. Findings will contribute to a better understanding of how near viewing behaviours can be quantified objectively and relationships with myopia. [ABSTRACT FROM AUTHOR]

Weak passwords are one of the most pervasive threats in cybersecurity. Facing this threat, users require guidance on how to protect themselves. A method frequently used by IS practitioners and researchers to provide this guidance is fear appeals, persuasive messages intended to prompt behavioral changes in response to a threat. However, previous research has not considered a key element of fear appeal effectiveness: task primacy. When fear appeals are a part of the primary or focal task, users' cognitive engagement will be high by default. However, when fear appeals are delivered as secondary tasks, such as interruptive security messages, users' engagement is likely to be low because the primary task takes priority in attentional and cognitive resources. In such cases, a remedy is needed to elicit engagement with the fear appeal. In this research note, we theorize that cognitive engagement acts as a contextual moderator that is critical to the effectiveness of fear appeals under the boundary condition of task primacy. Further, we theorize that interactivity, a mechanism that adapts message content through tailored real-time feedback in response to a user's actions, is a key remedy to enhance engagement with fear appeals. However, to date fear appeals have largely been tested in noninteractive primary tasks, and no study has provided a theoretical explanation for why interactivity enhances the power of a fear appeal. We empirically examined engagement as a contextual moderator in two ways. First, we conducted a field experiment, which manipulated messages on a password creation form on a real-world website. Second, we performed a qualitative focus group study to triangulate the experimental results and more fully reify our theoretical model. Together, the findings reveal that interactivity acts as a catalyst to engage participants with a fear appeal, which then allows the persuasive message of the fear appeal to be internalized. The concepts of boundary condition of task primacy and engagement suggest ways that fear appeals can be more effectively applied in research and practice. [ABSTRACT FROM AUTHOR]

This study proposes a stock handling system that combines an automatic shelf and a picking robot with the aim of reducing the labor required for stocking and disposing of items. The robot system was developed by referring to the rules of the robot competition WRS2020 F.C.S.C. The picking robot is a standard single-arm mobile manipulation robot and the automatic shelf is characterized by the fact that the shelves move up and down and back and forth automatically. Automatic movement of the shelves in the pull-out direction allows the end-effector of the manipulator to approach the item from above and select the grasping position from a number of candidates. This improves the stability of the grasping of the item and is expected to prevent the item from falling during transportation. When there are tall items at the front of the shelf, the end-effector can directly approach the items at the back of the shelf from above the shelf as the shelf plate automatically moves in the pull-out direction. We report the mechanical configuration of the automatic shelf and basic experimental results for stocking and disposal work by the proposed robot system. [ABSTRACT FROM AUTHOR]

The perceptual feature of a task such as how a task goal is perceived influences performance and coordination of bimanual actions in neurotypical adults. To assess how bimanual task goal modifies paretic and non-paretic arm performance and bimanual coordination in individuals with stroke affecting left and right hemispheres, 30 participants with hemispheric stroke (15 right-hemisphere damage—RHD); 15 left-hemisphere damage—LHD) and 10 age-matched controls performed reach-to-grasp and pick-up actions under bimanual common-goal (i.e., two physically coupled dowels), bimanual independent-goal (two physically uncoupled dowels), and unimanual conditions. Reach-to-grasp time and peak grasp aperture indexed motor performance, while time lags between peak reach velocities, peak grasp apertures, and peak pick-up velocities of the two hands characterized reach, grasp, and pick-up coordination, respectively. Compared to unimanual actions, bimanual actions significantly slowed non-paretic arm speed to match paretic arm speed, thus affording no benefit to paretic arm performance. Detriments in non-paretic arm performance during bimanual actions was more pronounced in the RHD group. Under common-goal conditions, movements were faster with smaller peak grasp apertures compared to independent-goal conditions for all groups. Compared to controls, individuals with stroke demonstrated poor grasp and pick-up coordination. Of the patient groups, patients with LHD showed more pronounced deficits in grasp coordination between hands. Finally, grasp coordination deficits related to paretic arm motor deficits (upper extremity Fugl–Meyer score) for LHD group, and to Trail-Making Test performance for RHD group. Findings suggest that task goal and distinct clinical deficits influence bimanual performance and coordination in patients with left- and right-hemispheric stroke. [ABSTRACT FROM AUTHOR]

