Execution Behavior Research Articles

Analyzing Lane Change Execution Behavior on Expressway Using an Instrumented Vehicle: A Random Effect Accelerated Failure Time Approach

Analyzing Lane Change Execution Behavior on Expressway Using an Instrumented Vehicle: A Random Effect Accelerated Failure Time Approach

Neural correlates of motor imagery and execution in real-world dynamic behavior: evidence for similarities and differences.

A large body of evidence shows that motor imagery and action execution behaviors result from overlapping neural substrates, even in the absence of overt movement during motor imagery. To date it is unclear how neural activations in motor imagery and execution compare for naturalistic whole-body movements, such as walking. Neuroimaging studies have not directly compared imagery and execution during dynamic walking movements. Here we recorded brain activation with mobile EEG during walking compared to during imagery of walking, with mental counting as a control condition. We asked 24 healthy participants to either walk six steps on a path, imagine taking six steps, or mentally count from one to six. We found beta and alpha power modulation during motor imagery resembling action execution patterns; a correspondence not found performing the control task of mental counting. Neural overlap occurred early in the execution and imagery walking actions, suggesting activation of shared action representations. Remarkably, a distinctive walking-related beta rebound occurred both during action execution and imagery at the end of the action suggesting that, like actual walking, motor imagery involves resetting or inhibition of motor processes. However, we also found that motor imagery elicits a distinct pattern of more distributed beta activity, especially at the beginning of the task. These results indicate that motor imagery and execution of naturalistic walking involve shared motor-cognitive activations, but that motor imagery requires additional cortical resources.

Compensation Incentive of Executives under the Situation of Synergy or Mutual Exclusion of Corporate Profit and Innovation Tasks: Based on Incentive Game Model between Principal and Agent

Based on the synergistic or mutually exclusive relationship between corporate profits and innovation tasks, such that shareholders can predict these two scenarios, this study constructed a multitask principal-agent mode considering “the degree of synergy or mutual exclusion between profit and innovation,” “salary reduction penalty,” and other factors. Based on mathematical logic, we determined the correlation and influence of synergistic or mutually exclusive degrees on executive profitability compensation and salary reduction penalties. Based on the 2016–2022 annual reports of A-share listed companies registered in Shanghai and Shenzhen, China, this research empirically verifies the effects of the aforementioned degree of synergy and mutual exclusion on managers’ compensation incentives. The research conclusions are stated as follows: (1) If shareholders can predict the synergy between profitability and innovation activities, then the salary reduction penalty (representing executive compensation stickiness) exhibits a significant negative correlation with the degree of synergy μ, whereas if the coefficient of executive profitability compensation βi (compensation sensitivity) bears a moderately positive relationship with μ, the shareholders will, to a certain extent, improve the performance-sharing coefficient of senior executives and reduce the penalty coefficient of salary reduction to increase the overall income level of senior executives via the incentive effect. (2) If shareholders can predict the mutually exclusive effect of profitability and innovation activities, the salary reduction penalty (representing executive compensation stickiness) is significantly positively correlated with the degree of mutual exclusion μ, whereas the coefficient of executive profitability compensation βi (compensation sensitivity) negatively affects the degree of synergy μ to a certain extent; however, this negative relationship is not prominent. This indicates that to avert the short-sighted behaviour of executives, shareholders will drive them toward investing in innovation by reducing the profitability compensation coefficient as well as increasing the innovative compensation coefficient. Simultaneously, the shareholders will increase the penalty coefficient of salary reduction to urge the executives to strengthen the operation and management of other profitable activities of the enterprise to maintain short-term performance at a reasonable level. (3) If shareholders cannot predict the synergy between profitability and innovation activities, they will attribute the source of excess earnings to the efforts of the senior executives. In particular, a greater degree of synergy is more likely to reduce the penalty for the senior executives. If the shareholders cannot predict the mutually exclusive effect of profitability and innovation tasks, the correlation between the penalty coefficient of salary reduction and the degree of mutual exclusion is related to the decline in performance. In such a scenario, the shareholders attribute the short-term deterioration in corporate performance to the negligence of the senior executives in corporate operations. Consequently, they urge senior executives to seriously operate the enterprise by increasing the penalty for senior executives. If the decline in performance exceeds the critical value, the shareholders will effectively motivate the senior executives by reducing the penalty coefficient of their salary reduction and moderately increasing their profit-making compensation sharing coefficient to avoid negative investment or their resignation.

