Domain Specificity Research Articles

Fractional-order PID controller design via optimal selection strategy of frequency domain specifications

In this paper, a novel fractional-order Proportional-Integral Derivative (PID) controller design depending on optimal selection of frequency domain specifications is proposed for time delay systems. The frequency domain specification sets, namely, (i) phase margin and gain crossover frequency and (ii) phase margin and gain margin are determined so that the reference model is optimal according to three time domain performance indices, i.e. Integral Square Error (ISE), Integral Time Square Error (ITSE) and Integral Absolute Error (IAE). Here, the delayed Bode's ideal transfer function is employed in the reference model. Moreover, the stability region of the reference model is given via a theorem. In simulation studies, the proposed methodology is compared with other two different methods using the same frequency domain specifications. It is observed that the proposed optimal fractional-order PID controllers outperform according to the mentioned performance indices, and they also possess considerably acceptable performance in terms of other time domain specifications such as overshoot, settling time, etc.

The cost of guilt: unpacking the emotional mechanism between work-to-family conflict and unethical pro-family behavior

Drawing on the appraisal theory of emotions and domain specificity perspective, we explore why and when work-to-family conflict leads to unethical pro-family behavior in the workplace. In particular, we propose that work-to-family conflict reinforces unethical pro-family behavior via employee felt guilt. Further, supervisor support for family issues attenuates the relationship between work-to-family conflict and felt guilt, whereas perceived forgiveness climate strengthens the relationship between felt guilt and unethical pro-family behavior. Two time-lagged field studies conducted in Pakistan and China supported our hypotheses. Study 1 demonstrated that work-to-family guilt mediated the relationship between work-to-family conflict and unethical pro-family behavior. Study 2 replicated these findings and provided additional support for our boundary conditions. Specifically, supervisor support for family issues buffered the positive effect of work-to-family conflict on work-to-family guilt; perceived forgiveness climate amplified the positive effect of work-to-family guilt on unethical pro-family behavior. Theoretical and practical implications of our findings were discussed.

A graphical technique of controller design and selection of lower and upper bounds in controller design using optimization techniques

AbstractThe regulation and stabilization of a system's output to achieve desired performance and ensure system reliability require the use of different controllers, but selecting appropriate control parameters presents a challenge in ensuring robustness and stability. Proportional–integral–derivative (PID) controllers are popularly used due to their simplicity and effectiveness in addressing these challenges. In this paper, a simple, effective, and efficient, novel graphical technique is proposed to design PID and its variants (PI/PD) controllers, which addresses the challenges in selecting appropriate control parameters. The method involves creating three equispaced vectors for controller parameters , and obtaining a 3D (2D in PI/PD) Cartesian grid of these vectors. All nodes in the grid provide several possible controllers, and integral time squared error (ITSE) is calculated for each controller from the closed‐loop step response of the system. The obtained ITSE is plotted in a 4D (PID) or 3D (PI/PD) graph, and controller parameters corresponding to the minimum value of ITSE are identified. Furthermore, the proposed graphical technique aids in choosing the lower and upper bounds (LB and UB) if the controller is designed using optimization techniques. The better selection of LB and UB reduces the search space resulting in lesser execution time and fewer iterations. To validate the proposed graphical technique, we designed various controllers for widely‐used brush‐less DC and switch reluctance motors in electric vehicles. Additionally, by choosing the LB and UB with the proposed technique, controllers are also designed using three optimization techniques: particle swarm optimization, black widow optimization algorithm, and honey badger algorithm. The obtained controllers using the graphical technique outperformed the optimization techniques in terms of time and frequency domain specifications, and the proposed selection of lower and upper bounds resulted in improved performance in terms of iterations and execution time.

Grounding and Deepening Academic Writing in Human Resource Development: The Role of Selecting and Representing the Supporting Literature

That all academic writing should be based on a comprehensive review of previous research is well understood. Yet how to accomplish this task given the burgeoning literature in our field and in the many contributing fields of study has received surprisingly little attention in publishing guidelines in HRD and related fields. To encourage the development of HRD scholarship as a distinct and yet interdisciplinary body of knowledge, discernment, justification, and clarity about the selection and representation of the existing literature are needed in three areas. Domain specificity is concerned with the link to the HRD disciplinary base, practice relevance situates the work in a recognized HRD practice domain, and communicative interest clarifies the author’s value stance. The conclusion addresses implications for novice and experienced writers, the training of graduate and professional students, and the editorial policies of the leading HRD journals.