Objective: Using graph theoretical analysis, the current study explores network properties of highly associated brain areas during initiation and inhibition. Method: The current study utilized a publicly available dataset of functional connectivity matrices generated during initiation and inhibition (go/nogo paradigm) in 144 healthy adults between the age of 20 and 86 who were recruited from the greater Toronto area (Jenny R Rieck et. al, 2021). The researcher selected brain areas (ROIs) that showed high correlation (>0.75) from each participant's matrices and input high incidents of functional connectivity among all participants into an incidental matrix which was used to generate a network graph for each task. ROIs are presented as nodes (vertices) while their connections are edges. Core measures, such as degree distribution, mean distance, within module degree z score, and gateway coefficient, were analyzed. Results: The analysis showed a disconnected network across several brain regions and several common connections among somatomotor, default A, and peripheral visual networks. For the initiation task, the medial prefrontal cortex on both hemispheres are more frequently activated. A high betweenness was found in different brain areas for the inhibition and initiation across visual and default networks. Further analysis showed the extra-striate cortex appears to be the "hub" for initiation while the extra-striate superior cortex appears to be the "hub" for inhibition. Conclusion(s): The present study showed several common brain areas that are activated during both initiation and inhibition, highlighted differences in activation between the two tasks and explored several areas that could be a "hub" during each task. [ABSTRACT FROM AUTHOR]

Aspect-level sentiment analysis aims to determine the sentiment polarity towards specific aspect in reviews. However, little research has been done on the influence of complex sentences on sentiment classification. Based on this, this paper proposed an aspect sentiment classification model based on Bert and Self-attention network with relative position. Firstly, it used the dynamic weighted sampling method to balance the rare contrastive sentences, so that the model can learn more contrastive sentence feature information. Then, it jointly trained the feature representations extracted by double-head self-attention network with relative position and the feature representations obtained by the Pre-trained model with absolute position. Finally, it used the label smoothing regularization technology to stabilize the model to identify the neutral samples. It tested this model on Sub Task 2 in SemEval 2014 task, and improved both accuracy and Macro-F1 indicators of the two datasets. The experimental results show that the effectiveness of the proposed model for contrastive sentences classification, and also yield improvements in the whole test set over other benchmark models. [ABSTRACT FROM AUTHOR]

Robots make decisions in a variety of situations requiring multitasking. Therefore, in this work, a method is studied to address multiple tasks based on reinforcement learning. Our previous method selects an action when the q-values of the action for each task correspond to a priority value in the q-table. However, the decision-making would select an ineffective action in particular situations. In this study, an action value weighted by priority is defined (termed as action priority) to indicate that the selected action is effective in accomplishing the task. Subsequently a method is proposed for selecting actions using action priorities. It is demonstrated that the proposed method can accomplish tasks faster with fewer errors. [ABSTRACT FROM AUTHOR]

Ultra-short-term HRV features assess minor autonomous nervous system variations such as variations resulting from cognitive stress peaks during demanding tasks. Several studies compare ultra-short-term and short-term HRV measurements to investigate their reliability. However, existing experiments are conducted in low cognitively demanding environments. In this paper, we propose to evaluate these measurements' reliability under cognitively demanding tasks using a near real-life setting. For this purpose, we selected 31 HRV features, extracted from data collected from 21 programmers performing code comprehension, and compared them across 18 different time frames, ranging from 3 min to 10 s. Statistical significance and correlation tests were performed between the features extracted using the larger window (3 min) and the same features extracted with the other 17 time frames. We paired these analyses with Bland–Altman plots to inspect how the extraction window size affects the HRV features. The main results show 13 features that presented at least 50% correlation when using 60-second windows. The HF and mNN features achieved around 50% correlation using a 30-second window. The 30-second window was the smallest time frame considered to have reliable measurements. Furthermore, the mNN feature proved to be quite robust to the shortening of the time resolution. [ABSTRACT FROM AUTHOR]