A modular artificial intelligence and asset administration shell approach to streamline testing processes in manufacturing services

The increasing demand for personalized products and cost-effectiveness has highlighted the necessity of integrating intelligence into production systems. This integration is crucial for enabling intelligent control that can adapt to variations in features, parts, and conditions, thereby enhancing functionalities while reducing costs. This research emphasizes the incorporation of intelligence in testing processes within production systems. We introduce a novel approach for controlling testing functionality using an asset administration shell enriched with modular artificial intelligence. The proposed architecture is not only effective in controlling the execution behavior through services but also offers the distinct advantage of a modular design. This modularity significantly contributes to the system’s adaptability and scalability, allowing for more efficient and cost-effective solutions as different machine-learning models may be substituted to meet requirements. The effectiveness of this approach is validated through a practical use case of leak testing, demonstrating the benefits of the modular architecture in a real-world application.

The effects of local newspaper closures on nonprofits’ executive compensation

We examine the role of local newspapers in monitoring the nonprofit sector by testing how local newspaper closures affect nonprofits’ executive compensation levels. Although prior research establishes that local newspaper closures affect behavior of for-profits and municipalities, the unique governance and enforcement environment of nonprofits make it unclear whether and how closures of local newspapers will affect nonprofits’ executive compensation spending behavior. Consistent with local newspapers serving as an alternative monitoring mechanism within the nonprofit sector, we find that, following local newspaper closures, the levels of nonprofits’ executive compensation spending increases. This effect is less pronounced among nonprofits having audits and among those with better internal governance. Our results suggest that newspaper closures exacerbate agency problems among nonprofits particularly when alternative monitoring mechanisms of nonprofits are weaker.

A Malware Detection Framework Based on Semantic Information of Behavioral Features

As the amount of malware has grown rapidly in recent years, it has become the most dominant attack method in network security. Learning execution behavior, especially Application Programming Interface (API) call sequences, has been shown to be effective for malware detection. However, it is troublesome in practice to adequate mining of API call features. Among the current research methods, most of them only analyze single features or inadequately analyze the features, ignoring the analysis of structural and semantic features, which results in information loss and thus affects the accuracy. In order to deal with the problems mentioned above, we propose a novel method of malware detection based on semantic information of behavioral features. First, we preprocess the sequence of API function calls to reduce redundant information. Then, we obtain a vectorized representation of the API call sequence by word embedding model, and encode the API call name by analyzing it to characterize the API name’s semantic structure information and statistical information. Finally, a malware detector consisting of CNN and bidirectional GRU, which can better understand the local and global features between API calls, is used for detection. We evaluate the proposed model in a publicly available dataset provided by a third party. The experimental results show that the proposed method outperforms the baseline method. With this combined neural network architecture, our proposed model attains detection accuracy of 0.9828 and an F1-Score of 0.9827.

Experimental EMFI detection on a RISC-V core using the Trace Verifier solution

Physical attacks are powerful threats that can cause changes in the execution behavior of a program. Control-Flow Integrity (CFI) is used to check the program’s flow execution, ensuring that it remains unaltered by these attacks. The RISC-V Trace Encoder (TE) provides valuable information about the user program’s execution path, and is used as part of a CFI solution. An enhanced version of the TE specifications permits detecting intricate fault models such as the corruption of any discontinuity instruction, using an additional Trace Verifier (TV) hardware module. In this paper, we present a buffer overflow software attack simulation and experimental ElectroMagnetic Fault Injection (EMFI) attacks conducted on an Field Programmable Gate Array (FPGA) board that implements a RISC-V core linked to the enhanced TE and TV modules. Unlike existing CFI solutions, our proposed approach does not require modifications to the RISC-V compiler, user application code or the RISC-V core. The average overhead of our solution in terms of hardware area, memory and power consumption are equal to 13.6%, 3.5% and 9% respectively.

Uncovering the distinct macro-scale anatomy of dysexecutive and behavioural degenerative diseases.

