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Computer-based curriculum-based measurement (CBM) is a relatively common practice, but surprisingly few studies have examined the reliability of computer-based CBM. This study sought to examine the reliability of CBM administered via paper/pencil versus the computer. Twenty-one of 25 students in two third-grade classes (N = 21) participated in two generalizability studies. The primary facet of interest, format of assessment, was examined for two measures, a fact operation (fact family measure) and a more complex operation (multidigit addition). Researchers administered four alternate forms of each measure under both computer and paper/pencil conditions. Results indicated ideal reliability of measurement within all conditions and results were consistent across assessment formats for the fact operation. However, assessment format explained a large proportion of variance for the more complex skill (multidigit addition). Results indicate a need to consider the reliability of transitioning assessment from paper/pencil to computer-based response on a measure-by-measure basis. [ABSTRACT FROM AUTHOR]

This study aimed to analyze the 100 most-cited papers in the field of oral medicine and pathology over time, identifying the areas of more intense research. Papers in journals of oral medicine and pathology were identified using the Web of Science database. The specified research period was between 1900 and 2019. Descriptive statistics was used to analyze the data. Pearson's correlation analysis was used to explore the relationships among Web of Science citations, Dimensions citations, and Altmetric Attention Score. The number of citations of an article in the top 100 most-cited papers published in 1953 or later ranged from 541 to 3623. The papers were published in 47 different journals. The New England Journal of Medicine, American Cancer Society, and Nature Genetics published the most papers. Authors from 18 different countries published papers on head and neck cancer, craniofacial congenital anomalies, and osteonecrosis. Most of the papers were laboratory and descriptive studies. A correlation analysis showed a strong correlation only between Web of Science and Dimensions citations. In sum, although non-specific journals for pathology and oral medicine published the majority of the 100 most-cited papers, this biometric citation study show that head and neck cancer was the issue with the most citations. Together, these results make an important scientific contribution by providing a historical perspective on the research carried out. [ABSTRACT FROM AUTHOR]

Background: radiotherapy is one of the major treatments for lung cancer and has been a hot research area for years. This bibliometric analysis aims to present the research trends on lung cancer radiotherapy. Method: On August 31, 2022, the authors identified 9868 articles on lung cancer radiotherapy by the Web of Science (Science Citation Indexing Expanded database) and extracted their general information and the total number of citations. A bibliometric analysis was carried out to present the research landscape, demonstrate the research trends, and determine the most cited papers (top-papers) as well as top-journals on lung cancer radiotherapy. After that, the authors analyzed the recent research hotspots based on the latest publications in top-journals. Results: These 9868 papers were cited a total of 268,068 times. "Durvalumab after chemoradiotherapy in stage III non-small-cell lung cancer" published in 2017 by Antonia et al. was the most cited article (2110 citations). Among the journals, New England Journal of Medicine was most influential. Moreover, J. Clin. Oncol. and Int. J. Radiat. Oncol. Biol. Phys. was both influential and productive. Corresponding authors represented the USA (2610 articles) and China mainland (2060 articles) took part in most publications and articles with corresponding authors from Netherlands were most cited (46.12 citations per paper). Chemoradiotherapy was the hottest research area, and stereotactic body radiotherapy has become a research hotspot since 2006. Radiotherapy plus immunotherapy has been highly focused since 2019. Conclusions: This bibliometric analysis comprehensively and quantitatively presents the research trends and hotspots based on 9868 relevant articles, and further suggests future research directions. The researchers can benefit in selecting journals and in finding potential collaborators. This study can help researchers gain a comprehensive picture of the research landscape, historical development, and recent hotspots in lung cancer radiotherapy and can provide inspiration for future research. [ABSTRACT FROM AUTHOR]

This paper presents a current literature review (from the years 2017–2022) on issues related to the application of power system stabilizers (PSSs) for damping electromechanical swings in power systems (PSs). After the initial selection of papers found in the databases used, over 600 publications were qualified for this review, of which 216 were subjected to detailed analysis. In the review, issues related to the following problems are described: applications of classic PSSs, applications of new stabilizer structures based on new algorithms (including artificial intelligence), development of new methods for tuning PSSs, and operation of PSSs in PSs with high power generation by renewable sources. Describing individual papers, the research methods used by the authors (simulations, measurement methods, and a combination of both) are specified, attention is paid to the waveforms presented in the papers, and reference is made to the types of PSs in which PSSs (large multimachine, reflecting real systems, smaller standard multimachine New-England type, and simplest single-machine) operate. The tables contain detailed comments on the selected papers. The final part of the review presents general comments on the analyzed papers and guidelines for future PS stability studies. [ABSTRACT FROM AUTHOR]

Accurate short-term load forecasting (STLF) plays an essential role in sustainable energy development. Specifically, energy companies can efficiently plan and manage their generation capacity, lessening resource wastage and promoting the overall efficiency of power resource utilization. However, existing models cannot accurately capture the nonlinear features of electricity data, leading to a decline in the forecasting performance. To relieve this issue, this paper designs an innovative load forecasting method, named Prophet–CEEMDAN–ARBiLSTM, which consists of Prophet, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), and the residual Bidirectional Long Short-Term Memory (BiLSTM) network. Specifically, this paper firstly employs the Prophet method to learn cyclic and trend features from input data, aiming to discern the influence of these features on the short-term electricity load. Then, the paper adopts CEEMDAN to decompose the residual series and yield components with distinct modalities. In the end, this paper designs the advanced residual BiLSTM (ARBiLSTM) block as the input of the above extracted features to obtain the forecasting results. By conducting multiple experiments on the New England public dataset, it demonstrates that the Prophet–CEEMDAN–ARBiLSTM method can achieve better performance compared with the existing Prophet-based ones. [ABSTRACT FROM AUTHOR]

