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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]

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 Historical documents (e.g. early histories, journals, and reports) contain descriptions of burning.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]

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]

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]

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]

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 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]

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]

As an alternative to the Frequentist p‐value, the Bayes factor (or ratio of marginal likelihoods) has been regarded as one of the primary tools for Bayesian hypothesis testing. In recent years, several researchers have begun to re‐analyze results from prominent medical journals, as well as from trials for FDA‐approved drugs, to show that Bayes factors often give divergent conclusions from those of p‐values. In this paper, we investigate the claim that Bayes factors are straightforward to interpret as directly quantifying the relative strength of evidence. In particular, we show that for nested hypotheses with consistent priors, the Bayes factor for the null over the alternative hypothesis is the posterior mean of the likelihood ratio. By re‐analyzing 39 results previously published in the New England Journal of Medicine, we demonstrate how the posterior distribution of the likelihood ratio can be computed and visualized, providing useful information beyond the posterior mean alone. [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 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 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]

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]

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]

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]

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]

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]

To determine the percentage of female adolescent patients (13-26 years old) who had HIV testing ordered within 90 days of incident sexually transmitted infection (STI) diagnosis during an outpatient clinic visit. This was a retrospective chart review study evaluating 830 visits among 589 female patients 13 to 26 years who had an incident STI diagnosed in outpatient Adolescent Medicine or Pediatric Practices in an urban, nonprofit, academic, free-standing children's hospital at the main campus and a community site in the Northeast United States. Odds of HIV screening was greater at the community-based adolescent medicine practice (odds ratio [OR] = 3.17; 95% confidence interval [CI]: [1.92, 5.24]) and when seen by an adolescent medicine provider (OR = 1.44; 95% CI: [1.02, 2.03]). Only 33.5% (n = 283) of 844 clinical encounters had HIV screening obtained within 90 days of incident STI diagnosis. Overall, HIV screening rates within 90 days of STI diagnosis was low, and there is much room for improvement. [ABSTRACT FROM AUTHOR]

This cross-sectional study describes knowledge, perceived competence, and behaviors relative to intimate partner violence (IPV)-related brain injury (BI) among staff in residential domestic violence shelter programs across a New England state. A 23-item questionnaire was administered to registrants of an online IPV-related BI training series. Within this sample, knowledge about IPV-related BI was high, but relative to providing screening, accommodations, and specialized referrals to survivors with BI, perceived competence was low, and behaviors were infrequent. IPV shelter agencies should facilitate IPV-related BI training programs for staff and prioritize developing and implementing BI screening, accommodation, and referral policies and procedures. [ABSTRACT FROM AUTHOR]

Lyme disease (LD) is the most common vector-borne disease in the United States (U.S.). This paper assesses how climate change may influence LD incidence in the eastern and upper Midwestern U.S. and the associated economic burden. We estimated future Ixodes scapularis habitat suitability and LD incidence with a by-degree approach using variables from an ensemble of multiple climate models. We then applied estimates for present-day and projected habitat suitability for I. scapularis, present-day presence of Borrelia burgdorferi, and projected climatological variables to model reported LD incidence at the county level among adults, children, and the total population. Finally, we applied an estimate of healthcare expenses to project economic impacts. We show an overall increase in LD cases with regional variation. We estimate an increase in incidence in New England and the upper Midwestern U.S. and a concurrent decrease in incidence in Virginia and North Carolina. At 3°C of national warming from the 1986–2015 baseline climate, we project approximately 55,000 LD cases, a 38-percent increase from present-day estimates. At 6°C of warming, our most extreme scenario, we project approximately 92,000 LD cases in the region, an increase of 145 percent relative to current levels. Annual LD-related healthcare expenses at 3°C of warming are estimated to be $236 million (2021 dollars), approximately 38 percent greater than present-day. These results may inform decision-makers tasked with addressing climate risks, the public, and healthcare professionals preparing for treatment and prevention of LD. [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]

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]

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]

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]

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]

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]

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]

Background: Clinical judgment is declining in new graduate nurses, which affects patient safety and is therefore tested on the Next Generation NCLEX. There is limited research describing barriers and facilitators impacting nursing faculty's experiences teaching clinical judgment. Aims: The purpose of this study was to explore barriers and facilitators affecting undergraduate nursing faculty's clinical judgment teaching methods. Methods: Sixteen qualitative interviews were conducted with full-time nursing faculty at seven universities in the Northeast and Southeast regions of the United States. Results: The findings revealed program, student, and faculty factors affecting clinical judgment teaching methods. Subthemes included time, class size, students' class preparation, critical thinking, task orientation, professional development, and faculty resistance. Conclusion: Minimizing barriers and strengthening facilitators based on participants' practices and previous research can support more effective clinical judgment pedagogy, which has the potential to achieve Next Generation NCLEX success and potentially increase patient safety. [ABSTRACT FROM AUTHOR]