There is a longstanding ambiguity regarding the clinical diagnosis of dementia syndromes predominantly targeting executive functions versus behaviour and personality. This is due to an incomplete understanding of the macro-scale anatomy underlying these symptomatologies, a partial overlap in clinical features and the fact that both phenotypes can emerge from the same pathology and vice versa. We collected data from a patient cohort of which 52 had dysexecutive Alzheimer's disease, 30 had behavioural variant frontotemporal dementia (bvFTD), seven met clinical criteria for bvFTD but had Alzheimer's disease pathology (behavioural Alzheimer's disease) and 28 had amnestic Alzheimer's disease. We first assessed group-wise differences in clinical and cognitive features and patterns of fluorodeoxyglucose (FDG) PET hypometabolism. We then performed a spectral decomposition of covariance between FDG-PET images to yield latent patterns of relative hypometabolism unbiased by diagnostic classification, which are referred to as 'eigenbrains'. These eigenbrains were subsequently linked to clinical and cognitive data and meta-analytic topics from a large external database of neuroimaging studies reflecting a wide range of mental functions. Finally, we performed a data-driven exploratory linear discriminant analysis to perform eigenbrain-based multiclass diagnostic predictions. Dysexecutive Alzheimer's disease and bvFTD patients were the youngest at symptom onset, followed by behavioural Alzheimer's disease, then amnestic Alzheimer's disease. Dysexecutive Alzheimer's disease patients had worse cognitive performance on nearly all cognitive domains compared with other groups, except verbal fluency which was equally impaired in dysexecutive Alzheimer's disease and bvFTD. Hypometabolism was observed in heteromodal cortices in dysexecutive Alzheimer's disease, temporo-parietal areas in amnestic Alzheimer's disease and frontotemporal areas in bvFTD and behavioural Alzheimer's disease. The unbiased spectral decomposition analysis revealed that relative hypometabolism in heteromodal cortices was associated with worse dysexecutive symptomatology and a lower likelihood of presenting with behaviour/personality problems, whereas relative hypometabolism in frontotemporal areas was associated with a higher likelihood of presenting with behaviour/personality problems but did not correlate with most cognitive measures. The linear discriminant analysis yielded an accuracy of 82.1% in predicting diagnostic category and did not misclassify any dysexecutive Alzheimer's disease patient for behavioural Alzheimer's disease and vice versa. Our results strongly suggest a double dissociation in that distinct macro-scale underpinnings underlie predominant dysexecutive versus personality/behavioural symptomatology in dementia syndromes. This has important implications for the implementation of criteria to diagnose and distinguish these diseases and supports the use of data-driven techniques to inform the classification of neurodegenerative diseases.

Research on the influence of equity incentive and internal control quality on company investment decision under the 14th five-year plan

ABSTRACT With the increasing intensification of market competition, companies need to implement innovative strategies to gain market advantages. As an effective measure for companies to reduce agency costs between management and shareholders and alleviate the conflict of interest between the two, equity incentive can directly affect the behaviour of company executives. Investment decision is the foundation of a company’s healthy growth and cash flow growth in the future. This paper selects the panel data of Chinese listed companies from 2011 to 2021 as a sample, uses the quality of internal control as an intermediary variable in the process of measuring the implementation of equity incentives, and empirically studies the relationship between equity incentives and corporate investment decisions. The results show that there is a positive correlation between equity incentives and investment decisions, and the quality of internal control plays an intermediary role between the two. Equity incentive can optimize the internal control, improve the quality of internal control, so as to effectively promote the investment decision of companies. The implementation of equity incentives gives companies a competitive advantage while also adding momentum to economic development, thereby enhancing national competitiveness.

Performance and profiling data of plane-wave calculations in quantum ESPRESSO simulation on three supercomputing centres.

This dataset reflects the parallel execution profiles of five Quantum ESPRESSO simulation (QE) versions in finding the total energy of the Cerium Oxide lattice using the self-consistent field (SCF) method. The data analysis used a strong scale setting to identify the optimal parameters and computing resources needed to complete a single SCF loop for one specific material efficiently. This analysis notably contributed to achieving the Best Performance Award at the 5th APAC HPC-AI Competition. The data comprises three sets. The first set features the parallel execution traces captured via the Extrae performance profiling tool, offering a broad view of the QE's model execution behaviour and how it used computational resources. The second set records how long QE's model ran on a single node at three HPC centres: ThaiSC TARA in Thailand, NSCC ASPIRE-1 in Singapore, and NCI Gadi in Australia. This set focuses on the impact of adjusting three parameters for K-point parallelisation. The final set presents benchmarking data generated by scaling out the QE's model across 32 nodes (1,536 CPU cores) on the NCI Gadi supercomputer. Despite its focus on a single material, the dataset serves as a roadmap for researchers to estimate required computational resources and understand scalability bottlenecks, offering general guidelines adaptable across different HPC systems.