Objective: To identify key papers in urology using a novel bibliometric index called the disruption score.Methods: A PubMed search was conducted to identify papers published in Journal of Urology, European Urology, Urology, Urologic Oncology, Journal of Endourology, and BJU International, Nature Reviews Urology. Selected urology papers published in other medical journals were also included. Using a validated dataset of disruption scores for all papers published in 1954-2014, the top 100 most-disruptive urology papers, as well as the top 100 most-cited papers, were identified. Comparisons between both lists and across journals were investigated.Results: A total of 72,623 published articles were included. Journal of Urology had the most articles in the most-disruptive papers list (n = 69) followed by BJU International (n = 16). New England Journal of Medicine had the most papers in the most-cited papers list (n = 26) followed by Journal of Urology (n = 23). Only 7 papers were common to both the most-disruptive papers and most-cited papers lists. Oncology was highly represented among the most-cited papers (n = 60), whereas the most-disruptive papers included a broader representation of urology. The most common study design among the most disruptive papers was small case-series/case reports, whereas the most common study design among the most-cited papers was randomized controlled trials.Conclusion: The disruption score identified landmark papers in urology that have introduced innovative ideas. Disruption score captures a unique profile of scientific impact that may be used in combination with other bibliometric indices to identify scholarly achievements in urology. [ABSTRACT FROM AUTHOR]

Introduction: A large body of literature has been published on urinary incontinence, ranging from medical treatment, epidemiology and surgical techniques. A bibliometric analysis is used to identify high-quality research papers using criteria such as citation rate and journal impact factor. Objectives: To describe key themes and topics in urinary incontinence literature in the last 50 years. Methods: Thomson Reuters Web of Science citation indexing database was used to identify the top 100 cited articles in urinary incontinence in the last 50 years. Data sets were subdivided into manuscript type, theme, author, institution, country of origin, journal and citation rate. Results: Mean number of citations in the top 100 group for manuscripts was 676, ranging between 2444 and 306. Most cited paper was by Irwin et al. The manuscript with the highest citation rate was by Dumoulin et al., citation rate of 470.7/year. The largest number of manuscripts was published between 2000 and 2009 (n = 47). The New England Journal of Medicine (NEJM) had the highest impact factor (74.67) and five manuscripts were published in this journal. Fifty-seven per cent of articles were published in journals with impact factor < 5. The vast majority of the articles focussed on epidemiology, followed by surgical treatment of urinary incontinence, 69% being original research studies. Conclusion: This is the first bibliometric analysis of the top 100 most influential papers in urinary incontinence. The key themes identified were epidemiology and surgical management, with most papers being original research studies. [ABSTRACT FROM AUTHOR]

Introduction: To gain a better understanding of the progression of coronary artery bypass grafting (CABG) and its impact on clinical practice, bibliometric citation analysis can be performed. Bibliometric citation analysis is a method of determining the most influential papers on a topic based on several citations and impact factor.Method: A search of the Thomson Reuters Web of Science citation indexing database and research platform was completed using the terms "CABG," "Coronary artery bypass graft," "Coronary artery," "bypass," and/or "bypass grafting." The returned dataset was sorted by the number of citations.Results: The search yielded a total of 11 560 papers which were ranked in order of citations. New England Journal of Medicine published the most papers in the top 100 and generated the most significant number of citations with 20 papers in total followed by Journal of the American College of Cardiology. It also has the highest impact factor and 5-year impact fact in 2007 of 79.26 and 67.513, respectively.Conclusion: The most cited manuscripts by Serruys et al described a randomised trial comparing percutaneous coronary intervention and CABG for treating severe coronary artery disease. This work provides the most influential references related to CABG and serves as a guide as to the area of focus in CABG. [ABSTRACT FROM AUTHOR]

Retractions of coronavirus disease 2019 (COVID‐19) papers in high impact journals, such as The Lancet and the New England Journal of Medicine, have been panned as major scientific fraud in public media. The initial reaction to this news was to seek out scapegoats and blame individual authors, peer‐reviewers, editors, and journals for wrong doing. This paper suggests that scapegoating a few individuals for faulty science is a myopic approach to the more profound problem with peer‐review. Peer‐review in its current limited form cannot be expected to adequately address the scope and complexity of large interdisciplinary science research collaboration, which is central in translational research. In addition, empirical studies on the effectiveness of traditional peer‐review reveal its very real potential for bias and groupthink; as such, expectations regarding the capacity and effectiveness of the current peer review process are unrealistic. This paper proposes a new vision of peer‐review in translational science that, on the one hand, would allow for early release of a manuscript to ensure expediency, whereas also creating a forum or a collective of various experts to actively comment, scrutinize, and even build on the research under review. The aim would be to not only generate open discussion and oversight respecting the quality and limitations of the research, but also to assess the extent and the means for that knowledge to translate into social benefit. [ABSTRACT FROM AUTHOR]

The social economy is growing rapidly, and the power grid load demand is increasing. To maintain the stability of the power grid, it is crucial to achieve accurate and rapid power system stability assessment. In the actual operation of the power network, data loss is an unavoidable situation. However, most of the data‐driven models currently used assume that the input data is complete, which has obvious limitations in real‐world applications. This paper suggests an IVS‐GAN model to assess power system stability using incomplete phasor measurement unit measurement data with random loss. The proposed method combines the super‐resolution perception technology based on generative adversarial network (GAN) with a time‐series signal classification model. The generator adopts a 1D U‐Net network and uses convolutional layers to complete and recover missing data. The discriminator adopts a new gated recurrent unit–attention architecture proposed here to better extract voltage temporal variation features on key buses. The result of this paper is that the stability evaluation method outperforms other algorithms in high voltage data loss rates on the New England 10‐machine 39‐bus system. [ABSTRACT FROM AUTHOR]

This paper reflects on the process of designing and implementing an update to the Introduction to Information Technology course at Bentley University, a business university in New England. Driven by a university-wide curriculum reform initiative and following best practices from digital literacy frameworks and IS model curricula, the new CS 100 course, entitled Solving Business Problems with Information Technology, shifted emphasis from a personal computing context to exploring small business applications of technology. Students networked with university alumni at “Topics in Tech” presentations, where they learned about career options as information technology professionals. The authors describe the pilot courses that led to proposing a new CS 100 course and reflect its challenges and successes. Challenges included meeting the university’s goal of transfer friendliness, scaling from a few pilots to multiple sections, consistency of course delivery, and evaluating assessment. Successes include placing course topics in a business context, introducing current technologies, and providing opportunities for students to learn about career opportunities and experiences from university alumni. The paper also describes how CS 100 aligns with the university’s student learning goals for the new curriculum. These include developing future-focused skills, encouraging curiosity and critical analysis, communicating and collaborating in different settings, and demonstrating understanding of issues related to ethical use of technology. [ABSTRACT FROM AUTHOR]

