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Our objective was to design and develop an open-source model capable of simulating interventions for primary prevention of cardiovascular disease (CVD) that incorporated the cumulative effects of risk factors (eg, cholesterol years or blood-pressure years) to enhance health economic modeling in settings which clinical trials are not possible. We reviewed the literature to design the model structure by selecting the most important causal risk factors for CVD—low-density lipoprotein-cholesterol (LDL-C), systolic blood pressure (SBP), smoking, diabetes, and lipoprotein (a) (Lp(a))—and most common CVDs—myocardial infarction and stroke. The epidemiological basis of the model involves the simulation of risk factor trajectories, which are used to modify CVD risk via causal effect estimates derived from Mendelian randomization. LDL-C, SBP, Lp(a), and smoking all have cumulative impacts on CVD risk, which were incorporated into the health economic model. The data for the model were primarily sourced from the UK Biobank study. We calibrated the model using clinical trial data and validated the model against the observed UK Biobank data. Finally, we performed an example health economic analysis to demonstrate the utility of the model. The model is open source. The model performed well in all validation tests. It was able to produce interpretable and plausible (consistent with expectations of the existing literature) results from an example health economic analysis. We have constructed an open-source health economic model capable of incorporating the cumulative effect of LDL-C (ie, cholesterol years), SBP (SBP-years), Lp(a), and smoking on lifetime CVD risk. • Many health economic models for cardiovascular disease (CVD) are based on randomized clinical trials; however, because they do not incorporate the cumulative effect of changes in risk factors, they may underestimate the benefit of therapies as the time horizon of the studies increases. No health economic models have incorporated the cumulative effect of risk factors on the risk for incident CVD. • Herein, we outline the construction of a health economic model that incorporates the cumulative and causal effects of low-density lipoprotein-cholesterol, systolic blood pressure, smoking, diabetes, and lipoprotein (a) (Lp(a)) on the risk of myocardial infarction and stroke. We describe the rationale behind the novel model structure, how we incorporated causal effects of key cardiovascular risk factors, and calibrated and tested the model against real-world data. We also provide all syntax necessary for model construction. • This model has potential in public health and clinical decision making when a clinical trial for the intervention simulated is not possible or practical, which is the case for most long-term studies on the primary prevention of CVD. It can assess the cost-effectiveness of complex interventions for CVD prevention and identify individuals in whom long-term targeted CVD prevention is cost-effective. [ABSTRACT FROM AUTHOR]

Cent cinquante ans après la naissance du mot dans le lexique anglais, comment, aujourd'hui encore, parler de « psychothérapie » ? Si les objectifs et les méthodes originels du concept de « psychothérapie » apparaissaient simples et génériques, à savoir « soigner par l'esprit », notre psychiatrie et notre psychologie contemporaines ont développé une multitude de « psychothérapies » qui se présentent en général comme distinctes. Difficile pour les patients et leurs familles de s'y retrouver, difficile pour nos internes de psychiatrie et nos mastérisants en psychologie de s'y orienter, difficile pour nos autorités administratives de s'y investir. Comme elles nous apparaissent fondamentales à l'essence-même et à l'avenir de la notion de « psychothérapie », afin d'en approcher sa définition, nous convoquons les sciences du langage : (i) lexico-bibliographique en analysant la littérature scientifique des bases de données internationales et, plus globalement, le langage spécialisé psychologique et psychiatrique ; (ii) psycholinguistique en référence aux sciences cliniques du langage ; (iii) linguistique informatisée comme nous y invite le déploiement récent de l'intelligence artificielle pour l'espace de la santé mentale autant sur les plans diagnostiques que thérapeutiques, avec l'émergence des psybots. Notre objectif final sera de proposer une synthèse, une redéfinition de la notion de psychothérapie pour la psychiatrie et la psychologie clinique contemporaines. La majorité des sources retiennent une large indication aux psychothérapies, à la fois destinées à apaiser les maladies psychiatriques, les troubles psychologiques et psychosomatiques, les