Several industrial pick-and-place applications, such as collaborative assembly lines, rely on visual tracking of the parts. Recurrent occlusions are caused by the manipulator motion decrease line productivity and can provoke failures. This work provides a complete solution for maintaining the occlusion-free line of sight between a variable-pose camera and the object to be picked by a 6R manipulator that is not wrist-partitioned. We consider potential occlusions by the manipulator as well as the operator working at the assembly station. An actuated camera detects the object goal (part to pick) and keeps track of the operator. The approach consists of using the complete set of solutions obtained from the derivation of the univariate polynomial equation solution to the inverse kinematics (IK). Compared to numerical iterative solving methods, our strategy grants us a set of joint positions (posture) for each root of the equation from which we extract the best (minimizing the risks of occlusion). Our analytical-based method, integrating collision and occlusion avoidance optimizations, can contribute to greatly enhancing the efficiency and safety of collaborative assembly workstations. We validate our approach with simulations as well as with physical deployments on commercial hardware. [ABSTRACT FROM AUTHOR]

Altruistic choice is influenced by the relationship between the person making the choice and the recipient, and such relationships are based on an intangible quality known as social distance. This review examines the research on social distance as a part of the social discounting task, which employs behavioral economic methods to quantify the impact of social relationships on altruistic choice. The review examines the origins of the social discounting task and the subsequent work in laboratory simulations and as applied to clinical populations. The application of social discounting and social distance to the study of altruism is discussed. [ABSTRACT FROM AUTHOR]

Hypothetical purchase tasks are a widely used tool to determine the reinforcing value of commodities, especially commodities which are difficult to deliver experimentally. Amazon Mechanical Turk users (N = 375) completed two novel hypothetical purchase tasks (quantity of purchase and probability of purchase) and other measures to estimate how much an individual values the opportunity to exercise in a gym. We examined correlations between demand indices generated by each task and measures related to physical activity. In addition, we compared rates of systematic and nonsystematic responding between the two tasks. Exploratory analyses of demand indices and measures of physical activity suggest initial evidence of construct validity for each task. When accounting for an order effect, the probability of purchase task generated significantly lower rates of nonsystematic responding compared to the quantity of purchase task (2.87% vs. 14.6%, respectively). We discuss how these results may inform improved construction of future hypothetical purchase tasks and implications for using likelihood and quantity purchase tasks. [ABSTRACT FROM AUTHOR]

This study aimed: (1) to evaluate the hand motor fatigability in people with spinal cord injury (SCI) and compare it with measurements obtained form an able-bodied population; (2) to compare the hand motor fatigability in people with tetraplegia and in people with paraplegia; and (3) to analyse if motor fatigability is different in people with SCI with and without clinical significant perceived fatigability. Materials and Methods: 96 participants with SCI (40 cervical and 56 thoracolumbar) and 63 able-bodied controls performed a simple hand isometric task to assess motor fatigability. The Fatigue Severity Scale was used for perceived fatigability evaluation. Results: The main results of this study can be summarized as follows: (1) the waning in muscle force (motor fatigability) during a fatiguing task is similar in controls and participants with SCI; (2) the motor fatigability is influenced by the maximal muscle force (measured at the beginning of the task); and (3) the perceived fatigability and the motor fatigability are largely independent in the individuals with SCI. Conclusion: Our findings suggest that the capability to maintain a prolonged effort is preserved in SCI, and this capacity depends on the residual maximal muscle force in people with SCI. [ABSTRACT FROM AUTHOR]

We ran a field experiment to investigate whether individual performance in teams was affected by the gender of the leader. About 430 students from an Italian University took an intermediate exam that was partly evaluated on the basis of teamwork. Students were randomly matched in teams of three and, in each team, we randomly chose a leader entrusted with the task of coordinating the work of the team. We find a positive and significant effect of female leadership on team performance. This effect is driven by the higher performance of team members in female-led teams rather than by an improvement in leader performance. In spite of the higher performance of female-led teams, male members tended to evaluate female leaders as less effective, whereas female members have provided more favorable judgments. Our results are consistent with stereotypically feminine personality traits influencing leadership style and the decision on the amount of effort to exert in a task where females are contravening stereotypical behavior and their traditional societal role. [ABSTRACT FROM AUTHOR]