Objectives: A bibliometric and knowledge-map analysis is used to explore hotspots' evolution and development trends in the CAR-T cell field. By looking for research hotspots and new topics, we can provide new clues and ideas for researchers in this field. Methods: The articles and reviews regarding CAR-T cells were retrieved and obtained from the Web of Science Core Collection (WOSCC) on October 28th, 2021. CtieSpace [version 5.8.R3 (64-bit)] and VOSviewer (version 1.6.17) were used to conduct the bibliometric and knowledge-map analysis. Results: 660 authors from 488 institutions in 104 countries/regions published 6,867 papers in 1,212 academic journals. The United States was absolutely in the leading position in this research field. The institution that contributed the most publications was the University of Pennsylvania. Carl H June published the most articles, while Shannon L Maude had the most co-citations. However, there was little cooperation between countries. After 2012, cooperation among various institutions was also small. The journals that published the most CAR-T cell-related papers were Frontiers in immunology and Cancers. Nevertheless, Blood and The New England Journal of Medicine were the most commonly co-cited journals. The most influential research hotspots were the research of CAR-T cells in hematological malignancies, the related research of cytokine release syndrome (CRS), CD19, and the anti-tumor activity and efficacy of CAR-T cells. The latest hotspots and topics included the study of CAR-T cells in solid tumors, universal CAR-T cells, CAR-NK cells, CD22, and anakinra (the IL-1 receptor antagonist). The research of CAR-T cells in solid tumors was a rapidly developing hot field. Emerging topics in this field mainly included the study of CAR-T cells in glioblastoma (related targets: IL13Rα2, EGFRvIII, and HER2), neuroblastoma (related target: GD2), sarcoma (related target: HER2), and pancreatic cancer (related target: mesothelin), especially glioblastoma. Conclusion: As an anti-tumor therapy with great potential and clinical application prospects, CAR-T cell therapy is still in a stage of rapid development. The related field of CAR-T cells will remain a research hotspot in the future. [ABSTRACT FROM AUTHOR]

Background: The extent of past Indigenous cultural burning in the eastern US remains contested. Historical documents (e.g. early histories, journals, and reports) contain descriptions of burning. Scholars have summarised descriptions, but few have compiled them into databases. Aims: This paper presents efforts to compile descriptions of past Indigenous burning in the eastern US and early results from mapped descriptions. Methods: Utilising previously cited descriptions and those discovered from digitised historical texts, the current dataset mapped >250 descriptions of burning in the northeastern US. Most were historical summaries from 19th century authors, and fewer were firsthand observations. Descriptions are currently shared as a GIS data layer, a tabular file, and an interactive web map. Key results: Descriptions correspond with fire-adapted vegetation, and clusters of descriptions suggest burning over large extents (e.g. southern New England, western New York). Estimated dates of burning or initial Euro-American settlement show an east–west succession in Indigenous fire exclusion and replacement with early Euro-American burning. Conclusions: Historical descriptions suggest regional-extent influence of Indigenous burning upon past forested ecosystems, but the veracity of descriptions should be carefully evaluated. Implications: This study provides a dataset for further examination of Indigenous burning and comparison with other methodologies for historical cultural fire reconstruction. This study creates a dataset of historical descriptions of Indigenous wildland burning from digitised historical texts in the eastern US. The current version of the dataset contains >250 descriptions in the northeastern US, mainly from 19th century historians. Descriptions correspond with geographic patterns in past fire-adapted vegetation. [ABSTRACT FROM AUTHOR]

This paper considers the Market Basket upheaval of 2013–2014 from the perspective of patriarchy, breach, workplace dignity, and social drama. It draws on Lingo and Elmes original data and analytic approach to their study of food workers in a family-owned, New England, supermarket chain who, after an unexpected change to the board, rose up to restore their patriarch and paternalistic institutional practices. It reimagines the Market Basket case through the lens of Victor Turner's social drama with a focus on key phases of the upheaval which included breach, crisis, redress, and reintegration. The paper considers the power of paternalism to unify and activate loyal, working class followers who benefit greatly from paternalistic practices and feel threatened by their removal. It also considers the risks of paternalism particularly under conditions where a charismatic patriarch has less benign intentions and workers follow with unquestioned loyalty. [ABSTRACT FROM AUTHOR]

This paper examines the use of manifold learning in the context of electric power system transient stability analysis. Since wide-area monitoring systems (WAMSs) introduced a big data paradigm into the power system operation, manifold learning can be seen as a means of condensing these high-dimensional data into an appropriate low-dimensional representation (i.e., embedding) which preserves as much information as possible. In this paper, we consider several embedding methods (principal component analysis (PCA) and its variants, singular value decomposition, isomap and spectral embedding, locally linear embedding (LLE) and its variants, multidimensional scaling (MDS), and others) and apply them to the dataset derived from the IEEE New England 39-bus power system transient simulations. We found that PCA with a radial basis function kernel is well suited to this type of power system data (where features are instances of three-phase phasor values). We also found that the LLE (including its variants) did not produce a good embedding with this particular kind of data. Furthermore, we found that a support vector machine, trained on top of the embedding produced by several different methods was able to detect power system disturbances from WAMS data. [ABSTRACT FROM AUTHOR]