Purpose: Intimate partner violence (IPV) victim advocates are exposed daily to the traumas of their clients, including the potential exposure to an intimate partner homicide (IPH). While research has examined the effects of daily secondary exposure to IPV on victim advocates, little is known about the specific effect of IPH. This study examined how the IPH of a client affected advocates' perception of and approach to their work. Methods: Nine advocates were recruited from the northeastern U.S. and interviewed about their experience of the IPH of a client. Advocate interviews were analyzed using The Listening Guide Analysis which systematically isolates and listens to the different, and often contradictory, voices that a participant uses. Results: Exposure to IPH changed participants' perception of their role, how they defined client, and how they interacted with future clients. At a macro-level, the IPH of a client motivated advocates to advance changes in agency protocol, multisector responses, and state policy based on what they had learned from the IPH. Opportunities to translate shifts in their worldview into tangible changes to protocol and policy were critical to advocate adjustment after the IPH. Conclusions: In order to support advocates after IPH, organizations should acknowledge the potentially transformative effect of IPH and create opportunities for meaning making to assist in advocate adjustment. It is imperative for advocacy organizations to support their employees to prevent advocate burnout and the loss of experienced staff, and to continue to provide effective services to vulnerable members of their communities after IPH. [ABSTRACT FROM AUTHOR]

Sea‐level change threatens the U.S. East Coast. Thus, it is important to understand the underlying causes, including ocean dynamics. Most past studies emphasized links between coastal sea level and local atmospheric variability or large‐scale circulation and climate, but possible relationships with local ocean currents over the shelf and slope remain largely unexplored. Here we use 7 years of in situ velocity and sea‐level data to quantify the relationship between northeastern U.S. coastal sea level and variable Shelfbreak Jet transport south of Nantucket Island. At timescales of 1–15 days, southern New England coastal sea level and transport vary in anti‐phase, with magnitude‐squared coherences of ∼0.5 and admittance amplitudes of ∼0.3 m Sv−1. These results are consistent with a dominant geostrophic balance between along‐shelf transport and coastal sea level, corroborating a hypothesis made decades ago that was not tested due to the lack of transport data. Plain Language Summary: Sea‐level rise is an imminent threat to coastal communities worldwide, including the U.S. East Coast. Therefore, it is crucial to understand the processes driving regional sea‐level change. While past studies documented how coastal sea level may be influenced by large‐scale ocean circulation, less attention has been paid to the role of more local currents over the shelf and slope. Here we explore the relationship between coastal sea level along the northeastern U.S. and the Shelfbreak Jet, a current that flows along the shelfbreak from the Labrador Sea to Cape Hatteras (North Carolina). From 7 years of in situ data of both current velocities and water levels, we see that as coastal sea level rises, Shelfbreak Jet transport increases westward (and vice versa) on timescales of days to weeks. Our results lay the groundwork for understanding relationships between coastal sea level and local ocean dynamics elsewhere. Key Points: Daily Shelfbreak Jet transports and Southern New England coastal sea levels are anti‐correlated during 2014–2022The observed relationship between these two variables is consistent with geostrophic balanceFor this region, coastal sea levels are more sensitive to local ocean dynamics than to large‐scale circulation [ABSTRACT FROM AUTHOR]

It is unknown to what extent medical researchers generalize study findings beyond their samples when their sample size, sample diversity, or knowledge of conditions that support external validity do not warrant it. It is also unknown to what extent medical researchers describe their results with precise quantifications or unquantified generalizations, i.e., generics, that can obscure variations between individuals. We therefore systematically reviewed all prospective studies (n = 533) published in the top four highest ranking medical journals, Lancet, New England Journal of Medicine (NEJM), Journal of the American Medical Association (JAMA), and the British Medical Journal (BMJ), from January 2022 to May 2023. We additionally reviewed all NEJM Journal Watch clinical research summaries (n = 143) published during the same time. Of all research articles reporting prospective studies, 52.5% included generalizations beyond specific national study populations, with the numbers of articles with generics varying significantly between journals (JAMA = 12%; Lancet = 77%) (p < 0.001, V = 0.48). There was no evidence that articles containing broader generalizations or generics were correlated with larger or more nationally diverse samples. Moreover, only 10.2% of articles with generalizations beyond specific national populations reported external validity strengthening factors that could potentially support such extrapolations. There was no evidence that original research articles and NEJM Journal Watch summaries intended for practitioners differed in their use of broad generalizations, including generics. Finally, from the journal with the highest citation impact, articles containing broader conclusions were correlated with more citations. Since there was no evidence that studies with generalizations beyond specific national study populations or with generics were associated with larger, more nationally diverse samples, or with reports of population similarity that may permit extensions of conclusions, our findings suggest that the generalizations in many articles were insufficiently supported. Caution against overly broad generalizations in medical research is warranted. [ABSTRACT FROM AUTHOR]