Few-shot learning is an extremely challenging task in computer vision that has attracted increased research attention in recent years. However, most recent methods do not fully use the task’s information, and few of the seen samples result in large intraclass differences among the same classes. In this paper, we propose a novel task encoding with distribution calibration (TEDC) model for few-shot learning, which uses the relationships among the feature distributions to reduce intraclass differences. In the TEDC model, an integrated feature extraction module (IFEM) is proposed, which extracts the multiangle visual features of an image and fuses them to obtain more representative features. To effectively utilize the task information, a novel task encoding module (TEM) is proposed, which obtains the task features by fusing all the seen samples’ information and uses them to adjust all the samples’ features for more generalizable task-specific representations. We also propose a distribution calibration module (DCM) to reduce the bias between the distribution of the support features and the query features in the same class. Extensive experiments show that our proposed TEDC model achieves an excellent performance and outperforms the state-of-the-art methods on three widely used few-shot classification benchmarks, specifically miniImageNet, tieredImageNet and CUB-200-2011. [ABSTRACT FROM AUTHOR]

Objective: The length of the hamstring muscles plays an important role in human movements. The aim of the present study was to compare ROM, perceived tightness, and kinetic variables during balance, walking, and running tasks in athletes with and without hamstring tightness. Methods: Thirty healthy female athletes (15 with hamstring tightness and 15 controls) were assessed for ROM, perceived tightness, and kinetic parameters which were obtained by Moticon SCIENCE insoles and Moticon software during single-leg balance, slow/fast walking, and running. Independent t test was used to compare the outcome measures between two groups. Results: The results showed that the control group and the athletes with hamstring tightness are significantly different in regards to ROM, perceived tightness (P = 0.001), the mean center of pressure in the mediolateral direction (MCOPML) (P = 0.01) in single- leg balance, maximum total force of stance phase (MaxTFSP) (P < 0.02) in slow walking, and mean Y end point of gait line (MYEPGL) (P = 0.04) in fast walking. In the running task, none of the study variables were significantly different between the two groups of athletes with and without hamstring tightness. Conclusion: It is recommended to pay more attention to the hamstring flexibility, especially during balance and walking tasks and regaining its normal length should be included in the rehabilitation plans. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to determine if forward step-down task frontal kinematics differ in women with and without patellofemoral pain (PFP). Methods: Cross-sectional study. A total of 32 women were allocated into a healthy control group (CG; n = 16) and to a PFP (n = 16) group. All participants performed two trials with five consecutive forward step-down task (FSD) repetitions each. A video camera, positioned 3 m from the participant's frontal plane, recorded the movement (sampling rate = 30 Hz). All recorded videos were evaluated on Image-J software, and the following outcomes were obtained: delta mean (∆mean, the difference between final and initial positions) and delta peak (∆peak) values for Q-angle (Qϴ), hip and knee frontal plane projection angles, and dynamic valgus index. We compared groups with the Student's t test for independent samples and the Mann–Whitney test. Results: Groups showed similar (p > 0.05) values for Q-angle (∆mean CG = 3.7° ± 2.5°, PFP = 3.2° ± 2.9°; ∆peak CG = 5.8° ± 2.5°, PFP = 5.1° ± 3.1°), hip frontal plane projection angle (∆mean CG = − 13.2° ± 5.4°, PFP = − 10.7° ± 5.3°; ∆peak CG = − 16.9° ± 5.1°, PFP = − 13.7° ± 5.2°), knee frontal plane projection angle (∆mean CG = -3.3° ± 4.5°, PFP = − 3.9° ± 4.5°; ∆peak CG = − 7.9° ± 6.7°, PFP = − 7.6° ± 5.2°) and dynamic valgus index (∆mean CG = − 17.2° ± 8.3°, PFP = − 15.0° ± 9.2°; ∆peak CG = − 19.4° ± 8.1°, PFP = − 17.3° ± 8.7°). Conclusion: The similarity in frontal plane kinematics during FSD between PFP female patients and healthy women suggests that clinicians should be cautious when determining PFP presence in clinical practice with this method and when using it to measure a healthy condition to be achieved during rehabilitation. Trial registration: Study was registered at Clinical Trials (NCT02734030) on Jan 1th of 2016 (retrospectively registered). [ABSTRACT FROM AUTHOR]