Climatic changes in the northeastern US are expected to cause coniferous stands to transition to deciduous stands over the next hundred years. Mercury (Hg) sequestration in forest soils may change as a result. In order to understand potential effects of 5 this transition, we studied aboveground vegetation and soils at paired coniferous and deciduous stands on eight mountains in Vermont and New Hampshire, US. Organic horizons at coniferous stands accumulated more Total Hg (THg) (42±6 gha-1) than deciduous stands (30±4 gha-1). Total Hg pools in the mineral horizons were similar for coniferous (46±8 gha-1) and deciduous stands (45±7 gha-1). Soil properties (C, 10 %clay, and pH) explained 56% of the variation in mineral soil Hg concentration when multiple regressed. Foliar and bole wood Hg concentrations were generally greater for coniferous species than deciduous species. We estimated Hg mean residence time (MRT) in the organic and mineral horizons at coniferous and deciduous stands using a simple two-box model. Organic horizon MRT were longer at coniferous stands 15 (183±44 yr) than deciduous stands (65±15 yr). Mineral soil horizon MRT values were also longer for coniferous stands (386±57 yr) than for deciduous stands (188±27 yr). We concluded that organic horizon Hg accumulation is influenced by vegetation type but mineral horizons are primarily affected by soil properties. Further investigations into the effect of vegetation type on volatilization, atmospheric deposition, and leaching 20 rates are needed to constrain regional Hg cycling rates. [ABSTRACT FROM AUTHOR]

Transient stability of a power system can be significantly affected by wind power generators due to their stochastic power output and complex dynamic characteristics. This paper proposes a robust optimization approach for coordinating generation dispatch and emergency load shedding against transient instability under uncertain wind power output. The problem is modelled as a two-stage robust optimization (TSRO) model considering transient stability constraints, where the first-stage is to optimize the generation dispatch (preventive control) before a contingency and the second-stage decision is the emergency load shedding (emergency control) after the contingency occurrence under the worst case of wind power variation. To solve this TSRO problem, this paper also proposes a solution algorithm which integrates transient stability assessment and transient stability constraint construction in a column and constraint generation framework. The proposed method is validated on the New-England 39-bus system and the Nordic32 system, which shows high computational efficiency and stability robustness against uncertain wind power. [ABSTRACT FROM AUTHOR]

Much has been written on the skills and capabilities of a new generation raised with social media, smartphones, and immediate access to data and information via the Internet. Today's college students grew up using the Internet, where they both generate and consume data. But do incoming college students have the skills necessary to thrive in a digital world that requires the ability to generate, analyze, and share insights from data? This paper presents a study, performed at two small New England institutions each with a business focus, which examines the digital skill sets of first-year college students in relation to the skills they have developed before entering college. The authors also consider whether there is a "digital divide" among first-year college students in relation to their previous technology skills. When applying the Databilities framework for evaluating data literacy competencies, results show that teaching data literacy skills to first-year college students will be critical to their academic success as future information technology workers. [ABSTRACT FROM AUTHOR]

Maintaining stability in modern power systems is challenging due to complex structures, rising power demand, and load disturbances. The integration of renewable energy sources further threatens stability by causing imbalances between generation and demand. Conventional load frequency stabilization methods fall short in such scenarios. This paper proposes an optimal fractional‐order proportional‐integral‐derivative‐acceleration (FOPIDA) controller, enhanced by a robust adaptive neuro‐fuzzy inference system (ANFIS), to improve load frequency control and reliability in power systems with wind and solar generators. First, the dynamical model of a multi‐area interconnected power system, including a thermal power plant, wind turbine, and solar photovoltaic generators, is developed. A decentralized ANFIS‐FOPIDA controller is then designed for load frequency control objectives. The gains of this controller are optimized using the whale optimization algorithm (WOA), focusing on frequency deviation and tie‐line power exchange. Simulations on a New England IEEE 10‐generator 39‐bus power system demonstrate the approach's effectiveness under various disturbances, including random load‐generation disturbances and nonlinear generation behaviors. Comparisons with other strategies, such as fractional order (FO) beetle swarm optimization algorithm (FOBSOA)‐FOPIDA, WOA‐PIDA, and WOA‐ANFIS‐PIDA, and recent control approaches highlight the superior performance of the WOA‐ANFIS‐FOPIDA method in enhancing power system stability. [ABSTRACT FROM AUTHOR]

To address uncertainty as well as transient stability constraints simultaneously in the preventive control of wind farm systems, a novel three-stage optimization strategy is established in this paper. In the first stage, the probabilistic multi-objective particle swarm optimization based on the point estimate method is employed to cope with the stochastic factors. The transient security region of the system is accurately ensured by the interior point method in the second stage. Finally, the verification of the final optimal objectives and satisfied constraints are enforced in the last stage. Furthermore, the proposed strategy is a general framework that can combine other optimization algorithms. The proposed methodology is tested on the modified WSCC 9-bus system and the New England 39-bus system. The results verify the feasibility of the method. [ABSTRACT FROM AUTHOR]

The optimal PMU placement problem is placing the minimum number of PMUs in the network to ensure complete network observability. It is an NP-complete optimization problem. PMU placement based on cost and critical nodes is solved separately in the literature. This paper proposes a novel approach, a degree of centrality in the objective function, to combine the effect of both strategies to place PMUs in the power network optimally. The contingency analysis and the effect of zero-injection buses are solved to ensure the reliability of network monitoring and attain a minimum number of PMUs. Integer linear programming is used on the IEEE 7-bus, IEEE 14-bus, IEEE 30-bus, New England 39-bus, IEEE 57-bus, and IEEE 118-bus systems to solve this problem. The results are evaluated based on two performance measures: the bus observability index (BOI) and the sum of redundancy index (SORI). On comparison, it is found that the proposed methodology has significantly improved results, i.e., a reduced number of PMUs and increased network overall observability (SORI). This methodology is more practical for implementation as it focuses on critical nodes. Along with improvement in the results, the limitations of existing indices are also discussed for future work. [ABSTRACT FROM AUTHOR]