souffrances existentielles. Les notions d'inconscient et de prise de conscience, la place des langages verbaux et non verbaux, l'importance de la relation patient–praticien sont en majorité retenues. L'approche corporelle et les psychothérapies collectives ne sont mentionnées que plus aléatoirement. L'organisation des séances n'est évoquée que rarement, tout comme le statut du thérapeute ou l'idée que la singularité de celui-ci s'avère un élément central du traitement. La mention d'une nécessité de formation spécifique du praticien est davantage abordée, tout comme la possibilité d'association de la psychothérapie à des thérapeutiques pharmacologiques ou environnementales. Concernant l'évaluation du traitement, la définition d'objectif (global ou focal) n'est mentionnée que plus incidemment, tout comme l'intérêt d'une validité scientifique avec notamment, la prise en compte du risque d'effets indésirables. La notion dynamique de processus ou de mécanismes thérapeutiques n'est que peu évoquée or, l'étude des processus de changement pourrait participer à la définition des psychothérapies. L'évaluation des pratiques psychothérapeutiques serait à même de fédérer « la psychothérapie » à partir d'un socle commun et, s'appuyant sur celui-ci, d'ouvrir aux spécificités éventuelles « des psychothérapies » en fonction de leurs indications et/ou de leurs méthodes. Si de considérables investissements ont été placés dans l'évaluation des psychothérapies et dans les neurosciences, ils n'ont en 25 ans guère modifié la pratique psychothérapeutique de terrain et n'ont pas identifié, dans ce champ, de biomarqueurs spécifiques. Or parallèlement, depuis trois ans, des linguomarqueurs se développent à vitesse vertigineuse pour l'espace de la santé psychique, invitant les sciences du langage à mieux saisir la notion de psychothérapie, en particulier par l'analyse interlocutoire. Le développement des modèles logiciens, les méthodes d'intelligence artificielle, le tout doublé de l'augmentation exponentielle de la force de calcul d'ordinateurs personnels, ouvre la voie à un traitement automatisé du langage appliqué à la psychothérapie. Les intelligences artificielles commencent à identifier des linguomarquers en santé mentale tout en se donnant pour objectif de créer des soins scientifiquement évalués par des psybots. Qu'est-ce que la psychothérapie aujourd'hui ? Avec l'objectif d'un mieux-être, la psychothérapie est un ensemble de méthodes qui peuvent diversement s'associer dans le but d'apaiser les maladies psychiatriques, et/ou les troubles psychologiques, et/ou les souffrances existentielles. Les objectifs thérapeutiques et les moyens construits pour « faire aller mieux » sont le plus souvent concertés entre le patient avec sa demande de soins (ou nécessitant des soins sans consentement le cas échéant), d'une part, et le praticien qui y répond, d'autre part. Les thérapies peuvent être collectives en réunissant plusieurs patients (thérapies de couple, familiales, de groupe comme dans un débriefing par exemple) et, un ou plusieurs praticiens (co-thérapeute, psychothérapie institutionnelle). L'évaluation diagnostique médicopsychologique reste interdépendante des soins. Si les psychothérapies sont majoritairement efficaces, dans l'état actuel des connaissances scientifiques, les concepts théoriques sur lesquels se basent les psychothérapies (courants psychanalytiques, cognitifs, humanistes, existentiels, etc.) ne semblent pas strictement en adéquation avec les pratiques connues sous le même vocable et qui peuvent s'associer voire s'intégrer entre-elles, spontanément ou de manière formalisée. Une tendance actuelle consiste à considérer les domaines thérapeutiques existants comme des outils thérapeutiques. L'expression et l'association verbale, l'exposition, la prise de conscience corrélative à la reconstruction de représentations, la mise en pratique des volontés de changement, apparaissent comme de grands cadres structurants les psychothérapies. En d'autres termes, les psychothérapies possèdent des facteurs d'efficacité communs à toutes, et des facteurs spécifiques à chacune, ces derniers méritant d'être mieux axiomatisés. Le risque d'effets indésirables doit être pris en compte (aggravation de comportements d'évitement, re-traumatisation, majoration de traits de personnalité passifs-dépendants, etc.). Pour toute psychothérapie, la place du langage verbal apparaît prédominante, y compris en l'absence de langage vocalisé, comme lors de l'association à d'autres formes d'expression tels les arts picturaux, l'expression corporelle ou théâtrale, la relation avec un animal. Une psychothérapie est principalement constituée par une interaction monologique (avec soi-même) et dialogique (avec un clinicien) qui apaise les souffrances humaines grâce à des actions verbales permettant d'harmoniser les réseaux de représentations. Elle est scientifiquement caractérisable (et donc évaluable) par des linguomarqueurs lexico-sémantiques, syntaxiques et pragmatiques. Mais dans le même temps, la pratique de tout thérapeute lui est singulière autant qu'elle cherche à s'adapter à la singularité du patient et donc, ne s'inscrit pas uniquement dans une logique de normativité, au contraire. Les psychothérapeutes (médecins et psychologues pour la plupart) sont spécialement formés à la pratique psychothérapeutique et respectent les cadres réglementaires et déontologiques de leur profession. Dans l'idéal, ils devraient bénéficier d'une supervision, particulièrement dans les situations où le patient ne peut guère choisir son praticien (dans un camp de personnes réfugiées, en milieu militaire opérationnel, etc.). Le traitement est habituellement organisé en séances dont la durée et le rythme sont adaptées à la problématique. Les séances de thérapie peuvent, selon les modèles médico-économiques de chaque pays, être remboursées partiellement ou totalement. Une psychothérapie peut s'associer à d'autres dimensions thérapeutiques, notamment pharmacologiques (médicaments antidépresseurs, régulateurs de l'humeur, etc.), neuropsychologiques (remédiation cognitive essentiellement), environnementales (règles hygiénodiététiques, congé de maladie, etc.). De plus en plus, des robots conversationnels ou psybots proposent une offre de soin basique et complémentaire destinée à la régulation émotionnelle, la sophrologie, l'observance thérapeutique, etc. La psychothérapie reste une notion anthropologique, difficilement définissable en quelques phrases, autant qu'elle vise à apaiser les tourments issus de la nature humaine, dans son entièreté philosophique, mais également les tourments singuliers intimes à chaque être dont le cerveau et les réseaux de représentations demeurent uniques. Les tensions issues de nos réseaux de représentations les caractérisent au point de pouvoir être considérées comme homéostatiques, si elles ne font pas souffrir. La psychothérapie nécessite ainsi cette adaptation permanente, cette intelligence co-constructive avec le patient, et dont l'explicitation avancée des résultats ne sera jamais totalement certaine car c'est par cette création continue-même, toujours instable, toujours en devenir, y compris les soins parachevés, que se construit la psychothérapie. One hundred and fifty years after the word first appeared in the English lexicon, how can we still talk about "psychotherapy" today? While the original aims and methods of the concept of "psychotherapy" appeared simple and generic, namely "to heal through the mind," our contemporary psychiatry and psychology have developed a multitude of "psychotherapies", which generally present themselves as distinct. This makes it difficult for patients and their families to find their way around, difficult for our psychiatric interns and psychology master's students to orient themselves, and difficult for our administrative authorities to get involved. As they appear to us to be fundamental to the very essence and future of the notion of "psychotherapy," in order to approach its definition, we call upon the language sciences: (i) lexico-bibliographical, by analyzing the scientific literature in international databases and, more generally, specialized psychological and psychiatric language; (ii) psycholinguistics, with reference to the clinical sciences of language; (iii) computerized linguistics, as the recent deployment of artificial intelligence in the field of mental health invites us to do, at both diagnostic and therapeutic levels, with the emergence of psybots. Our final objective will be to propose a synthesis and redefinition of the notion of psychotherapy for contemporary psychiatry and clinical psychology. The majority of sources indicate that psychotherapy is widely used to treat psychiatric illnesses, psychological and psychosomatic disorders, and existential suffering. The notions of the unconscious and awareness, the place of verbal and non-verbal languages, and the importance of the patient–practitioner relationship are the most widely accepted. The somatic approach and group psychotherapy are mentioned less frequently. The organization of sessions is rarely mentioned, as is the status of the therapist or the idea that the therapist's uniqueness is a central element of the treatment. The need for specific training for the practitioner was mentioned more often, as was the possibility of combining psychotherapy with pharmacological or environmental therapies. With regard to the evaluation of treatment, the