A Comparative Study of Social Information Processing and Executive Functioning in Children with Attention Deficit and Hyperactivity Disorder and Typically Developing Children

Introduction: Examining the performance of children with Attention Deficit Hyperactivity Disorder (ADHD) in each step of the social information processing and their executive functioning behaviors while comparing them to typically developing (TD) children and determining their limitations in these processes is important for reducing the future risks that children with ADHD may face in academic and social life. In this context, the aim of the study is to comparatively examine the social information processing and executive functioning behaviors of children with ADHD and TD children. Method: The study was conducted using a general survey model, which is one of the quantitative research designs. The participants of the study included 25 children diagnosed with ADHD, aged between 8 and 10, and 25 TD children of the same gender and age range. Additionally, 25 teachers and 50 parents participated in the study. The data collection tools used in the study were the Social Information Processing Assessment Form and the Parent and Teacher Form of the Behavioral Rating Inventory of Executive Functions (BRIEF). Findings: The study findings showed significant differences between children with ADHD and TD children in all stages of the Social Information Processing Assessment Form. Similar significant differences were also found in all the sub-scales and sub-dimensions of the Parent and Teacher Form of the Behavioral Rating Inventory of Executive Functions. The relationships between social information processing skills and executive functioning skills also revealed significant associations between some sub-stages of the Social Information Processing Skills Assessment Form and some sub-dimensions of the Parent and Teacher Form of the Behavioral Rating Inventory of Executive Functions. Discussion: The findings indicate that children with ADHD experience limitations in each of the six steps of the Social Information Processing Model and in some sub-dimensions of executive functions when compared to their TD peers. The findings emphasize the significance of the relationships between social information processing and executive functioning in the development of social and academic skills in children with ADHD.

호텔 총주방장의 조직미덕에 의한 직무열의와의 관계에서 정서적몰입의 매개역할

In this study, considering the characteristics of the hotel industry, the relationship between the organizational virtues of the head chef of the hotel and the employee's job enthusiasm was identified. It is intended to provide implications for To summarize the research results of this thesis, first, it was found that the organizational virtues of the head chef of a hotel had a statistically significant (+) effect on job enthusiasm. Second, the executive chef's organizational virtue was found to have a significant (+) effect on the emotional commitment of employees. Third, it was found that employees' job zeal had a significant (+) effect on their emotional commitment. Finally, as a result of verifying the mediating effect of emotional commitment between the executive chef's organizational virtue and job zeal, which is the core of this paper, it was found to have a complete mediating effect. This means that job enthusiasm can be improved through job satisfaction, trust, and a sense of calling due to emotional immersion in forming relationships with employees due to the executive chef's virtuous behavior in organizational management. importance has been demonstrated.

Associations Between Executive Functioning, Behavioral Functioning, and Adaptive Functioning Difficulties in Wiedemann-Steiner Syndrome.

Wiedemann-Steiner syndrome (WSS) is a neurogenetic disorder caused by heterozygous variants in KMT2A. Recent investigations suggest increased anxiety and behavior regulation challenges among those with WSS although the neurobehavioral phenotype remains largely unknown. This study aims to examine the pattern of and associations between executive functioning (EF) and behavior functioning among those with WSS. This study involved utilizing caregiver-report inventories (Behavior Rating Inventory of Executive Function 2nd Edition, BRIEF-2; Adaptive Behavior Assessment 3rd Edition, ABAS-3; Strengths and Difficulties Questionnaire, SDQ) to assess day-to-day behavior functioning among those with WSS (N = 24; mean age = 10.68years, SD = 3.19). Frequency of clinical elevations in daily difficulties in EF, adaptive behaviors, and behavior regulation were reported. Correlations and hierarchical linear regressions were used to determine the relationships between EF with behavior and adaptive functioning. Out of our sample, 63% met clinical levels of executive functioning difficulties on the BRIEF-2, and 75% with Hyperactivity and 54% with Emotional Problems on the SDQ. In addition, 33% were rated >2 SD below the normative mean in overall adaptive functioning on the ABAS-3. Elevated ratings in BRIEF-2 Shift, reflective of challenges with mental flexibility, predicted more Emotional Problems and accounted for 33.5% of its variance. More difficulties in Emotional Control were related to greater adaptive deficits, accounting for 33.3% of its variance. Those with WSS are at risk for EF deficits, hyperactivity, and emotional dysregulation. EF correlates with adaptive and affective behaviors, highlighting the promise of behavioral interventions to target cognitive flexibility, emotional awareness, and reactivity in this population.