Transient stability improvement of power systems in the event of short-circuit faults has always been an important issue in power systems analysis and studies. Resistive-type superconducting fault current limiters (RSFCL), owing to their capability in restricting fault currents, have been often taken into account as an efficient method to improve the transient stability of a power system. Regarding technical constraints as well as economic concerns, optimal allocation and sizing of RSFCLs in a power system play a crucial role in their efficient utilization. This paper aims to continue the authors' previous work and enhance the transient stability of power systems by proposing an optimization approach for optimal sizing and the allocation of various candidate numbers of RSFCLs, as the most employed type of SFCL and the most efficient one in transient stability improvement. To solve the optimization problem, a PSO-based algorithm is solved in MATLAB through an objective function and related constraints. The efficacy of the proposed algorithm is evaluated by numerical studies on the IEEE 39-Bus New England system in various scenarios through the assessment of critical fault clearing time (CCT) as well as the generators rotor angle deviations as two crucial criteria for the transient stability of power systems. Simulating the optimization results in DIgSILENT Power Factory indicates an evident enhancement of the power system transient stability via employing optimized RSFCLs resulted from the proposed optimization algorithm. Moreover, the level of transient stability enhancement highly depends on the number of optimized RSFCLs employed in the power system. The results of this paper present a helpful guideline for power system planners to select an appropriate stability scheme based on RSFCLs besides other related technical and economic issues. [ABSTRACT FROM AUTHOR]

In recent years, the power system transient stability assessment (TSA) based on a data-driven method has been widely studied. However, the topology and modes of operation of power systems may change frequently due to the complex time-varying characteristics of power systems. which makes it difficult for prediction models trained on stationary distributed data to meet the requirements of online applications. When a new working situation scenario causes the prediction model accuracy not to meet the requirements, the model needs to be updated in real-time. With limited storage space, model capacity, and infinite new scenarios to be updated for learning, the model updates must be sustainable and scalable. Therefore, to address this problem, this paper introduces the continual learning Sliced Cramér Preservation (SCP) algorithm to perform update operations on the model. A deep residual shrinkage network (DRSN) is selected as a classifier to construct the TSA model of SCP-DRSN at the same time. With the SCP, the model can be extended and updated just by using the new scenarios data. The updated prediction model not only complements the prediction capability for new scenarios but also retains the prediction ability under old scenarios, which can avoid frequent updates of the model. The test results on a modified New England 10-machine 39-bus system and an IEEE 118-bus system show that the proposed method in this paper can effectively update and extend the prediction model under the condition of using only new scenarios data. The coverage of the updated model for new scenarios is improving. [ABSTRACT FROM AUTHOR]

This paper presents a fault detection and identification system for power systems using an artificial neural network approach while discussing its advantages and disadvantages. The initial data for the proposed technique are a set of simulated post-fault bus voltages and currents obtained at a sampling rate which emulates a complete phasor measurement unit (PMU)-based wide area measurement system (WAMS). Several types of faults are considered, such as short circuits and line and load contingencies. All fault and steady-state simulations have been performed on MATLAB using the Power System Toolbox. The artificial neural network was designed using an architecture proper for pattern recognition with supervised learning. As a result, satisfactory predictions within short time periods are obtained. The test system used in all simulations is the IEEE 39-Bus New England Power System, which has 10 generation units, 21 loads, and three distinct areas alongside transient and sub transient models, with PMUs distributed over up to 14 buses. Future works are also discussed in this paper, showing the possibilities for feature engineering in this type of problem, as well as the application of other machine learning and data analytics techniques for PMU-based WAMS databases. [ABSTRACT FROM AUTHOR]

This paper offers non‐linear control for enhancing the transient stability in power systems containing a photovoltaic (PV) and doubly fed induction generator (DFIG) by transient energy function (TEF) method and finite‐time observers. At first, the TEF method is utilized to enhance the transient stability in a power system containing a PV, DFIG, and synchronous generator (SG) by constructing a hybrid Lyapunov function. Then, the derivative terms in control are estimated with finite‐time observers. The main contribution of the research is the application of the TEF technique in the transient stability evaluation of a power system consisting of PV, SG, and DFIG. Another innovation of the research is the simultaneous control of DFIG and PV, whose uncertain parameters are estimated with the use of finite‐time observer. The proposed non‐linear control scheme is robust against changes in the configuration of the power system. In order to show the capability of this control scheme, time domain simulations are performed on the IEEE 9‐bus, and the NEW ENGLAND Standard 39‐Bus power system. Using the obtained result, some comparisons are made with the back‐stepping control scheme to clarify the superiority of the proposed method. The comparisons show that the proposed non‐linear control scheme can properly provide extra damping to reduce the first‐swing fluctuations in less time. The manuscript contains the new original results of the authors' research. In this article, to maintain and improve the transient stability, a new controller with simultaneous management of photovoltaic (PV) and doubly fed induction generator (DFIG) has been developed. The contributions of the paper are as follows. (1) The transient energy function (TEF) is obtained for the power system containing synchronous generator (SG) and DFIG. (2) The control laws are acquired with four PV and DFIG control variables. (3) The derivative parameters of the PV and DFIG controls by a finite‐time observer are estimated. [ABSTRACT FROM AUTHOR]

The goal of contingency ranking is to provide a list of possible critical situations and rank them according to the severity of their impact on a power network. The methods of contingency ranking may be divided into two major categories: static and dynamic techniques. Static approaches are fast and can be implemented in real‐time, but they present different results depending on the parameter which has been selected for contingency ranking. Dynamic methodologies are more accurate than static ones, but they are time‐consuming. This paper presents a novel combined static and dynamic method for contingency ranking which takes advantage of both techniques and shows the performance evaluation for the hybrid method using accuracy and efficiency as criteria. The proposed method uses three well‐known static indices and the Lyapunov spectrum based dynamic approach to select the worst critical lines. IEEE 39‐bus (New England grid) and IEEE 118‐bus networks are utilized to verify the proposed method. The method provides speed and accuracy. One of the prominent features of the proposed approach is its ability to rank contingencies that lead to network load flow divergence. [ABSTRACT FROM AUTHOR]

Transient stability of the electric power system still heavily rests on a timely and correct operation of the relay protection of individual power generators. Power swings and generator pole slips, following network short-circuit events, can initiate false relay activations, with negative repercussions for the overall system stability. This paper will examine the generator's underimpedance (21G) and out-of-step (78) protection functions and will propose a machine learning based classifier for supporting and reinforcing their decision-making logic. The classifier, based on a support vector machine, will aid in blocking the underimpedance protection during stable generator swings. It will also enable faster tripping of the out-of-step protection for unstable generator swings. Both protection functions will feature polygonal protection characteristics. Their implementation will be based on European practice and IEC standards. Classifier will be trained and tested on the data derived from simulations of the IEEE New England 10-generator benchmark power system. [ABSTRACT FROM AUTHOR]

