Second-generation Models Research Articles

Reflective supervision and the strategic integrative model in social work supervision

Supervision in the clinical field, including social work, represents a transformative process aimed at enhancing the supervisee's personal and professional development through the acquisition of essential competencies and skills. As a cornerstone of lifelong learning, supervision facilitates continuous growth and adaptation within the professional practice. Literature on clinical supervision identifies two primary categories of models: first-generation models, rooted in psychotherapeutic traditions, and second-generation models, which build upon and expand these foundations. This study introduces a model of supervision tailored to social work, derived from the integrative supervision framework. Central to this model is the supervisee's learning process, which is supported by three key components: the supervision framework, learning factors, and a reflective process involving both supervisor and supervisee in the context of case discussions. The supervisory relationship functions as the cohesive element that binds the model's components. The practical applicability of this integrative supervision model has been validated within the context of an integrative psychotherapy training program, where social workers were effectively trained and supervised. This model highlights the potential for enhanced learning outcomes and professional competency development in social work supervision.

GLAD-M35: a joint P and S global tomographic model with uncertainty quantification

SUMMARY We present our third and final generation joint P and S global adjoint tomography (GLAD) model, GLAD-M35, and quantify its uncertainty based on a low-rank approximation of the inverse Hessian. Starting from our second-generation model, GLAD-M25, we added 680 new earthquakes to the database for a total of 2160 events. New P-wave categories are included to compensate for the imbalance between P- and S-wave measurements, and we enhanced the window selection algorithm to include more major-arc phases, providing better constraints on the structure of the deep mantle and more than doubling the number of measurement windows to 40 million. Two stages of a Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton inversion were performed, each comprising five iterations. With this BFGS update history, we determine the model’s standard deviation and resolution length through randomized singular value decomposition.

Can transformers transform financial forecasting?

PurposeThis study aims to critically evaluate the competitiveness of Transformer-based models in financial forecasting, specifically in the context of stock realized volatility forecasting. It seeks to challenge and extend upon the assertions of Zeng et al. (2023) regarding the purported limitations of these models in handling temporal information in financial time series.Design/methodology/approachEmploying a robust methodological framework, the study systematically compares a range of Transformer models, including first-generation and advanced iterations like Informer, Autoformer, and PatchTST, against benchmark models (HAR, NBEATSx, NHITS, and TimesNet). The evaluation encompasses 80 different stocks, four error metrics, four statistical tests, and three robustness tests designed to reflect diverse market conditions and data availability scenarios.FindingsThe research uncovers that while first-generation Transformer models, like TFT, underperform in financial forecasting, second-generation models like Informer, Autoformer, and PatchTST demonstrate remarkable efficacy, especially in scenarios characterized by limited historical data and market volatility. The study also highlights the nuanced performance of these models across different forecasting horizons and error metrics, showcasing their potential as robust tools in financial forecasting, which contradicts the findings of Zeng et al. (2023)Originality/valueThis paper contributes to the financial forecasting literature by providing a comprehensive analysis of the applicability of Transformer-based models in this domain. It offers new insights into the capabilities of these models, especially their adaptability to different market conditions and forecasting requirements, challenging the existing skepticism created by Zeng et al. (2023) about their utility in financial forecasting.

Considering context: Current relationship satisfaction in a second-generation model of men's physical intimate partner violence.

Despite a half-century of scholarship devoted to explicating and disrupting the intergenerational transmission of family violence, it remains a prominent and destructive social force in the United States. Theoretical models have posited a variety of historical and concurrent risk and protective factors implicated in the trajectory from childhood violence exposure to adult perpetration. Using a second-generation model of intimate partner violence (IPV), we integrated social learning and attachment conceptualizations to examine pathways from family-of-origin violence to IPV perpetration among adult men. A sample of mixed-sex couples (N = 233) completed self-report measures related to social learning and attachment-based factors (e.g., violence in past relationships, child exposure, IPV attitudes, adult attachment) and participated in a 10-min conversation about a desired area for change in their relationship. Following, each partner participated in a video-mediated-recall procedure assessing their anger volatility and eliciting attributions of their partners' behavior. We tested mediation pathways (consistent with social learning and attachment theories) between violence in men's families of origin and their adult IPV perpetration as a function of relationship satisfaction. The proposed model fit the data well (CFI = 0.95) but had notable modifications from the hypothesized model. Generally, social-learning pathways were more consistent with the data. Relationship satisfaction interacted with some parameters. Results support theoretical advances in understanding IPV. Although exposure to violence in men's family of origin confers risk for later IPV, and a social learning developmental pathway is consistent with results, some of these effects are altered by relationship context.