Synthesizing MILP Constraints for Efficient and Robust Optimization

While mixed integer linear programming (MILP) solvers are routinely used to solve a wide range of important science and engineering problems, it remains a challenging task for end users to write correct and efficient MILP constraints, especially for problems specified using the inherently non-linear Boolean logic operations. To overcome this challenge, we propose a syntax guided synthesis (SyGuS) method capable of generating high-quality MILP constraints from the specifications expressed using arbitrary combinations of Boolean logic operations. At the center of our method is an extensible domain specification language (DSL) whose expressiveness may be improved by adding new integer variables as decision variables, together with an iterative procedure for synthesizing linear constraints from non-linear Boolean logic operations using these integer variables. To make the synthesis method efficient, we also propose an over-approximation technique for soundly proving the correctness of the synthesized linear constraints, and an under-approximation technique for safely pruning away the incorrect constraints. We have implemented and evaluated the method on a wide range of benchmark specifications from statistics, machine learning, and data science applications. The experimental results show that the method is efficient in handling these benchmarks, and the quality of the synthesized MILP constraints is close to, or higher than, that of manually-written constraints in terms of both compactness and solving time.

PR controller-based droop control strategy for AC microgrid using Ant Lion Optimization technique

Microgrids are now an integral part of the modern power system to maintain the stability of the power distribution process. Ensuring the frequency and voltage stability in the autonomous mode is quite a challenging task indeed. These have now reached the extent of utilizing evolutionary intelligence techniques leading to the concept of intelligent microgrids. In this work, a novel droop control strategy is implemented with a proportional resonant controller, whose proportional gain is optimized by the Ant Lion Optimization algorithm (A.L.O). The efficacy of the A.L.O algorithm for its application in the primary level droop control for voltage stability is investigated in this work. The superiority of the A.L.O optimized PR controller over the conventional PI controller is compared in terms of error indices, timed domain specifications, speed of response, voltage regulation and T.H.D levels. It could ensure a higher speed of response, better voltage stability and higher power quality as against its PI counterpart. The performance of the proposed A.L.O optimized PR controller is validated by comparing it with the performance achieved by controllers tuned with two other algorithms namely, particle swarm optimization (P.S.O) and Satin bower bird optimization (S.B.O). The proposed controller could ensure better steady-state stability compared to the other two.

Design of a robust and practicable SSI damping controller using H[formula omitted] technique for series compensated DFIG-based wind farms

This paper designs a robust and practicable subsynchronous interaction (SSI) damping controller using H∞ technique for the safe operation of series capacitor compensated wind farms (WFs) with doubly-fed induction generator (DFIG) wind turbines (WTs). Mixed sensitivity control design together with pole placement are formulated into a set of linear matrix inequalities (LMIs) to obtain the controller parameters. The LMI technique allows to include both desirable frequency and time domain specifications. The proposed damping controller is integrated into the WT controller (WTC) and receives the DFIG converter currents as inputs. The implementation of the proposed controller does not require any communication links between the WTs and WF secondary control layer. The controller output signals are applied to the inner control loops of DFIG converters and are dynamically limited for the desired fault-ride-through (FRT) performance. The effectiveness of the damping controller is verified through detailed electromagnetic transient (EMT) simulations. In these simulations, the complete medium-voltage (MV) collector grid is modeled with all details, and it is assumed that the wind speed at the location of each turbine follows a Gaussian distribution. The collected results confirm the accuracy of the modeling of the entire WF as an aggregated WT with the average wind speed.

Empirical analysis of security-related code reviews in npm packages

Security issues are a major concern in software packages and their impact can be detrimental if exploited. Modern code review is a widely-used practice that project maintainers adopt to improve the quality of contributed code. Prior work has shown that code review has an important role in improving software quality, however, in-depth analyses on code review in relation to security issues are limited.Therefore, in this paper, we aim to explore the role of code review in finding and mitigating security issues. In particular, we investigate active and popular npm packages to understand what types of security issues are raised during code review, and what kind of mitigation strategies are employed by package maintainers to address them. With pull requests (PRs) being the medium of code review under study, we analyze 171 PRs with raised security issues. We find that such issues are discussed at length by package maintainers. Moreover, we find that code review is effective at identifying certain types of security concerns, e.g., Race Condition, Access Control, and ReDOS, as dealing with such issues requires in-depth knowledge of the project domain and implementation specifics. Interestingly, we also observe that some projects have automated tools integrated in the project development cycle, which enhances the identification of frequent cases of certain security issues. When analyzing how maintainers respond to the raised security issues, we find that most of the issues (55%) are frequently addressed and mitigated. In other cases, security concerns ended up not being fixed or are ignored by project maintainers. Leveraging our findings, we offer several implications for project maintainers to support the role of reviewing code in finding and fixing security concerns.