notion of defining an objective (global or focal) is mentioned only incidentally, as is the importance of scientific validity, in particular taking into account the risk of undesirable effects. The dynamic notion of therapeutic processes or mechanisms is rarely mentioned, yet the study of change processes could help to define psychotherapies. The evaluation of psychotherapeutic practices would be capable of federating "psychotherapy" on the basis of a common foundation and, building on this, opening up to the possible specificities of "psychotherapies" according to their indications and/or methods. Although considerable investment has been made in the evaluation of psychotherapies and in neuroscience, over the last 25 years there has been little change in psychotherapeutic practice in the field, and no specific biomarkers have been identified. At the same time, over the last three years, linguomarkers have been developing at breakneck speed in the field of psychological health, inviting the language sciences to gain a better grasp of the notion of psychotherapy, in particular through interlocutory analysis. The development of logician models and artificial intelligence methods, coupled with the exponential increase in the computing power of personal computers, is paving the way for automated language processing applied to psychotherapy. Artificial intelligences are beginning to identify biomarkers in mental health, with the aim of creating scientifically evaluated care by psybots. What is psychotherapy today? With the aim of improving well-being, psychotherapy is a set of methods that can be combined in various ways to alleviate psychiatric illnesses and/or psychological disorders and/or existential suffering. The therapeutic objectives and the means devised to "make people feel better" are most often agreed between the patient requesting treatment (or requiring treatment without consent when legally applicable) and the practitioner who responds. Therapies may be collective, bringing together several patients (couples therapy, family therapy, group therapy such as debriefing, for example) and one or more practitioners (co-therapist, institutional psychotherapy). Medical diagnosis and psychological assessment remain interdependent with care. While most psychotherapies are effective, given the current state of scientific knowledge, the theoretical concepts on which psychotherapies are based (psychoanalytical, cognitive, humanist, existential, etc.) do not seem to be strictly in line with the practices known under the same name, which may be associated or even integrated with each other, either spontaneously or in a formalized way. A current trend is to consider existing therapeutic areas as therapeutic tools. Expression and verbal association, exposure, awareness correlating with the reconstruction of representations, and putting into practice the will to change, appear to be the main frameworks structuring psychotherapies. In other words, psychotherapies have factors of efficacy that are common to all of them, and factors that are specific to each, the latter deserving to be better axiomatized. The risk of undesirable effects must be taken into account (aggravation of avoidance behavior, re-traumatization, increase in passive-dependent personality traits, etc.). In all psychotherapy, the role of verbal language appears to be predominant, even in the absence of vocalized language, such as when associated with other forms of expression such as the pictorial arts, bodily or theatrical expression, or a relationship with an animal. Psychotherapy consists mainly of monological interaction (with oneself) and dialogical interaction (with a clinician) that alleviates human suffering through verbal actions that harmonize networks of representations. It can be scientifically characterized (and therefore evaluated) using lexical-semantic, syntactic, and pragmatic linguomarkers. But at the same time, every therapist's practice is singular in that it seeks to adapt to the patient's uniqueness, and therefore does not fit solely into a logic of normativity, on the contrary. Psychotherapists (mostly doctors and psychologists) are specially trained in psychotherapeutic practice and respect the regulatory and ethical framework of their profession. Ideally, they should benefit from supervision, particularly in situations where the patient has little choice of practitioner (in a refugee camp, in an operational military environment, etc.). Treatment is usually organized in sessions, the length and pace of which are adapted to the problem. Depending on the medical and economic model in each country, therapy sessions may be partially or fully reimbursed. Psychotherapy can be combined