Purpose: Fatigue-induced hip-abductor weakness may exacerbate lower-limb misalignments during different dynamic single-leg tasks. We sought to evaluate the effects of fatigue and task on lower limb kinematics and muscle activation and to find associations between measurements obtained in two tasks. Methods: One-group pretest–posttest design. Seventeen healthy adults (9 W) performed the single-leg squat (SLSQUAT) and the single-leg hop (SLHOP) before and after a hip-abduction fatigue protocol. Hip adduction, knee frontal plane projection angle (knee FPPA) and heel inversion displacement were measured during the eccentric phase of the SLSQUAT and the SLHOP, as well as activation of the gluteus medius (GMed), tensor fascia latae (TFL), peroneus longus (PER) and tibialis anterior (TA). Moments and tasks were compared using a repeated-measures two-way ANOVA. Correlation between tasks was evaluated using Spearman's correlation. Results: No differences in kinematics or activation were found between moments. Hip-adduction displacement (P = 0.005), GMed (P = 0.008) and PER (P = 0.037) activation were higher during SLSQUAT, while TA activation was higher during SLHOP (P < 0.001). No differences were found between tasks in knee FPPA and heel inversion. Hip-adduction and knee FPPA were not correlated between tasks, while ankle inversion displacement was positively correlated (rs = 0.524–0.746). Conclusion: Different characteristics of SLSQUAT (slower and deeper) seem to have led to increased hip adduction displacement, GMed, and PER activation and decreased TA activation, likely due to higher balance requirements. However, hip-abductor fatigue didn't influence lower-limb alignment during the tasks. Finally, evaluations should be performed with different single-leg tasks since they don't give the same lower-limb alignment information. [ABSTRACT FROM AUTHOR]

Organizations' hiring processes are increasingly shaped by various digital tools and e-recruitment systems. However, there is little understanding of the recruiters' needs for and expectations towards new systems. This paper investigates recruitment chatbots as an emergent form of e-recruitment, offering a low-threshold channel for recruiter-applicant interaction. The rapid spread of chatbots and the casual nature of their user interfaces raise questions about the perceived benefits, risks, and suitable roles in this sensitive application area. To this end, we conducted 13 semi-structured interviews, including 11 interviews with people who are utilizing recruitment chatbots and two people from companies that are developing recruitment chatbots. The findings provide a qualitative account of their expectations and motivations, early experiences, and perceived opportunities regarding the current and future use of chatbots in recruitment. While chatbots answer the need for attracting new candidates, they have also introduced new challenges and work tasks for the recruiters. The paper offers considerations that can help to redesign recruitment bots from the recruiter's viewpoint. [ABSTRACT FROM AUTHOR]

NATO's 2010 Strategic Concept established three core tasks for the Alliance: collective defense, crisis management, and cooperative security. While those tasks remain sound, the 2010 Concept reflected a different geopolitical, geostrategic, and security environment from today's, characterized by renewed conflict with Russia, concerns about China's strategic and economic ambitions, and new security challenges like hybrid threats and disinformation. Considering the changed strategic landscape and emerging challenges, we argue that NATO should make several refinements to its core tasks. European Allies must improve defense capabilities, ensuring their ability to help NATO meet its core tasks. In conjunction with the other Allied nuclear powers (the United Kingdom and France), the U.S. must renew its commitment to maintaining NATO as a nuclear alliance. NATO should adopt a more rigorous operational definition of crisis management, and a more systematic emphasis on the early warning and pre-crisis phases. Finally, while national "resilience" is already implied in Article 3ʹs requirement for member states to "maintain and develop their individual and collective capacity to resist armed attack," adding it as a fourth core task would powerfully emphasize the need for allies to address new elements of resilience, to include both technological threats and democratic backsliding. [ABSTRACT FROM AUTHOR]