Modeling high-frequency financial data using R and Stan: A bayesian autoregressive conditional duration approach

In econometrics, Autoregressive Conditional Duration (ACD) models use high-frequency economic or financial duration data, which mostly exhibit irregular time intervals. The ACD model is widely used to examine the duration of transaction volume and duration of price variations in stock markets. In this work, our goal is to devise testing that will aid in the identification of the best potential duration model among a set of four models using Bayesian approach. We test three models that rely on conditional mean duration (Weibull ACD, Log Weibull ACD, Generalized Gamma ACD) and one conditional median duration model (Birnbaum-Saunders ACD), and are being compared each other. The study was done in Rstan, a programming language for statistical inference, and the simulation uses the Hamiltonian Monte Carlo (HMC) algorithm of Markov Chain Monte Carlo (MCMC) to sample from the posterior distribution. Our findings show that Log Weibull ACD (second-generation model) as best among the four models followed by Birnbaum-Saunders ACD (third-generation model). The result offers methodological implications for algorithmic trading (algo-trading), high-frequency trading and risk management.

An 8-year longitudinal study of long-term, continuous users of electronic cigarettes

Background and AimsE-cigarettes have been available for over 15 years, but relatively little is known about long-term users. Our aim was to describe change over time in behaviours, attitudes and dependence in long-term users. Design and ParticipantsA longitudinal study of 375 e-cigarette users enrolled on the Internet in 2012–2016 and surveyed again in 2021 (8 years later on average), who continuously used e-cigarettes in the interval. FindingsFewer people in 2021 (11 %) than at baseline (33 %) had smoked tobacco in the past 31 days. Participants switched from second-generation models at baseline (e.g. Ego) to box mods in 2021 (e.g. iStick), they used larger refill bottles, they used home-made e-liquids twice as often, they used tobacco flavours less often and the nicotine concentration in e–liquids decreased from 12 to 6 mg/mL. There was no change over time in the time to the first e-cigarette puff of the day, but an e-cigarette dependence score of 0–100 decreased from 75 to 60, the frequency and strength of urges to vape decreased (from 31 % to 18 % of “strong” urges) and the proportion of people who said they would be likely to succeed if they tried to stop vaping increased. Compared to baseline, fewer people in 2021 reported vaping to cope with cravings or other smoking cessation symptoms, and fewer people reported vaping to quit smoking, to avoid relapse into smoking, or to reduce their tobacco consumption (p < 0.001 for all differences). ConclusionsIn long-term, continuous users, over a period of 8 years, substantial changes were observed in the models of e-cigarettes used, in the flavours and strength of e-liquids, and in the reasons for vaping. Their level of nicotine dependence tended to decrease over time. These users were satisfied with e-cigarettes and vaped mostly because they felt that vaping was less dangerous than smoking, and for enjoyment.

Training Indigenous Community Researchers for Community-Based Participatory Ethnographic Dementia Research: A Second-Generation Model.

Conducting community-based participatory research (CBPR) is a complex endeavor, particularly when training non-academic community members. Though examples of CBPR training programs and protocols have been published, they often address a limited set of concepts and are tailored for university or medical school students. Here, we describe the process of developing an online CBPR training program for American Indian (United States) and Indigenous (Canada) community members to conduct multi-sited ethnographic dementia research. This program is unique in its breadth and depth, as our program covers CBPR theory, methods, practical research, and administrative skills. Significantly, this program centers Indigenous methodology, pedagogy, and processes such as two-eyed seeing, storywork, and decolonization approaches. Key to this training program is a "second-generation" approach which incorporates experiential knowledge from prior community-based researchers and academic partners and is designed to develop CBPR capacity among community-based researchers and partnering communities. In this paper, we detail the experience of the first cohort of learners and subsequent improvement of the training materials. Unique challenges related to the specific research focus (dementia care pathway), population/setting (American Indian and Indigenous communities), and technology (rural digital infrastructure) are also discussed.

An Analysis of Pakistan’s Vulnerability to Economic Crisis

The post 9/11 scenario in Pakistan’s economy can readily be identified with a host of positive developments. Real GDP growth rates have averaged around 6 percent since 2002, stock market surges have broken all the previous records, there is much more dynamism in the banking industry, capital flows are pouring into the economy, foreign exchange reserves have swelled to record high levels, and poverty has witnessed a declining trend. However, what mars these celebrations since last year is the scepticism of some market commentators on the growing vulnerability of Pakistan’s economy to crisis.1 The main weakness, as widely pointed out, remains the sustainability of current account deficit along with rising fiscal imbalances. A review of empirical literature on the determinants of currency crisis introduces a host of macroeconomic fundamentals broadly based on the predictions of the seminal first- and second-generation models. Although the list of these determinants varies from study to study, the consensus appears to be on the sustainability of external and fiscal positions as the main predictors of a crisis. An overview of the Pakistani fundamentals since 2000 reveals that broadly key Pakistani economic indicators do not give an immediate cause for concern. However, the emergence of primary budget balance as a deficit and the growing trade and current account deficits in the last two years does seem to be a cause for concern.