with other therapeutic approaches, particularly pharmacological (antidepressants, mood regulators, etc.), neuropsychological (mainly cognitive remediation) and environmental (dietary hygiene rules, sick leave, etc.). Increasingly, conversational robots or psybots are offering basic and complementary care for emotional regulation, sophrology, therapeutic compliance, etc. Psychotherapy remains an anthropological notion, difficult to define in a few sentences, in as much as it aims to soothe the torments arising from human nature, in its philosophical entirety, but also the singular, intimate torments of each being whose brain and networks of representations remain unique. The tensions arising from our networks of representations characterize them to such an extent that they can be considered homeostatic, if they do not cause suffering. Psychotherapy therefore requires this permanent adaptation, this co-constructive intelligence with the patient, the results of which can never be totally certain, because it is through this very continuous creation, which is always unstable, always in the process of becoming, even when the treatment has been completed, that psychotherapy is constructed. [ABSTRACT FROM AUTHOR]

Ghana has a long history of engagement with the IMF. Successive governments of Ghana have sought economic bailouts from the IMF due to worsening domestic macroeconomic stability. This paper examines Ghana's historical engagement with the IMF and the associated macroeconomic outcomes, and offers lessons for economic restructuring and growth beyond the bailouts. The paper explores the common patterns of the key macroeconomic variables and possible latent causal effects. The results reveal intermittent and short-term effects of the IMF programs. The bailouts often have a short-term impact on macroeconomic stability and growth, but the effects are unsustainable in the long term, especially after the IMF program ends. [ABSTRACT FROM AUTHOR]

Ammonia production has traditionally been done by using the Haber-Bosch process, that operates at extremely high pressure (200–300 bar), has a large carbon footprint, and requires significant energy. For ammonia to be used as a hydrogen carrier, it is desired that it is produced by using modular technologies under benign conditions, yet the economics remain commercially viable. This paper investigates a novel technology for ammonia synthesis by using a microwave-assisted low-pressure reactor. Microwave reactors are compact and can be readily modularized and started/shutdown thus making them ideal to be integrated with the electric grid or with regional/local renewable-based electric generation facilities. For separation of unreacted reactants from the product ammonia, if the traditional condensation separation technology used in the high-pressure Haber-Bosch process is used, then the separation process needs to be operated under cryogenic condition thus adversely affecting the economics. A solid sorbent based separation technology is investigated in this paper. A kinetic model for the microwave-catalytic synthesis process is used. An isotherm model is developed for MgCl 2 –Si adsorbent and used for modeling the dynamic adsorption-desorption cycle. A plant-wide model with heat and mass integration is developed. An economic model is developed and used for economic optimization by using an equation-oriented approach. Since the adsorption-desorption process is dynamic, for techno-economic optimization, a reduced order model for the key performance measures of the adsorption-desorption process as a function of its input and decision variable is developed under cyclic steady-state conditions. For the optimized MW-assisted process, the levelized cost of ammonia is $772/mt as opposed to $808/mt for the conventional Haber-Bosch process for a hydrogen price of $2.07/kg. The MW-assisted process is found to be economically viable in the US market if the hydrogen price is below $4/kg. • Plant-wide model of a novel MW-assisted ammonia synthesis process is developed. • A solid-sorbent based separation technology is investigated for separation. • A reduced model based approach is developed for optimizing the adsorption process. • For the optimized process, the levelized cost of ammonia is found to be $772/mt. • The technology is found to be economically viable for H 2 price below $4/kg. [ABSTRACT FROM AUTHOR]