Risk-taking is a fundamental aspect of life spanning diverse contexts. Despite many tests being readily available, the behavioral assessment of risk propensity in recreational contexts, where decisions are not necessarily motivated by monetary gains or losses, is not well represented. As the tower building task (TBT) shares features of recreational activities, we evaluated whether it could assess risk-taking in this type of scenario. In the TBT, participants use standard-size wooden blocks to build the tallest tower they can within a 10 min period. In the current study we (i) examined methodological modifications to the task to either promote or reduce risky behavior and (ii) tested possible associations between the TBT scores and those of two commonly used risk-taking evaluations: The Balloon Analogue Risk Task (BART) and the Sensation Seeking Scale (SSS). We found that limiting the number of permitted collapses decreased the willingness to take risks, whereas challenging participants to exceed a "record" height increased risk-taking. TBT scores of one of the conditions correlated with scores of the BART and the SSS, particularly with the subscale addressing recreational activities. These findings suggest that the TBT offers a potentially useful means of evaluating risk-taking behaviors akin to those of the recreational domain. [ABSTRACT FROM AUTHOR]

The paper presents an analysis of user tasks in the conceptual models, with an overview of the objectives and functions of the catalogue from Cutter to the International Cataloguing Principles, a critical reflection on user tasks and a proposal for a rethinking of these. The user tasks as presented in the conceptual models present critical aspects, in particular they do not bring out some important aspects concerning the users' motivations for searches and the users' competences. The presentation of some critical aspects of user Ttasks is followed by an initial proposal for a more complex reflection on how users use catalogues to carry out searches of different kinds. [ABSTRACT FROM AUTHOR]

This paper presents the first framework (up to the authors' knowledge) to address time-varying objectives in finite-horizon Deep Reinforcement Learning (DeepRL), based on a switching control solution developed on the ground of Bellman's principle of optimality. By augmenting the state space of the system with information on its visit time, the DeepRL agent is able to solve problems in which its task dynamically changes within the same episode. To address the scalability problems caused by the state space augmentation, we propose a procedure to partition the episode length to define separate sub-problems that are then solved by specialised DeepRL agents. Contrary to standard solutions, with the proposed approach the DeepRL agents correctly estimate the value function at each time-step and are hence able to solve time-varying tasks. Numerical simulations validate the approach in a classic RL environment. [ABSTRACT FROM AUTHOR]

Background: Recently, it was reported that the extent of cortico-cortical functional connections can be estimated by the correlation coefficient based on electroencephalography (EEG) monitoring. We aimed to investigate whether the EEG correlation coefficient change with motor task activation can predict the functional outcomes of hemiparetic stroke patients. Methods: Sixteen post-stroke hemiparetic patients admitted to our rehabilitation ward were studied. On admission, EEG recording to calculate the correlation coefficient was performed at rest and during motor task activation. For the analysis of the EEG data, the program software FOCUS (NIHON KOHDEN, Japan) was used. The motor function of paretic limbs was evaluated with the Fugl–Meyer Assessment (FMA) on admission and 4 weeks after admission. Results: Significant increases in the correlation coefficient with motor task activation were noted in C3-F3 or C4-F4, C3-F7 or C4-F8, and F3-F7 or F4-F8 of the lesional hemisphere. Among them, the rate of the correlation coefficient change in F3-F7 or F4-F8 in the lesional hemisphere was significantly correlated with the rate of the upper-limb FMA score change. Conclusion: The extent of the EEG correlation coefficient change with motor task activation in F3-F7 or F4-F8 of the lesional hemisphere may help predict the motor functional outcomes of hemiparetic upper limbs after stroke. [ABSTRACT FROM AUTHOR]