Does intermunicipal cooperation favor higher firm creation? French evidence from a natural experiment

This paper investigates whether the increasing cooperation between municipalities in the 2000s in France favored firm creation and what type of intermunicipal cooperation was more effective. Results first show that a higher share of municipalities involved in cooperation is a significant and positive driver of firm creation. Second, results indicate that to favor firm creation, intermunicipal governments must rely on business tax sharing. Our findings are in line with first and second-generation models of fiscal federalism. Indeed, the lower tax competition is probably key to make fiscal integration conducive to firm creation. And local governments are more likely to provide market-enhancing public goods when they face the relevant fiscal incentives. Finally, we suggest that the two goals of the 1999 law (increased cooperation between urban municipalities and business tax-based sharing) were effective in boosting firm creation in the 2000s.

Improving the Behavioral Intention of Continuous Online Learning Among Learners in Higher Education During COVID-19.

The COVID-19 pandemic caused colleges and universities to rely heavily on online learning to continue knowledge dissemination to learners. This study used the second-generation model of unified theory of acceptance and use of technology (UTAUT2) to comprehensively analyze the mediating effects of self-efficacy, which affects learners’ effective use of online tools for learning, and capability of metacognition and self-regulation, which can independently adjust learning progress into the UTAUT2 model, on the learner’s willingness to continue online learning [i.e., their behavioral intention (BI)] by constructing a UTAUT2-based e-learning model. This study administered questionnaires to undergraduates in universities in East China to collect data. The effects of performance expectancy, effort expectancy (EE), social influence (SI), and facilitating conditions (FCs), hedonic motivation (HM), price value (PV), and habits on BI (directly or through mediators) were analyzed through data analysis and structural equation modeling, and the UTAUT2-based e-learning model was accordingly modified. The results indicated that the self-efficacy enhanced the effects of EE, SI, FCs, HM, and PV on learners’ BI; that metacognition and self-regulation (MS) capabilities enhanced the effects of EE on learners’ BI; and that habits had a direct and strong effect on BI. This study also provided some suggestions to enhance higher education learners’ willingness to continue online learning, such as improving social recognition and support, careful design of teaching content, easy-to-use technology, financial support. These results and suggestions may guide colleges and universities in conducting, continuing, or enhancing online education, particularly as the pandemic continues.

Verification of the design provisions for foundation footings subjected to punching-shear

The results of an experimental program on the punching-shear capacity of foundation footings without shear reinforcement are presented and discussed in this paper, in the case of four tests on as many footings resting on a quasi-natural subsoil (top thin sand layer and bottom thick gravel layer). The design models of EC2 (2004) and prEC2 (2020) for the prediction of the punching-shear capacity are checked as well, by considering 90 tests well documented in the literature and the four tests performed in this research project. Special attention is devoted to the role played by the subsoil of the footing. The largest differences between the test results and the predictions occur in the case of quasi-natural subsoils, while the footings resting on point supports yield the smallest differences. The comparison of experimental and predicted capacities shows that the current model in EC2 (2004) is neither reliable nor safe, for any type of subsoil, since the ratio between the experimental and the assessed values of the load-bearing capacity ranges from 0.625 and 0.810 in 95% of the cases, depending on subsoil properties. On the contrary, the second-generation model introduced in prEC2 (2020) provides better results, since the previous ratio is close to 0.95 in 95% of the cases examined in the paper.

The Capability and Social Justice Theories: Developing a Second-Generation Model for Enhancing Epistemological Access in Flood-Prone Schools in Kenya

This paper draws from a larger doctoral study, conducted between 2013 and 2016 in five flood-prone schools of the Budalang’i division of western Kenya. The mixed-methods study was based on empirical data drawn from twenty-three in-depth interviews from parents, senior school managers, and Sub County Education officers. Fifteen of these interviews were with males and eight with females. A questionnaire was completed by a total of 191 Standard Eight pupils, 49.2% boys and 50.8% girls across the five schools. Focus group discussions (FGDs) consisting of ten pupils from each of the five schools were also conducted. The study investigated the extent to which flood-prone schools can generate equitable epistemological access (EEA) and how they are committed to delivering a socially just educational experience. The research was embedded in the 'critical realism framework' as the overarching philosophy, premised on Sen's capability approach and Nancy Fraser's social justice framework. The two theories offer competing predications that: 1) the development of individual capabilities improves lives 2) the development of individuals should be based on a socially just approach. Findings suggested that to develop individual capabilities, schools need to embark on a socially just approach, especially to learners who are subjected to deprivation. The paper models a capabilities and social justice approach, as a substantial contribution to our understanding of the extent to which flood-prone schools of Kenya may improve individual capability development. Apart from its implications for policy, we suggest that the model should be implemented in schools to determine its efficacy.