TI-MVD: A temporal interaction-enhanced model for malware variants detection

Advanced malware variants attacks have been posing catastrophes to the cyber ecosystem. However, existing malware variants detection methods are feeble for detecting the advanced malware variants due to the twofold flaws. First, most detection methods focus on analyzing the isolated features instead of investigating the meaningful contextual interactions between fine-grained malware entities, resulting in poor performance. Second, the existing graph-based detection approaches are incapable of leveraging the temporal dependence information between execution behaviors to capture the malicious evolutionary patterns and incur expensive time costs when traversing vast invalid paths. To overcome these limitations, this paper proposes TI-MVD, a temporal interaction-enhanced malware variants detection framework. TI-MVD models the fine-grained malware objects with a temporal heterogeneous graph, which can simultaneously leverage the temporal and structural embedding features to detect malware variants. Concretely, a novel end-to-end interaction-enhanced embedding approach is proposed to learn the structural embedding, which is capable of incorporating explicit and implicit interactive information between node pairs to boost detection effectiveness. Meanwhile, a strong-correlated clique method exploiting two coupled GRUs is presented to handle the temporal interactions in a parallel manner, which can drastically reduce the time cost of temporal embedding. Experimental results on four real-world datasets demonstrate that our proposed TI-MVD outperforms the state-of-the-art methods by a large margin.

Sex-specific associations between maternal phthalate exposure and neurodevelopmental outcomes in children at 2 years of age in the APrON cohort

BackgroundThere is inconsistent evidence regarding the sex-specific associations between prenatal phthalate exposure and children’s neurodevelopment. This could be due to differences in the phthalate exposures investigated and the neurodevelopmental domains assessed. ObjectiveTo evaluate the associations between prenatal phthalate exposure and sex-specific outcomes on measures of cognition, language, motor, executive function, and behaviour in children 2 years of age in the Alberta Pregnancy Outcomes and Nutrition (APrON) cohort. MethodsWe evaluated the associations between prenatal phthalate exposure and sex-specific neurodevelopmental outcomes in children at 2 years of age using data from 448 mothers and their children (222 girls, 226 boys). Nine phthalate metabolites were measured in maternal urine collected in the second trimester of pregnancy. Children’s cognitive, language, and motor outcomes were assessed using the Bayley Scales of Infant Development – Third Edition (Bayley-III). Parents completed questionnaires on children’s executive function and behavior, the Behavior Rating Inventory of Executive Function- Preschool Version (BRIEF-P) and Child Behavior Checklist (CBCL), respectively. Sex-stratified robust multivariate regressions were performed. ResultsHigher maternal concentrations of ΣDEHP and its metabolites were associated with lower scores on the Bayley-III Cognitive (β’s from −11.8 to −0.07 95% CI’s from −21.3 to −0.01), Language (β’s from −11.7 to −0. 09, 95% CI’s from −22.3 to −0.02) and Motor (β’s from −10.9 to −0.07, 95% CI from −20.4 to -0.01) composites in boys. The patterns of association in girls were in the opposite direction on the Cognitive and Language composites; on the Motor composite they were in the same direction as boys, but of reduced strength. Higher concentrations of ΣDEHP and its metabolites were associated with higher scores (i.e., more difficulties) on all measures of executive function in girls: inhibitory self-control (B’s from 0.05 to 0.11, 95% CI s from −0.01 to 0.15), flexibility (B’s from 0.04 to 0.11, 95% CI s from 0.01 to 0.21) and emergent metacognition (B’s from −0.01 to 0.06, 95% CIs from −0.01 to 0.20). Similar patterns of attenuated associations were seen in boys. Higher concentrations of ΣDEHP and its metabolites were associated with more Externalizing Problems in girls and boys (B’s from 0.03 to 6.82, 95% CIs from −0.08 to 12.0). Two phthalates, MMP and MBP, had sex-specific adverse associations on measures of executive function and behaviour, respectively, while MEP was positively associated with boys’ cognitive, language, and motor performance. Limited associations were observed between mixtures of maternal phthalates and sex-specific neurodevelopmental outcomes. ConclusionsMaternal prenatal concentrations of DEHP phthalates were associated with sex specific difference on measures of cognition and language at 2 years of age, specifically, poorer outcomes in boys. Higher exposure to DEHP was associated with poorer motor, executive function, and behavioural outcomes in girls and boys but the strength of these associations differed by sex. Limited associations were noted between phthalate mixtures and child neurodevelopment.