Power systems exhibit nonlinearity. causing dynamic instability and complex power oscillations. This research proposes an innovative strategy using the Novel Bat Algorithm (NBA) to achieve ideal Power System Stabilizers (PSSs) in a multimachine power system. The approach shifts electromechanical modes to specific areas in the s-plane. Enhancing the multi-machine power system and establishing stabilizer parameters for dynamic performance. The study examines the designed approach aptitude for standard lead-lag PSSs configurations. In order to elevate the global search problem and transfer some static operators for the optimum optimization process. the chaos mapping. also known as CNBA. is introduced into NBA. Four different forms of chaos maps are compared in experiments to resolve unconstrained mathematical issues in order to illustrate CNBA performance. In any other case. the challenge of designing PSS under a wide range of loading situations is transformed into an optimization challenge with the damping ratio of electromechanical modes with low damping as the target function. The optimal stabilizers' gains are gotten by employing the CNBA algorithm. Second plan. an effective technique is astutely established to delineate the PSS location and quantity using CNBA and another side using participation factor. To examine the efficacy of the proposed CNBA-based PSS on a large system; it is tested on the interconnected of New-England/New-York (16 generators and 68 buses) power grid. and verified by comparative study with NBA through eigenvalue analysis and nonlinear simulation to provide evidence the algorithmic competence of CNBA. The CNBA approach yields a minimum damping ratio of 37%. which is consistent with the its eigenvalue. In contrast, the NBA approach achieves a minimum damping ratio of 31%. The simulation results reveal the fine performance of the proposed CNBA-PSS in a convincing manner and its capacity to provide an excellent damping for inter-area and local oscillations under diverse operating cases compared to NBA-PSS then in the case of PSS location. [ABSTRACT FROM AUTHOR]

Background: Pain is a significant burden for children with neurodevelopmental disabilities but is difficult for clinicians to identify. No pain assessment tools for children with neurodevelopmental disabilities have been validated for use in pediatric intensive care units. The Individualized Numeric Rating Scale (INRS) is an adapted 0-to-10 rating that includes parents' input on their child's pain indicators. Objectives: To evaluate the reliability, validity, and feasibility and acceptability of use of the INRS for assessing pain in critically ill children with neurodevelopmental disabilities. Methods: This observational study enrolled critically ill patients with neurodevelopmental disabilities aged 3 to 17 years in 2 pediatric intensive care units at a children's hospital using a prospective repeated-measures cohort design. Structured parent interviews were used to populate each patient's INRS. Bedside nurses assessed pain using the INRS throughout the study. The research team completed independent INRS ratings using video clips. Participating parents and nurses completed feasibility and acceptability surveys. Psychometric properties of the INRS and survey responses were evaluated with appropriate statistical methods. Results: For 481 paired INRS pain ratings in 34 patients, interrater reliability between nurse and research team ratings was moderate (weighted κ = 0.56). Parents said that creating the INRS was easy, made them feel more involved in care, and helped them communicate with nurses. Conclusions: The INRS has adequate measurement properties for assessing pain in critically ill children with neurodevelopmental disabilities. It furthers goals of patient- and family-centered care but may have implementation barriers. [ABSTRACT FROM AUTHOR]

The concept of "Less is more" has been gaining increasing awareness and acceptance in Critical Care. In 2017, we attempted to systematically answer the question "Can less be more in intensive care" with empirical data. We reviewed all the critical care randomized clinical trials (RCTs) between 1 January 2008 and 5 October 2016 in the New England Journal of Medicine (NEJM). This article attempts to repeat the earlier exercise using data from 5 October 2016 to 31 December 2023. This analysis of critical care RCTs in the NEJM has shown three findings. Approximately three-quarter of RCTs in critical care in the NEJM between 2008 and 2023 failed to show benefit or harm. In the years 2008-2016, patients in the intervention cohort had a higher mortality compared to controls, but in the years 2016-2023, the difference in overall mortality in patients in the intervention and control arms was not statistically significant. Compared to the years 2008-2016, in the years from 2016 to 2023, the number of RCTs showing harm decreased and those showing benefit increased. [ABSTRACT FROM AUTHOR]