In this paper we propose a novel distributed continuous-time algorithm aimed to solve optimization problems with cost function being a sum of local strictly convex multidimensional functions associated to individual agents. Additionally, the problems can have coupled equality and inequality constraints. We prove global asymptotic convergence of the algorithm for a connected graph topology. In order to investigate its practical implementation, we analyze convergence when Euler method is applied to represent discrete-time communication. Finally, we support our results with numerical experiments of the developed approach application for power balancing in New England power system. [ABSTRACT FROM AUTHOR]

The increasing interactivity between energy carrier networks such as electrical, natural gas (NG), and heating can be appropriately used for improving the operation optimality along with overcoming some challenges of those systems. With such a view, this paper studies the practical issue of power transmission lines congestion management in integrated multicarrier energy systems (MCESs) and makes a comparison with the only electrical operation mode. The MCES consisting of electrical and NG network infrastructures with exchanged energy between them is modelled by considering the several local energy hubs and their electrical and heat loads. Rescheduling of energy sources (power plants and gas wells) and demand side management in both electrical and NG networks have been utilized as the two important tools in the developed congestion alleviation framework. The proposed method confirms that the provided flexibility in the integrated operation of the MCESs can lead to a remarkable reduction in the congestion management cost index. Implementing the proposed congestion management framework on an assumed test MCES with a combined 39‐bus New England power system and 20‐node Belgium NG system demonstrates its effectiveness and applicability for the system operators. The issue of power transmission lines congestion management in integrated multi‐carrier energy systems (MCESs) has been studied. The proposed method confirms that the provided flexibility in the integrated operation of the MCESs can lead to reduction in the congestion management cost. [ABSTRACT FROM AUTHOR]

Addressing the issue of reduced system inertia and significantly increased risk of system frequency deviation due to high penetration of renewable energy sources, this paper proposes a power system disturbance frequency trajectory prediction method based on light gradient boosting machine (LightGBM) Spearman to provide data support for advanced system stability judgment and the initiation of stability control measures. Firstly, the optimal cluster is determined by combining the K-means clustering algorithm with the elbow method to eliminate redundant electrical quantities. Subsequently, the Spearman coefficient is used to analyze feature correlation and filter out electrical quantities that are strongly correlated with frequency stability. Finally, a frequency trajectory prediction model is built based on LightGBM to achieve accurate prediction of disturbed frequency trajectories. The method is validated using a case study on the New England 10-machine 39-bus system constructed on the CloudPSS 4.0 full electromagnetic cloud simulation platform, and the results show that the proposed method has high accuracy in frequency trajectory prediction. [ABSTRACT FROM AUTHOR]

Holistic nursing practice requires an understanding of the constraints of poverty as one of the social determinants of health. Future nurses need to be change agents for social justice. A descriptive, qualitative study was conducted to explore students' experience of the Missouri Association for Community Action Poverty Simulation© (CAPS) and its impact on empathy and social justice awareness among a purposive sample of 56 sophomore baccalaureate nursing students at a public university in the Northeastern United States. Inductive thematic analysis was applied to data collected from a postparticipation reflection paper. Five themes emerged: (a) emotions, (b) personal history of poverty, (c) empathy, (d) rising advocacy, and (e) lessons learned. The results support that the CAPS simulation provides an experiential opportunity which impacts empathy and foundational attitudes to be a change agent for social justice. Recommendations include structured education about social determinants of health prior to the CAPS simulation, continued education throughout nursing curricula, and experiential opportunities to apply social justice skills before graduation. [ABSTRACT FROM AUTHOR]

Increasing the replacement of conventional synchronous machines by non-synchronous renewable machines reduces the conventional synchronous generator (SG) inertia in the modern network. Synthetic inertia (SI) control topologies to provide frequency support are becoming a new frequency control tactic in new networks. However, the participation of SI in the market of RES-rich networks to provide instant frequency support when required proposes an increase in the overall marginal operation cost of contemporary networks. Consequently, depreciation of operation costs by optimizing the required SI in the network is inevitable. Therefore, this paper proposes a flexible SI optimization method. The algorithm developed in the proposed method minimizes the operation cost of the network by giving flexible SI at a given SG inertia and different sizes of contingency events. The proposed method uses Box's evolutionary optimizer with a self-tuning capability of the SI control parameters. The proposed method is validated using the modified New England 39-bus network. The results show that provided SIs support the available SG inertia to reduce the RoCoF values and maintain them within acceptable limits to increase the network's resilience. [ABSTRACT FROM AUTHOR]