Poor sleep quality and its associated neurocognitive function in children with obesity with or without obstructive sleep apnea.

To evaluate the associations of OSA severity, snoring symptoms, subjective sleep quality, and daytime sleepiness with executive functioning and behaviors in children with obesity. This was a cross-sectional study of children aged 8-18years with obesity and symptoms suggestive of OSA. All participants underwent an overnight polysomnography and completed a set of questionnaires to assess their sleep-related breathing disordered (SRBD) symptoms [Pediatric Sleep Questionnaire (SRBD-PSQ)], sleep quality [Pittsburgh Sleep Quality Index (PSQI)], executive function [Behavior Rating Inventory of Executive Function (BRIEF)], and inattention and hyperactivity symptoms (Conners-3 Parent Short Form). A total of 85 children (62% male, mean age: 13.9 ± 3.0years) were included in this analysis, of whom 36, 16, and 33 were categorized into the non-OSA (obstructive apnea hypopnea index, OAHI < 1.5/h), mild OSA (OAHI 1.5-5/h), and moderate-severe OSA (OAHI ≥ 5/h) groups, respectively. Of 85 participants, 27(32%) were classified with poor sleep quality (PSQI composite score ≥ 8). From multiple linear regression analyses, poor sleep quality and sleepiness were both independently associated with higher BRIEF behavioral regulation T-score, metacognition T-score, and global executive composite T-score in the fully adjusted model. In addition, poor sleep quality was also independently associated with higher Conners-3 inattention and executive functioning T-scores, while greater sleepiness was also associated with a higher learning problem T-score. The presence of OSA and snoring were not associated with any cognitive outcomes. Subjective sleep quality and daytime sleepiness, but not OSA severity and snoring symptoms, were independently associated with executive functioning and behavioral problems in children with obesity.

Mind the gap: trajectory of cognitive development in young individuals with sickle cell disease: a cross-sectional study.

Compared to typically developing children and young adults (CYA-TD), those living with Sickle Cell Disease (CYA-SCD) experience more cognitive difficulties, particularly with executive function. Few studies have examined the relative importance of silent cerebral infarction (SCI), haemoglobin and arterial oxygen content on age-related cognitive changes using cross-sectional or longitudinal (developmental trajectory) data. This study presents cohort data from a single timepoint to inform studies with multiple timepoints. We compared cross-sectional raw and scaled scores as age-related changes in cognition (trajectories) in CYA-SCD and age-and ethnicity-matched CYA-TD. We also compared cross-sectional age-related changes in cognition (trajectories) in CYA-SCD with and without SCI to CYA-TD. General cognitive abilities were assessed using Wechsler Intelligence Scales, including the Verbal Comprehension Index (VCI) and Perceptual Reasoning Index (PRI) underpinning IQ. Executive function was evaluated using the Delis-Kaplan Executive Function System (D-KEFS) Tower subtest and the Behaviour Rating Inventory of Executive Function (BRIEF) questionnaire. SCI were identified from contemporaneous 3 T MRI; participants with overt stroke were excluded. Recent haemoglobin was available and oxygen saturation (SpO2) was measured on the day of the MRI. Data were available for 120 CYA-SCD [62 male; age = 16.78 ± 4.79 years; 42 (35%) with SCI] and 53 CYA-TD (23 male; age = 17.36 ± 5.16). Compared with CYA-TD, CYA-SCD experienced a delayed onset in VCI and slower rate of development for BRIEF Global Executive Composite, Metacognition Index (MI), and Behaviour Regulation Index. The rate of executive function development for the BRIEF MI differed significantly between CYA-TD and CYA-SCD, with those with SCI showing a 26% delay compared with CYA-TD. For CYA-SCD with SCI, arterial oxygen content explained 22% of the variance in VCI and 37% in PRI, while haemoglobin explained 29% of the variance in PRI. Age-related cognitive trajectories of CYA-SCD may not be impaired but may progress more slowly. Longitudinal studies are required, using tests unaffected by practice. In addition to initiation of medical treatment, including measures to improve arterial oxygen content, early cognitive intervention, educational support, and delivery of extracurricular activities could support cognitive development for CYA-SCD.Graphical Abstract.