Assessing the effect of climate change and financial development on agricultural production in ASEAN-4: the role of renewable energy, institutional quality, and human capital as moderators.

This paper examines the effect of climate change and financial development on agricultural production in ASEAN-4, namely Indonesia, Malaysia, the Philippines, and Thailand from 1990 to 2016. Further, we explore the role of renewable energy, institutional quality, and human capital on agricultural production. Since the shocks in one country affect another country, we use second-generation modeling techniques to find out the relationship among the variables. The Westerlund (2007) cointegration tests confirm long-run relationship among the variables. The results from cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model reveal that climate change negatively affects agricultural production; on the other hand, renewable energy, human capital, and institutional quality affect positively agricultural production. Moreover, renewable energy utilization, human capital, and intuitional quality moderates the effect of carbon emission on agricultural production. In addition, a U-shaped relationship exists between financial development and agricultural production, suggesting that financial development improves agricultural production only after reaching a certain threshold. Hence, this study suggests that ASEAN-4 countries must adopt flexible financial and agricultural policies so that farmers would be benefitted and agricultural production can be increased.

Second-generation TNFα turnover model for improved analysis of test compound interventions in LPS challenge studies

This study presents a non-linear mixed effects model describing tumour necrosis factor alpha (TNFα) release after lipopolysaccharide (LPS) provocations in absence or presence of anti-inflammatory test compounds. Inter-occasion variability and the pharmacokinetics of two test compounds have been added to this second-generation model, and the goal is to produce a framework of how to model TNFα response in LPS challenge studies in vivo and demonstrate its general applicability regardless of occasion or type of test compound. Model improvements based on experimental data were successfully implemented and provided a robust model for TNFα response after LPS provocation, as well as reliable estimates of the median pharmacodynamic parameters. The two test compounds, Test Compound A and roflumilast, showed 81.1% and 74.9% partial reduction of TNFα response, respectively, and the potency of Test Compound A was estimated to 0.166 µmol/L. Comparing this study with previously published work reveals that our model leads to biologically reasonable output, handles complex data pooled from different studies, and highlights the importance of accurately distinguishing the stimulatory effect of LPS from the inhibitory effect of the test compound.

To operate, or not to operate? Narrative review of the role of survival predictors in patient selection for operative management of patients with metastatic spine disease.

Accurate prediction of patient survival is an essential component of the preoperative evaluation of patients with spinal metastases. Over the past quarter of a century, a number of predictors have been developed, although none have been accurate enough to be instituted as a staple of clinical practice. However, recently more comprehensive survival calculators have been published that make use of larger data sets and machine learning to predict postoperative survival among patients with spine metastases. Given the glut of calculators that have been published, the authors sought to perform a narrative review of the current literature, highlighting existing calculators along with the strengths and weaknesses of each. In doing so, they identify two "generations" of scoring systems-a first generation based on a priori factor weighting and a second generation comprising predictive tools that are developed using advanced statistical modeling and are focused on clinical deployment. In spite of recent advances, the authors found that most predictors have only a moderate ability to explain variation in patient survival. Second-generation models have a greater prognostic accuracy relative to first-generation scoring systems, but most still require external validation. Given this, it seems that there are two outstanding goals for these survival predictors, foremost being external validation of current calculators in multicenter prospective cohorts, as the majority have been developed from, and internally validated within, the same single-institution data sets. Lastly, current predictors should be modified to incorporate advances in targeted systemic therapy and radiotherapy, which have been heretofore largely ignored.