Current aerobic fitness testing during ISS flight does not assess either critical power (CP) or work capacity above CP (W′). Both CP and W′ have been demonstrated to be highly related to time of performance during ground analogues of lunar or planetary work tasks. This study was conducted to determine if CP measures differ between trials performed without (Control) and with (WMD) metabolic gas exchange data collection during 3-min supramaximal cycle ergometer tests. A secondary aim was to determine if peak oxygen consumption (VO 2peak) can be ascertained from a 3-min CP test. Subjects (n = 19: 11 M, 8 F) were young and healthy (VO 2peak 34.7 ± 7.7 ml/kg/min). Each completed four cycle trials: a ramp test to determine VO 2peak , a familiarization trial of the 3-min CP test, and two additional CP tests (control and WMD). Critical power (watts) was calculated as the mean power during the last 30 s of the CP tests. W′ was calculated as the power-time integral above CP. No differences (P = 0.11) were found for CP watts between the WMD trial and control conditions (172 ± 46 W, 169 ± 49 W, respectively). Similarly, no differences were found for W' (11.3 ± 5.4 WMD, 11.7 ± 4.4 kJ control, P = 0.61) and peak watts (627 ± 326 W WMD, 636 ± 335 W control, P = 0.84). No differences (P = 0.23) were observed between VO 2peak measured during the CP test (2517 ± 576 ml/min) and that of the initial ramp test (2564 ± 550 ml/min). CP, peak watts, and W' values were not influenced by gas exchange measurement performed during CP tests. It also appears that VO 2peak can be attained using the 3-min protocol. Consideration should be given towards CP testing on ISS and future missions. • The use of metabolic gas analysis does not interfere with critical power values. • It appears to be possible to obtain VO 2peak from a critical power test. • Critical power testing data can be used for exercise prescription. • NASA exercise testing/training protocols may benefit by incorporating critical power testing pre-, in-, and post-flight. [ABSTRACT FROM AUTHOR]

While exam-style questions are a fundamental educational tool serving a variety of purposes, manual construction of questions is a complex process that requires training, experience and resources. Automatic question generation (QG) techniques can be utilized to satisfy the need for a continuous supply of new questions by streamlining their generation. However, compared to automatic question answering (QA), QG is a more challenging task. In this work, we fine-tune a multilingual T5 (mT5) transformer in a multitask setting for QA, QG and answer extraction tasks using Turkish QA datasets. To the best of our knowledge, this is the first academic work that performs automated text-to-text question generation from Turkish texts. Experimental evaluations show that the proposed multitask setting achieves state-of-the-art Turkish question answering and question generation performance on TQuADv1, TQuADv2 datasets and XQuAD Turkish split. [ABSTRACT FROM AUTHOR]

Background: Therapist appropriate responsivity to client ambivalence and resistance is considered an important interpersonal skill to avoid disengagement and ensure a continued collaborative, productive process. The present study examined the predictive validity of the newly developed Resistance Vignette Task (RVT), a 10‐item rapidly administered measure of therapist ability to appropriately respond to various presentations of client resistance. Methods: Following a resistance management workshop, the concurrent and prospective predictive capacity of RVT scores were examined through test interviews with ambivalent simulators and volunteers. Results: Prospectively, in test interviews with ambivalent interviewees, higher RVT scores immediately postworkshop were associated with significantly greater responsivity (appropriate responsivity and fewer responsivity errors) at 4‐month follow‐up. RVT scores at the 4‐month follow‐up point were also concurrently associated with significantly greater therapist responsivity and lower levels of interviewee resistance. Conclusions: These findings provide further validation for the RVT as a measure of therapist responsivity in vivo, in actual interviews by predicting and being concurrently associated with therapist performance in response to client resistance. Thus, the RVT holds promise in advancing therapist training, as well as research on resistance as it represents an efficient measure of this key therapist skill. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of the study is to examine enterprise searching practices across different work areas and work tasks in an enterprise search system in an international biotechnology company. Design/methodology/approach: A mixed-method approach studying employees' authentic search activities during a 4-month period by log data, questionnaire survey and interviews. The log data analysed the entire active searcher group, whereas the questionnaire and interviews focused on frequent searchers. Findings: The three studies provided insight into the searching activities and an understanding of the way searchers used the enterprise search system to search for information as part of their work tasks. The data identified three searcher groups, each with specific search characteristics. Four work task types were identified, and for all four types the searchers applied a tracing searching technique with use of contextual and historical relationships as paths. Practical implications: The findings point to the importance of knowledge on historical and contextual relations in enterprise search. Originality/value: The work sheds new light on enterprise searchers' information search practices. A significant contribution is the identification of a tracing search method used in relation to four essential work task types. Another contribution is the importance of historical and contextual knowledge to support the tracing search and decide what paths to follow. [ABSTRACT FROM AUTHOR]