Evaluating the Domain Specificity of Self-Efficacy for Nurse Practitioner Leadership Development

The purposes of this study were to evaluate self-efficacy (SE) levels of doctor of nursing practice nurse practitioner students (N = 64) and the relationship of SE with specific demographic and behavioral control variables. SE was measured using the General Self-Efficacy Scale, and behavioral control was assessed via 5 Likert scale items. The average SE was 32.8 (maximum score = 40), and the mean behavioral control score was 28.4 (maximum = 35). SE was significantly correlated with overall behavioral control. The benefits of SE align with the values promoted by graduate education—increased self-confidence, increased expertise, and potential for future leadership advancement.

A Historical Text-Based Game Designed to Develop Critical Thinking Skills

Designing an intervention that can effectively develop critical thinking skills is challenging because of the problems of transfer and domain specificity. The authors describe the design and development of a text-based game that could teach players important critical thinking skills in the domain of history. This was achieved by combining Schon's reflective practitioner model with game-based learning principles. The work contributes to the existing literature because the combination of the models employed allowed the game design to address the problem of transfer, as well as developing critical thinking skills. The instrument used to evaluate the effectiveness of the game was a questionnaire based on the reflective practitioner model. The gathered qualitative data were analysed through affinity diagramming. The results show that the game that was developed has the potential to encourage advanced levels of historical thought, as well as critical thinking skills.

SA-MAIS: Hybrid automatic sentiment analyser for stock market

Sentiment analysis of stock-related tweets is a challenging task, not only due to the specificity of the domain but also because of the short nature of the texts. This work proposes SA-MAIS, a two-step lightweight methodology, specially adapted to perform sentiment analysis in domain-constrained short-text messages. To tackle the issue of domain specificity, based on word frequency, the most relevant words are automatically extracted from the new domain and then manually tagged to update an existing domain-specific sentiment lexicon. The sentiment classification is then performed by combining the updated domain-specific lexicon with VADER sentiment analysis, a well-known and widely used sentiment analysis tool. The proposed method is compared with other well-known and widely used sentiment analysis tools, including transformer-based models, such as BERTweet, Twitter-roBERTa and FinBERT, on a domain-specific corpus of stock market-related tweets comprising 1 million messages. The experimental results show that the proposed approach largely surpasses the performance of the other sentiment analysis tools, reaching an overall accuracy of 72.0%. The achieved results highlight the advantage of using a hybrid method that combines domain-specific lexicons with existing generalist tools for the inference of textual sentiment in domain-specific short-text messages.

The production and distribution of scientific knowledge: A global perspective

The educational enterprise is not omnipotent and is heavily constrained by natural, socioeconomic and pedagogical factors. The present research aims to study the state of the production and distribution of scientific and mathematics knowledge worldwide using the Programme for International Student Assessment (PISA) 2018 big data bank. The first finding is that the distribution of this knowledge shows that about two-third of the world's population belongs to quality groups one, two, and three, representing the low-achieving section of the proficiency scale. The second finding is that there is practically no sign of domain specificity. Thus, the learning problems do not reside in the curriculum but in some higher cognitive factors such as general intelligence or developmental stage. It is high time to adopt educational policies oriented toward the real world rather than an aspired one. Keywords: PISA 2018, scientific literacy, quality groups, proficiency distribution, educational efficiency, individual differences.

Identification and control of Maglev system using fractional and integer order PID controller

System identification techniques have proved to be the most effective methodologies for the modeling highly non-linear and system. For the purpose of real-time parameter estimation of a Maglev system, a Teaching Learning Based Optimization (TLBO) for updating the weights of Functional Link Artificial Neural Network (FLANN) model is proposed and implemented in this research. Moreover, we proposed a one & two-Degree of Freedom (one-DOF & two-DOF) Fractional Order PID (FOPID) controller, where the parameters are optimized by using the Teaching Learning Based Optimization (TLBO) and the recently proposed Black Widow Optimization (BWO) algorithm. To investigate the robustness of the proposed controller, a pulse signal disturbance is added at equal intervals of the output of the identified model of the Maglev system. It is found that the suggested two-DOF FOPID controller with TLBO performs better than its counterpart in terms of both in time domain specifications (i.e., maximum overshoot = 1.2648%, settling time = 1.3884 sec and rise time = 0.8685 sec) and in robustness analysis (i.e., system is sufficiently robust, because the infinity norms of the sensitivity and the complementary sensitivity functions of the system are less than two). The TLBO algorithm has performed better for both identification and optimization of controller parameter due to very less number of algorithmic parameter is as compared to other algorithm.