Underfrequency load shedding is a common technique for maintaining the stability of the power system by removing the overload in a certain part of the system after a disturbance. The purpose of underfrequency load shedding is to balance output and load when a particular event causes a significant frequency drop in the power system. In conventional underfrequency load shedding schemes, the frequency thresholds of frequency relays are constant, this way it is difficult and sometimes impossible to control the frequency in various disturbances in the system. In this paper, an adaptive underfrequency load shedding (AUFLS) algorithm that is independent of communication between relays is presented. The relays are tuned to reduce loads taking into account local parameters such as voltage and frequency to prevent the occurrence of a cascade failure that can ultimately lead to the breakdown of the entire power system. In this paper, the rate of change of frequency (ROCOF) is obtained by applying the Hilbert-Huang transformation. Numerical simulations conducted on the New England 39 bus test system in the DIgSILENT PowerFactory and MATLAB software packages confirm the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Severe disturbances in a power network can cause the system frequency to exceed the safe operating range. As the last defensive line for system emergency control, under frequency load shedding (UFLS) is an important method for preventing a wide range of frequency excursions. This paper proposes a hierarchical UFLS scheme of "centralized real-time decision-making and decentralized real-time control" for inter-connected systems. The centralized decision-layer of the scheme takes into account the importance of the load based on the equivalent transformation of kinetic energy (KE) and potential energy (PE) in the transient energy function (TEF), while the load PE is used to determine the load shedding amount (LSA) allocation in different loads after faults in real-time. At the same time, the influence of inertia loss is considered in the calculation of unbalanced power, and the decentralized control center is used to implement the one-stage UFLS process to compensate for the unbalanced power. Simulations are carried out on the modified New England 10-generator 39-bus system and 197-bus system in China to verify the performance of the proposed scheme. The results show that, compared with other LSA allocation indicators, the proposed allocation indicators can achieve better fnadir and td. At the same time, compared with other multi-stage UFLS schemes, the proposed scheme can obtain the maximum fnadir with a smaller LSA in scenarios with high renewable energy sources (RES) penetration. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to describe the design and pilot program of a parent designed clothing option for hospitalized infants and children and to better understand the importance and effects of hospital clothing on families. Little research has been done on how clothing a hospitalized child impacts the child's quality of life and their parent's perception of care. Research has been limited to clothing in adults and its relation to infection. Design and Methods: A pediatric outfit (the Georgie) for hospitalized infants and children was designed based on insight from bedside nursing, physicians, parents, and supply chain personnel. The garment was pilot tested on select patients from intensive care units of a large children's hospital. A pre‐ and post‐use questionnaire was disseminated with questions focused on aspects of the child's care, comfort in changing child's clothes/diapers, number of times the Georgie was used and comfort level of using the Georgie. Survey responses were summarized using descriptive statistics. Results: Parents overall response to the Georgie was positive with great value placed on having their child dressed. All parents (n = 5) responded that too many lines were an obstacle to having their child dressed. Compared to the hospital Johnny, the Georgie (80%, n = 4) was the most preferred when placement and securement of monitoring lines was taken into consideration with one parent preferring a blanket and diaper only. Nurses felt the benefit outweighed the added effort in dressing the patient. The majority of the nurses had a positive initial reaction to the Georgie (80%, n = 4) and felt the lines or external devices were "very secure/secure" (80%, n = 4) when the patient was wearing the Georgie. Practice Implications: Implementing a new family centered care initiative of dressing critically ill patients in the Georgie may improve patient and family's quality of life while hospitalized. A larger scale study is indicated to assess the importance of dressing hospitalized pediatric patients for their families, to clarify the effect on nursing care, to optimize ability to stabilize lines, and to understand logistical issues. [ABSTRACT FROM AUTHOR]

Renewables, such as solar and wind generation, combined with storage are becoming a key part of modern grid. This paper develops probabilistic tools for analysis of grid reliability with such variable generation resources. The developed tools improve speed and accuracy of the reliability analysis compared to usual Monte Carlo methods. This is achieved by using an extension of well known convolution method applicable to interdependent variables. The interdependent distributions are obtained from historical data using Machine Learning of quantile models. The paper presents a novel approach to the analysis of reliability contribution of storage based on these models and related to Information Theory. The developed tools are demonstrated in several example scenarios for ISO-New England service area. [ABSTRACT FROM AUTHOR]

This paper proposes an approach to obtain dynamic versions of static distribution factors, such as power-transfer, line-outage, and outage-transfer distribution factors. With the proposed dynamic distribution factors (DDFs), one can predict line flows over the post-contingency transient period with the same computational effort as obtaining static distribution factors. Our development centers on deriving closed-form expressions that approximate generator outputs through the post-contingency transient period with a reduced-order aggregate dynamical model to recover dynamic generator participation factors. The full suite of DDFs can then be derived by combining these dynamic generator participation factors with injection shift factors, i.e., static linear sensitivities of line active-power flows with respect to nodal active-power injections, computed at the pre-disturbance steady-state operating point. We illustrate the accuracy and computational benefits of the proposed DDFs via numerical case studies involving the New England test system. [ABSTRACT FROM AUTHOR]

Conventional power systems function under the assumption that loads are uncontrollable, and that the generation control is the primary means of preserving system voltage, frequency, and stability. Thanks to recent advancements of power electronics technology and communication schemes, demand‐side resources are now capable of providing fast frequency regulation. Controllable loads can provide upward/downward reserve during frequency excursions. In this paper, the authors consider collective contribution of large clusters of controllable loads which modulate their aggregate demand power to regulate the primary frequency. Koopman model predictive control is designed to handle local frequency variations caused by various disturbances at each load bus, considering uncertain load models. The efficacy of the proposed method has been validated using the New‐England power system considering two scenarios, namely, load variation, and generation outage. [ABSTRACT FROM AUTHOR]

This paper emerged from discussions between the authors about our shared and different perspectives of climate change and its impact on the social, emotional, physical, spiritual and cultural wellbeing of Aboriginal Peoples and mental health services in a rural region, heavily impacted in recent years by bushfires and floods. Here we discuss, from the lead authors personal perspective as a Gamilaraay Woman, the experience of Solastalgia as a critical impact of climate change on wellbeing. Specifically, we discuss the relationship of a connection to country from a Gamilaraay, first person perspective through a series of diary entries from the lead author. Authors are researchers from different cultural backgrounds, connected through a medical research futures fund research project, to promote resilience within Aboriginal communities and the health services sector in the New England, North West region. The lead author has cultural connections to some of the communities we work with and our work is informed by these connections. While this paper was written to express an Aboriginal perspective on climate change and wellbeing, it reflects our shared perspectives of how disasters such as bushfires impact the wellbeing of Aboriginal peoples. We also explore the connection between the impact of localised, recurring natural disasters and the increasing demands on mental health services in regional and rural areas and discuss what this means with Aboriginal and non‐Indigenous mental health nurses and researchers working in regional and rural areas where access to mental health services often poses considerable challenges. From our perspective, mental health research and nursing play an important role in walking alongside Aboriginal Peoples as we explore, respond and create resilience to the ever‐present influence that climate change is having on our lives, communities, country and workplaces. [ABSTRACT FROM AUTHOR]