The letter to the editor responds to a recent paper by Armstrong et al. that discussed pre-colonial land use by Indigenous peoples in northwestern British Columbia. The authors of the letter reject the characterization of their own scholarship as racist and argue that Armstrong et al. misrepresented their findings. They emphasize that Indigenous peoples in southern New England did have ecological impacts on the landscape, but these impacts were primarily local in scale. The authors also highlight the importance of understanding the scale and variability of Indigenous peoples' ecological impacts for conservation and land management strategies. [Extracted from the article]

The potential role of the New England seamount chain (NESC) on the Gulf Stream pathway and variability has been long recognized, and the series of numerical experiments presented in this paper further emphasize the importance of properly resolving the NESC when modeling the Gulf Stream. The NESC has a strong impact on the Gulf Stream pathway and variability, as demonstrated by comparison experiments with and without the NESC. With the NESC removed from the model bathymetry, the Gulf Stream remains a stable coherent jet much farther east than in the experiment with the NESC. The NESC is the leading factor destabilizing the Gulf Stream and, when it is not properly resolved by the model's grid, its impact on the Gulf Stream's pathway and variability is surprisingly large. A high-resolution bathymetry, which better resolves the New England seamounts (i.e., narrower and rising higher in the water column), leads to a tighter Gulf Stream mean path that better agrees with the observed path and a sea surface height variability distribution that is in excellent agreement with the observations. [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]

Phasor Measurement Units (PMU) are capable to generate multi-dimensional time series data, which is one of the most important parts for monitoring power system operation. However, various internal and external factors frequently cause the system to generate anomalous data randomly, so we expect to clean and re-fill the raw PMU data with anomalies to provide support for further advanced applications such as situational awareness, early warning, and dispatch control of the system. Existing methods mostly use classical mathematics and traditional machine learning to analyze PMU data, which makes it difficult to identify the pattern changes of the data under multiple operating conditions in power systems. In this paper, we propose a hybrid model named IRFLMDNN, which consists of an improved CART random forest model and a dynamic neural network optimized by the Levenberg Marquardt algorithm for PMU data anomaly detection and adaptive data re-filling, respectively. Experimental results based on the IEEE 39-node 10-machine New England Power System show that the proposed method has accurate and robust anomaly detection and data refilling performance. [ABSTRACT FROM AUTHOR]

Participants of New England town meeting must follow protocols to participate in this direct democratic process. Over the past 200 years, the protocols have been enacted and adapted by participants in small towns across the region. Within annual meetings, one can find small breaches that could be interpreted as playful acts. In this paper, we use the comic frame as a theoretical lens to interpret instances of such play within the rhetorical deliberation of one New England town meeting. We analyze two instances where speakers playfully use recognized parts of town meeting to achieve their rhetorical ends. We conclude with a discussion of the way play can help accomplish identification in public discourse. [ABSTRACT FROM AUTHOR]

The power system blackouts have occurred in recent years all across the world. Therefore, it is necessary to develop more effective methods for preventing such events. In this paper, a novel effective method is proposed to restore the frequency of power system and make the system stable for major disturbances. To do this, for the first time, the adaptive load shedding and emergency demand response algorithms are combined to improve the power quality in addition to system stability. To evaluate the proposed method, the New England 39-bus standard grid is selected and simulated using DIgSILENT software package and its performance is studied for moderate and large power deficit scenarios. The obtained results prove the superiority of the new method in comparison with the pervious methods from points of view lower power interruption and reducing the probability of power system collapse by decreasing the convergence time and minimizing the frequency drop. [ABSTRACT FROM AUTHOR]

This paper chronicles my fisheries compliance and enforcement research during the past 40 years. My colleagues and I at the University of Rhode Island began researching fisheries law enforcement issues around 1980 because of the high degree of noncompliance in fisheries managed by the New England Fisheries Management Council. We collected data and demonstrated that the pure deterrence model does not explain fisheries compliance behavior well. This set us on a course to develop an enriched model of compliance behavion The formal enriched model accounts for tangible and intangible motivations influencing individuals' compliance decisions, resulting in better explanations of the evidence than the pure deterrence model. The model also provides practical and superior policy prescriptions. Although the enriched model is superior to the basic pure deterrence model, much research remains to be done on explaining compliance behavior and crafting more efficient and effective compliance and regulatory programs in fisheries. [ABSTRACT FROM AUTHOR]

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