Surface oxidation of polyhydroxyalkanoate films with different molecular structure via photo-activated chlorine dioxide radical and comparison of the influence on the properties

Polyhydroxyalkanoates (PHAs) are novel candidates for biodegradable plastics, and hydrophobic surfaces have been modified to improve their dyeability and adhesion to other materials. In this study, surface oxidation by photoactivated chlorine dioxide radicals was carried out on four types of PHA films with different molecular structures to investigate whether the number of introduced functional groups changes. Whether the mechanical properties, crystallinity, enzymatic degradability, and biodegradability in seawater were changed by oxidation was also investigated. It was found that the number of functional groups decreased in the polymer having monomer units without side chains, indicating that the reactivity of the oxidation is affected by the presence of the side chain. No significant changes in mechanical properties and crystallinity were observed. The enzymatic degradability of some of the oxidized PHA films was significantly reduced because it did not match the substrate specificity of the catalytic domain of a PHA depolymerase due to changes in the molecular structure caused by oxidation. In a biodegradation test using seawater, the initial biodegradation rate of the oxidized films was slightly reduced, suggesting that the oxidation may affect the biodegradation of microorganisms in the environment.

A multidimensional approach for enhancing and measuring creative thinking and cognitive skills

PurposeDespite the fact that research on creativity and cognition have garnered the attention of researchers and practitioners for decades, there is a lack of valid, reliable, and accessible instruments for enhancing and measuring these critical skills. Leveraging research from The LEGO Foundation and in collaboration with BrainPOP and the Learning Economy Foundation, this paper introduces an assessment framework for holistic skills and reports evidence from the 2022 validation study.Design/methodology/approachThe complexities associated with both competencies such as multidimensionality, authenticity, and domain specificity pose a major issue for its measurement and credentialing. This paper provides evidence-based insights on promising ways to measure and provide actionable insights on holistic skills.FindingsPreliminary evidence supports the assessment framework for holistic skills.Research limitations/implicationsFuture directions for further development of the assessment are discussed.Practical implicationsThe framework should also be of help for practitioners looking for research-based guiding principles for the design of learning-through-play activities aimed to help develop holistic skills across a wide range of digital, physical, and hybrid modalities.Social implicationsThe framework provides new instruments and insights for evaluating the social and educational impact of learning-through-play programs and initiatives.Originality/valueThe learning progressions and formative assessment for holistic skills development are novel and clearly needed in research and practice of learning-through-play.

Abstract CT131: Initial preclinical and clinical experience of autologous engineered monocytes in T cell lymphoma patients

Abstract For many patients with T cell lymphomas (TCL), sustained clinical benefit with standard treatment options is elusive. Myeloid cells, such as monocytes, dendritic cells and macrophages, readily accumulate in tumors, whereby they support tumor progression. The ability to harness the capability of myeloid cells to penetrate into tumors, and to subsequently program them to activate and elicit broad anti-tumor immunity has the potential to transform cancer therapies. With this goal we developed the first engineered monocyte cell product, by manipulating autologous monocytes to express a novel chimeric antigen receptor (CAR). This CAR contains a tumor recognition domain fused to a CD8 hinge domain, Fcγ and PI3K intracellular signaling domains. In addition to imparting tumor specificity, the Fcγ and PI3K signaling domains promote phagocytosis, cytokine production and antigen presentation upon activation. In a rodent model of melanoma (gp75+ B16/F10-OVA), Ly6C+ monocytes engineered with this receptor were able to phagocytose tumor cells and cross present antigen in vitro. In vivo infusion of engineered monocytes was associated with significant suppression of tumor growth. FACS analysis of tumor-infiltrates demonstrated that engineered monocytes preferentially infiltrated tumors and differentiated into antigen presenting cells. Adoptive T cell transfer of CFSE-labeled OT-I CD8+ T cells confirmed that treatment was also associated with increased accumulation of tumor specific T cells in tumor and spleen. Based on these promising data, MT-101 is being assessed in humans in the Phase 1, open-label, first-in-human trial in patients with refractory or relapsed T cell lymphoma, IMAGINE trial (NCT05138458). The primary objective is the assessment of safety and tolerability at Day 28, following 3 weekly cycles of 2 infusions. Secondary objectives include assessment of correlative markers of response, pharmacokinetics, and efficacy. In the first 3 subjects, MT-101 has been well-tolerated, with no evidence of cytokine release syndrome (CRS), immune effector cell-associated neurotoxicity syndrome (ICANS), or infusion reactions. Examination of biomarkers by CyTOF in one subject shows changes in circulating leukocytes, including B cells. In this subject, survival has been greater than 10 months, while the median overall survival of patients with R/R PTCL is 5.5 months. Continued patient enrollment and data collection is ongoing to confirm these observations. Citation Format: Michele Gerber, Thomas Prod'homme, Yuxiao Wang, Kyong-Rim Kieffer-Kwon, Neha Diwanji, Josephine D'Alessandro, Xing Du, Edward Cochran, Michael Gorgievski, Zheng Ling, Nicholas King, Siddhartha Mukherjee, Daniel Getts. Initial preclinical and clinical experience of autologous engineered monocytes in T cell lymphoma patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr CT131.