On the relevance of turbulent structures resolution for cross-flow in a helical-coil tube bundle

Helical-coil steam generators are being adopted in a number of advanced nuclear reactor designs because of their increased heat transfer efficiency and compactness. Due to the limited operational experience and the expected high cost of dedicated experiments, it is imperative to demonstrate the modeling capability. Computational fluid dynamics is ideally suited for this problem, due to its high resolution and accuracy. However, traditional low-cost URANS turbulence models have shown limited applicability for cross-flow in helical tube bundles. On the other hand, LES methods provide high-accuracy and high-fidelity data with prohibitively high computational cost for design use. In this work, the recently proposed hybrid second-generation model STRUCT is compared to classic URANS turbulence formulations against high-fidelity LES simulations. The STRUCT model produces accurate predictions for all relevant quantities, demonstrating high potential for reproducing helical-coil tube bundle flow phenomena accurately, at an affordable computational cost.

Emission Signatures from Sub-parsec Binary Supermassive Black Holes. II. Effect of Accretion Disk Wind on Broad Emission Lines

Abstract We present an improved semi-analytic model for calculation of the broad optical emission-line signatures from sub-parsec supermassive black hole binaries (SBHBs) in circumbinary disks. The second-generation model improves on the treatment of radiative transfer by taking into account the effect of the radiation-driven accretion disk wind on the properties of the emission-line profiles. Analysis of 42.5 million modeled emission-line profiles shows that correlations between the profile properties and SBHB parameters identified in the first-generation model are preserved, indicating that their diagnostic power is not diminished. The profile shapes are a more sensitive measure of the binary orbital separation and the degree of alignment of the black hole mini-disks and are less sensitive to the SBHB mass ratio and orbital eccentricity. We also find that modeled profile shapes are more compatible with the observed sample of SBHB candidates than with our control sample of regular active galactic nuclei. Furthermore, if the observed sample of SBHBs is made up of genuine binaries, it must include compact systems with comparable masses and misaligned mini-disks. We note that the model described in this paper can be used to interpret the observed emission-line profiles once a sample of confirmed SBHBs is available but cannot be used to prove that the observed SBHB candidates are true binaries.

Adapting Security Sector Reform to Ground-Level Realities: The Transition to a Second-Generation Model

ABSTRACTThe security sector reform (SSR) model has entered a period of uncertainty and change. Despite being mainstreamed in international development and security policy, SSR has had a meagre record of achievement. SSR analysts, practitioners and policymakers are increasingly speaking of the need to move to a second-generation SSR model. There is a growing belief that SSR in its current form is too utopian, technocratic, state-centric, and donor-driven to succeed. While there is no universally accepted blueprint for second-generation SSR, a number of characteristics have emerged that have begun to define the contours of this alternative vision: less overtly liberal; willing to engage non-state actors, norms and structures; more modest in is objectives and time frames; attuned to the political nature of the process; and bottom-up in its orientation.

Habilidades terapéuticas y limitaciones en la aplicación de las terapias de tercera generación en el contexto latinoamericano

Han pasado ya treinta años desde el surgimiento y consolidación de las Terapias de Tercera Generación como parte de las Terapias Cognitivo-Conductuales. La aplicación de estas implica el desarrollo de habilidades terapéuticas específicas que difieren parcialmente de las que se utilizan en otros modelos, una de ellas es el ejercicio cotidiano y constante para convertirse en terapeuta mindful. Ser un terapeuta mindful requiere apertura hacia las filosofías orientales y potenciar la vivencia de experiencias contemplativas en la vida cotidiana. El contexto latinoamericano presenta particularidades que limitan la adecuada ejecución de las terapias de tercera generación. Entre las dificultades del terapeuta se señalan la poca formación especializada; la sobreestimación de los modelos de la primera y segunda generación; la ignorancia y la apatía hacia el esfuerzo por ser un terapeuta mindful; el poco conocimiento y menosprecio a las filosofias orientales que dan sustento al mindfulness; y las carencias económicas y falta de oportunidades en muchos terapeutas comprometidos con su formación. En cuanto a las limitaciones del contexto se mencionan la religiosidade predominante con locus de control externo, la desconfianza a las intervenciones psicológicas basadas en la meditación y la inaccesibilidad a los sectores populares de la población

Currency Crises and Purchasing Power Parity in the Asian Countries: Evidence Based on Second-Generation Panel Unit-Root Tests

This study applies a second-generation panel unit-root tests to determine the stochastic properties of real exchange rates for 14 Asian countries. Based on three popular alternative definitions of a currency crisis, we identify the several important currency crisis episodes in the region. The purchasing power parity (PPP) hypothesis was overwhelmingly supported after accommodating these heterogeneous noisy and unstable observations. Our panel unit-root test that controls for cross-sectional dependence and is robust to structural breaks confirms that the crisis in all the countries fits well with the second-generation models of currency crisis, that is, the root cause of the currency crises may not lie in economic fundamentals. PPP relation emerges when breaks and cross country dependency has been taken into account for these 14 countries.