One of the proposed neural mechanisms involved in working memory is coupling between the theta phase and gamma amplitude. For example, evidence from intracranial recordings shows that coupling between hippocampal theta and cortical gamma oscillations increases selectively during working memory tasks. Theta-gamma phase-amplitude coupling can also be measured non-invasively through scalp EEG; however, EEG can only assess coupling within cortical areas, and it is not yet clear if this cortical-only coupling is truly memory-specific, or a more general phenomenon. We tested this directly by measuring cortical coupling during three different conditions: a working memory task, an attention task, and a passive perception condition. We find similar levels of theta-gamma coupling in all three conditions, suggesting that cortical theta-gamma phase-amplitude coupling is not a memory-specific signal, but instead reflects some other attentional or perceptual processes. Implications for understanding the brain dynamics of visual working memory are discussed. [ABSTRACT FROM AUTHOR]

In this contribution, the author contends that the way in which Pieter Lemmens interprets the transcendental of technology, particularly through the work of Bernard Stiegler, is only one of the possible ways of understanding the transcendental of technology. His thesis is that there are many other transcendentals of technology besides technology itself. The task of a philosophy of technology beyond the empirical turn could precisely consist in exploring these multiple transcendentals of technology, along with their multiple relations. In the first section, the author considers and criticizes the "empirical transcendentality" that characterizes most of the current philosophical approaches to technology, in particular when it comes to ethical issues. In the second section, he proposes to include Lemmens' perspective in a more general theory (and consequent practices) about the transcendentals of technology. The transcendentals of technology include social symbolic forms, culture, language, media, and many other dimensions that philosophy of technology has not systematically explored yet. [ABSTRACT FROM AUTHOR]

Comparative researchers have heavily focused their studies of social cognition on species that live in large social groups, while neglecting other potential predictors of social cognition. African crested porcupines (Hystrix cristata) are relatively rare among mammals in that they are cooperative breeders that pair for life. Little is known about their social cognition, but they are good candidates for exploring cooperative behavior due to the need to coordinate behavior to cooperatively raise young. Cooperation, as defined in this study, is the process by which two or more participants perform independent actions on an object to obtain a reward for all parties. Humans are thought to outperform all other species in the frequency and magnitude of cooperative behaviors. Yet, only by studying a variety of species can researchers fully understand the likely selection pressures for cooperation, such as cooperative breeding. Here, we pilot tested the feasibility of the popular loose-string task with a mated pair of African crested porcupines, a task that required the porcupines to cooperatively pull ropes to access an out of reach platform baited with food rewards. Other species presented with this task were able to work together to receive rewards but did not always demonstrate understanding of the role of their partner. The porcupines achieved success but did not appear to coordinate their actions or solicit behavior from their partner. Thus, similar to other species, they may achieve success in this task without taking their partner's role into account. This study demonstrates that the loose string task can be used to assess cooperation in porcupines. However, further experiments are needed to assess the porcupine's understanding of their partner's role under this paradigm. [ABSTRACT FROM AUTHOR]

In this study, we developed an evaluation method using image analysis for reaching tasks. Using this method, we studied forearm function during the reaching task in rats that received a unilateral injection of 6-OHDA into the striatum. The success ratio of the reaching task reduced to 40.5% seven days after the injection. In addition, significant changes were observed in the pronation angle of the forearm, posture control, and targeting (i.e., the distance between all fingertips and the center of the target pellet). Thus, unilateral injection of 6-OHDA reduces dopaminergic function in the brain and causes deterioration of forearm function and posture control in the reaching task. [ABSTRACT FROM AUTHOR]

Suspension-based locks are widely used in real-time systems to coordinate simultaneous accesses to exclusive shared resources. Although suspension-based locks have been well studied for sequential real-time tasks, little work has been done on this topic for parallel real-time tasks. This article for the first time studies the problem of how to extend existing sequential-task locking protocols and their analysis techniques to the parallel task model. More specifically, we extend two locking protocols OMLP and OMIP, which were designed for clustered scheduling of sequential real-time tasks, to federated scheduling of parallel real-time tasks. We present corresponding blocking analysis techniques, and develop path-oriented techniques to analyze and count blocking time. Schedulability tests with different efficiency and accuracy are further developed. Experiments are conducted to evaluate the performance of our proposed approaches against the state-of-the-art. [ABSTRACT FROM AUTHOR]