Data Sensitivity and Domain Specificity in Reuse of Machine Learning Applications

Data sensitivity and domain specificity challenges arise in reuse of machine learning applications. We identify four types of machine learning applications based on different reuse strategies: generic, distinctive, selective, and exclusive. We conclude with lessons for developing and deploying machine learning applications.

Cross-walking personality disorder types to ICD-11 trait domains: An overview of current findings.

The ICD-11 has adopted a classification of Personality Disorders (PD) that abolishes the established categorical PD types in favor of global severity classification with specification of individual trait domains. To facilitate and guide this profound transition, an overview of current research on empirical associations between established PD types and ICD-11 trait domains seems warranted. We identified a total of 9 relevant studies from 2018 to 2022, which were based on both clinical and community samples from U.S., China, Brazil, Denmark, Spain, Korea, and Canada. The patterns of associations with ICD-11 trait domains were systematically synthesized and portrayed for each PD type. Findings overall showed expected and conceptually meaningful associations between categorical PD types and ICD-11 trait domains, with only few deviations. Based on these findings, we propose a cross-walk for translating categorical PD types into ICD-11 trait domains. More research is needed in order to further guide continuity and translation between ICD-10 and ICD-11 PD classification in mental healthcare, including facet-level ICD-11 trait information. Moreover, the nine reviewed studies only relied on self-reported ICD-11 trait domains, which should be expanded with clinician-rated trait domains in future research. Finally, future research should also take ICD-11's essential PD severity classification into account.

Bell correlations outside physics

Correlations are ubiquitous in nature and their principled study is of paramount importance in scientific development. The seminal contributions from John Bell offer a framework for analyzing the correlations between the components of quantum mechanical systems and have instigated an experimental tradition which has recently culminated with the Nobel Prize in Physics (2022). In physics, Bell’s framework allows the demonstration of the non-classical nature of quantum systems just from the analysis of the observed correlation patterns. Bell’s ideas need not be restricted to physics. Our contribution is to show an example of a Bell approach, based on the insight that correlations can be broken down into a part due to common, ostensibly significant causes, and a part due to noise. We employ data from finance (price changes of securities) as an example to demonstrate our approach, highlighting several general applications: first, we demonstrate a new measure of association, informed by the assumed causal relationship between variables. Second, our framework can lead to streamlined Bell-type tests of widely employed models of association, which are in principle applicable to any discipline. In the area of finance, such models of association are Factor Models and the bivariate Gaussian model. Overall, we show that Bell’s approach and the models we consider are applicable as general statistical techniques, without any domain specificity. We hope that our work will pave the way for extending our general understanding for how the structure of associations can be analyzed.

The Future of Research on Executive Function and Its Development: An Introduction to the Special Issue

ABSTRACT Over the last several decades, research on executive function in children has flourished, producing a wealth of empirical findings. These findings have raised many theoretical and methodological questions that warrant attention and are addressed in this special issue. This introduction to the special issue reviews some of the recent history of the field before introducing the seven target articles. We introduce these articles in the context of current theoretical and methodological issues: domain generality versus domain specificity of executive function, ecological and cultural validity of executive function measures, executive function training and transfer, and the nature of relations between executive function and achievement and other outcomes. This diverse set of articles collectively provides many fresh, testable ideas that promise to advance the field and usher in the next wave of theory-guided executive function research.