CLC: A cross-level program characterization method

Characterization of program execution plays a key role in performance improvement. There are numerous transformations applied to each step that a program takes on its lowering from source code to a compiler intermediate representation to machine language to microarchitecture-specific execution. The unpredictable benefit of each transformation step could lead a notionally superior algorithm to exhibit inferior performance once actually run, and it can be hard to discern which step in the transformation path contradicted the code developer’s assumptions.Conventional approaches to program-execution characterization consider the behavior after only a single one of those steps, which limits the information that can be provided to the user. To help address the issue of myopic views of program execution, this paper presents a novel cross-level characterization approach for understanding the behavior of program execution at different levels in the process of writing, compiling, and running a program. We show that this approach provides a richer view of the sources of performance gains and losses and helps identify program execution in a more accurate manner.

The Differential Moderating Effect of Executive Compensation on Innovation Investment and Cash Holding Value in China

In the context of technological innovation promoting the long-term sustainable development of enterprises, how to better motivate senior executives to create greater value for an enterprise is being widely discussed. In particular, the COVID-19 outbreak has raised concerns about whether companies can deliver more value by holding large amounts of cash. However, although scholars have conducted a lot of research on topics such as innovation and firm value, how differentiated executive compensation incentives regulate the relationship between firm innovation and the value of cash holdings has hardly been explored. This paper selects the balanced panel data of 1470 A-share listed companies from 2012 to 2020 in China to explore the relationship between innovation investment, executive compensation, and the value of cash holdings. It is found that innovation investment has a positive impact on the value of the cash holdings. Based on Herzberg’s hygiene motivational factors, different types of executive compensation may have a hygiene effect or a motivational effect, which is different. As a result, the moderating effect of executive compensation on innovation investment and the value of cash holdings are significantly different. Executive equity compensation and in-service consumption are motivational attributes. They have a positive moderating effect on innovation investment and the value of cash holdings. The moderating effect of executive monetary compensation on innovation investment and the value of cash holdings changes with the change in monetary compensation. When monetary compensation is lower than the threshold value, monetary compensation is reflected as a hygiene attribute, so it has no significant positive moderating effect on innovation investment and the value of cash holdings. When monetary compensation is higher than the threshold value, monetary compensation is reflected as a motivational attribute, so it has a significant positive moderating effect on innovation investment and the value of cash holdings. Meanwhile, it is tested that monetary compensation is not manipulated by executive compensation defense behavior when it is reflected as motivational attributes.

A Type System for Safe Intermittent Computing

Batteryless energy-harvesting devices enable computing in inaccessible environments, at a cost to programmability and correctness. These devices operate intermittently as energy is available, using a recovery system to save and restore state. Some program tasks must execute atomically w.r.t. power failures, re-executing if power fails before completion. Any re-execution should typically be idempotent —its behavior should match the behavior of a single execution. Thus, a key aspect of correct intermittent execution is identifying and recovering state causing undesired non-idempotence. Unfortunately, past intermittent systems take an ad-hoc approach, using unsound dataflow analyses or conservatively recovering all written state. Moreover, no prior work allows the programmer to directly specify idempotence requirements (including allowable non-idempotence). We present curricle, the first type system approach to safe intermittence, for Rust. Type level reasoning allows programmers to express requirements and retains alias information crucial for sound analyses. Curricle uses information flow and type qualifiers to reject programs causing undesired non-idempotence. We implement Curricle’s type system on top of Rust’s compiler, evaluating the prototype on benchmarks from prior work. We find that Curricle benefits application programmers by allowing them to express idempotence requirements that are checked to be satisfied, and that targeting programs checked with Curricle allows intermittent system designers to write simpler recovery systems that perform better.