The Mount Hood Diabetes Challenge Network aimed to examine the impact of model structural uncertainty on the estimated cost-effectiveness of interventions for type 2 diabetes. Ten independent modeling groups completed a blinded simulation exercise to estimate the cost-effectiveness of 3 interventions in 2 type 2 diabetes populations. Modeling groups were provided with a common baseline population, cost and utility values associated with different model health states, and instructions regarding time horizon and discounting. We collated the results to identify variation in predictions of net monetary benefit (NMB) and the drivers of those differences. Overall, modeling groups agreed which interventions had a positive NMB (ie, were cost-effective), Although estimates of NMB varied substantially—by up to £23 696 for 1 intervention. Variation was mainly driven through differences in risk equations for complications of diabetes and their implementation between models. The number of modeled health states was also a significant predictor of NMB. This exercise demonstrates that structural uncertainty between different health economic models affects cost-effectiveness estimates. Although it is reassuring that a decision maker would likely reach similar conclusions on which interventions were cost-effective using most models, the range in numerical estimates generated across different models would nevertheless be important for price-setting negotiations with intervention developers. Minimizing the impact of structural uncertainty on healthcare decision making therefore remains an important priority. Model registries, which record and compare the impact of structural assumptions, offer one potential avenue to improve confidence in the robustness of health economic modeling. • Structural uncertainty is known to be an important, but often unexamined, contributor to healthcare decision uncertainty. • Conducting a common simulation exercise across 10 independent modeling groups using uniform parameterization has allowed us to investigate the structural drivers of differences in cost-effectiveness estimates between diabetes models. We show how blinded simulation exercises can be used to quantitatively examine both the drivers and impact of structural uncertainty. Similar exercises could be replicated to examine the effect of structural uncertainty in healthcare decision problems in other disease areas. • This article demonstrates the value of incentivizing collaboration and comparative assessments among modeling groups to critically examine their modeling practice. This generates more robust evidence for decision making. Healthcare decision makers may benefit from directly facilitating collaboration between modeling groups, such as aiding funding and maintenance of model registries, which can demonstrate the relative suitability of different decision models for specific decision problems. [ABSTRACT FROM AUTHOR]

The optimal control design of the boiler-turbine system is vital to ensure feasibility and high responsiveness over desired load variations. Using the traditional linear control techniques realization of this task is difficult, as the boiler-turbine mechanism has strong nonlinearities. Besides, environmental and economic concerns have replaced existing tracking control ones as the primary concerns of advanced power plants. Thus, this study proposes an optimal economic model predictive controller (EMPC) scheme for this unit on the basis of the input/output feedback linearization (IOFL) method. By employing the IOFL method, this unit is decoupled into a new linearized model that is utilized for developing the suggested optimal IOFL EMPC technique. The proposed control scheme is formulated in an economic quadratic programming form that considers the input-rate and input limits of the unit for optimal economic performance. In addition, an adaptive iterative algorithm is utilized for constraints mapping with guaranteeing a feasible solution in a finite number of steps without violation of original constraints over the entire predictive horizon. The outcomes of the simulation show that the suggested optimal IOFL EMPC scheme offers an improved dynamic and economic output performance over fuzzy hierarchical MPC, fuzzy EMPC, and nonlinear EMPC techniques during various load variations. • An optimal EMPC scheme based on IOFL method is proposed for boiler-turbine unit. • The IOFL EMPC scheme is formulated in an economic QP form including constraints. • An adaptive iterative algorithm ensures feasible solution without limits violation. • The IOFL EMPC scheme enhances dynamic economic performance for boiler-turbine unit. [ABSTRACT FROM AUTHOR]