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This paper examines the role of distinctions between genres in conflicts over expertise in an American textile mill. Riverway is a struggling 150-year-old New England textile mill where members of a diverse workforce focus on producing high quality fabric in a context that demands daily adaptive expertise. Based on fieldwork from 2015–19, we examine how Riverway workers interacted with documentation systems at the mill. They engaged with managers and coworkers around new forms of technology and shifting valuations about skill and expertise, and, in the process, made sense of their roles as workers in a declining industry where their skills and forms of expertise were nearly obsolete. Through analysis of conflicts in the mill, we examine how members of the mill's community of practice made sense of a changing genre ecology of tools for communicating, recording information, communicating asynchronously, and asserting expertise. We show how technologies for making fabric and communicating about fabric production became symbols of valuations tangentially linked to production. These technologies became lightning rods for debates about expertise, skill, and knowledge, and for everyday distinctions that workers and managers made about the value of their work during a time of economic change marked by mill closures. [ABSTRACT FROM AUTHOR]

Power system security assessment is one of the most important aspects of wind integrated power system due to intermittent and stochastic nature of wind. This paper proposes a nonparametric method for security risk assessment. Parzen window density estimation is utilized to obtain probability density functions for wind power, generation and load profiles. Correlation between independent and dependent samples of load, wind power and generation is replicated by a spatial transformation of probability distributions of random variables using Cholesky decomposition. Probabilistic load flow is performed for determining the branch flows and bus voltages of the power system for N − 1 contingency analysis. Risk assessment is performed by quantifying the probability and severity indices for branch flows and bus voltages. The proposed method is tested on modified New England 39-bus system and extended for simplified power grid of Shandong province, China. Simulation results and comparisons demonstrate the effectiveness and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

This paper investigates the history of a discursive figure that one could call the intelligent whaler. I argue that this figure's success was made possible by the construal and public distribution of whaling intelligence in an important currency of science – facts – in the preparatory phase for the United States Exploring Expedition (1838–1842). The strongest case for the necessity of the enterprise was New England whalers who were said to cruise uncharted parts of the oceans and whose discoveries of uncharted islands were reported in the local press. The document that stood at the core of the lobbying for an expedition was a table that newspaperman and public lecturer Jeremiah Reynolds had compiled after interviewing whaling captains in the country's principal whaling ports. Presenting whalers' experience in tabular and synoptic form, Reynolds's table helped forge the figure of the 'intelligent whaler', a mariner who had better geographical knowledge than other seafarers. By investigating the paper technologies that produced the 'intelligent whaler', this paper shows how Reynolds's translation of 'whaling intelligence' from news into facts marks the beginning of the intelligent whaler's long career in US-American debates about expansionism, exploration and science. [ABSTRACT FROM AUTHOR]

As a group, LGBTQ+ people experience food insecurity at a disproportionately high rate, yet food security scholars and practitioners are only beginning to uncover patterns in how food insecurity varies by subgroups of this diverse community. In this paper, we use data from the U.S. Census Bureau's Household Pulse Survey—which added measures of gender identity and sexuality for the first time in 2021—to analyze New Englanders' food insufficiency rates by gender, sexuality, race, and ethnicity. We find that (1) in the past seven days, 13.0 percent of LGB + (lesbian, gay, bisexual, and other non-heterosexual) New Englanders experience food insufficiency—which is nearly twice the rate of heterosexual people—and 19.8 percent of transgender+ (transgender, genderqueer, gender non-binary, and other non-cisgender people) New Englanders experience food insufficiency—which is two to three times the rate of cisgender men and women. (2) Whereas cisgender New Englanders experience food insufficiency at a lower rate than their counterparts in the rest of the nation (about two percentage points lower for both cisgender men and women), transgender+ New Englanders experience no such New England advantage compared to transgender+ people in the country as a whole. (3) LGBTQ+ New Englanders of color experience devastatingly high rates of food insufficiency, with, for example, one in three Black transgender+ New Englanders not having enough food to eat in the past seven days. These findings suggest that addressing food insecurity in New England demands approaching the problem with an intersectional queer lens, with attention to the ways in which racism, cissexism, and heterosexism are creating a systemic, ongoing food crisis for LGBTQ+ New Englanders, especially those who are transgender+ and/or people of color. [ABSTRACT FROM AUTHOR]

Background: Prior work has shown that middle school students struggle with algebra and that game‐based educational technologies, such as DragonBox and From Here to There!, are effective at improving students' algebraic performance. However, it remains unclear which aspects of algebraic knowledge shift as a result of playing these games and what game design features support algebraic learning. Objective: Using the data from a randomized controlled trial conducted in the 2020–2021 academic year, we (a) examined students' relative performance on assessment items measuring conceptual knowledge, procedural knowledge and procedural flexibility in algebraic equation solving, and (b) identified changes in these aspects of algebraic knowledge after playing DragonBox or From Here to There!. Methods: Eight hundred eighty‐seven seventh‐graders were randomly assigned to playing DragonBox or From Here to There! for nine 30‐min sessions throughout the school year. Students also completed a pretest, midtest and posttest measuring their algebraic knowledge. Results and Conclusion: First, prior to the intervention, students scored the highest on procedural knowledge and lowest on conceptual knowledge. Second, students significantly improved and maintained learning gains on conceptual knowledge throughout the intervention. Their performance on procedural knowledge and procedural flexibility items increased at midtest but decreased at posttest. Third, the pattern of results was consistent for students in the DragonBox and From Here to There! conditions, suggesting that both games may support students' conceptual understanding of algebra. The findings have implications for research and practice on supporting algebraic learning through game‐based technologies during and beyond educational disruptions. Lay Description: What is already known about this topic: Middle school students struggle with aspects of algebra.DragonBox and From Here to There! are two game‐based technologies designed to support students' algebraic learning.Both games implement point rewards and dynamic interactions; they differ in the uses of algebraic notation and problem structures. What this paper adds: Both games improved seventh‐graders' conceptual knowledge of algebraic equivalence.Students also improved on procedural knowledge and procedural flexibility, but the gains did not last to the end of the intervention. Implications for practice and/or policy: The games and their shared features may provide an engaging way to support students' conceptual understanding of algebra. [ABSTRACT FROM AUTHOR]