This study comprehensively examines the techno-economic potential of utilizing offshore wind resources for hydrogen production in Mexico. Through the integration of geospatial analysis techniques with energy generation and economic models, the research estimates hydrogen production, CO 2 eq emissions reduction potential, Levelized cost of electricity (LCOE), and Levelized cost of hydrogen (LCOH). The analysis highlights Mexico's capacity to produce up to 217.33 million tons of hydrogen annually, predominantly from the Gulf of Mexico. Centralized offshore hydrogen production demonstrates significant cost advantages, being up to 0.92 USD/kg cheaper than onshore production. The study also underscores the economic benefits of repurposing existing oil and gas infrastructure, which can reduce LCOH by up to 11%. Environmental benefits are substantial, with hydrogen use in ammonia production potentially reducing CO 2 eq emissions by 82.5%. Additionally, the study identifies highly suitable offshore areas for hydrogen production, particularly near existing oil infrastructure, facilitating the integration of new renewable energy projects with minimal additional infrastructure development. These findings provide valuable insights for policymakers and stakeholders, emphasizing the economic viability and environmental benefits of offshore wind hydrogen production as a strategic pathway for Mexico's energy transition and decarbonization efforts. [Display omitted] • Mexico can produce 217.33 MTon/year of hydrogen, 78.8% from the Gulf. • Transmitting energy offshore and then producing H 2 is up to 0.92 USD/kg cheaper. • Repurposing offshore oil infrastructure reduces LCOH by up to 11%. • 40% of offshore areas, near oil infrastructure, are ideal for hydrogen production. • 82.5% of CO 2 eq emissions in ammonia production could be reduced. [ABSTRACT FROM AUTHOR]

The recent CAP aims at better targeting beneficiaries and being more selective in its objectives. This has drawn attention to how policies interact with resources used by farms in terms of both economic and environmental costs. Conditional Process Models under Structural Equation Modeling framework may offer statistical indications on these complex interactions. The proposed model, called SMIRNE, is applied to an Italian macro-area at severe risk of land pollution (Pianura Padana) caused by livestock sector. Results show a more substantial support from pillar I policies than those provided by pillar II in addressing a relevant response of policies to the economic and environmental costs of the livestock activities with reference to the use of land. [ABSTRACT FROM AUTHOR]

• We rely on a multi-sectoral balance-of-payments constrained growth model that incorporates intermediate imports. • We explicitly incorporate the effects of intermediate imports and relative prices into the analysis. • The outcome of the study shows that the multi-sectoral balance-of-payments constrained growth model correctly predicts Turkey's growth path. • Heightened dependence on imported intermediates, resulting in a reduction in the income elasticity of export demand and an elevation in the income elasticity of import demand, could potentially exert adverse effects on the overall economic growth. • Countries, like Turkey, can benefit from increasing the usage of available domestic inputs in export production to reduce leakage occasioned by the extensive importation of foreign factor inputs. Several countries rely heavily on imported intermediate inputs for the manufacturing of their exported goods. Understanding the implications of this reliance on a country's growth performance is vital. To address this issue, we conducted an in-depth analysis using the multi-sectoral balance-of-payments constrained growth model with data from Turkey spanning 1970 to 2019. We used the autoregressive distributed lag method to estimate sectoral export, final import, intermediate goods import, and total import demand functions for five technology-based sectors. Subsequently, we calculated growth rates using the multi-sectoral balance of payments constrained growth models, factoring in the estimated income and price elasticities, as well as the respective sectoral shares in total exports, total imports, total final imports, and total intermediate goods imports. Our results demonstrate that the multi-sectoral balance of payments constrained growth model, which incorporates the impact of imported intermediate goods, successfully predicts Turkey's growth path. The findings indicate that structural changes in the production process and the use of imported intermediate inputs have a positive impact on exports. However, Turkey's significant dependence on imported intermediate goods during the production process leads to a decrease in the multi-sectoral balance of payments constrained growth rate. [ABSTRACT FROM AUTHOR]

This paper explores ways to promote the Shared Parking Business Economy Model (SPBEM) in traditional business districts (TBD) to mitigate their declining survival. A microscopic four-party evolutionary game model investigates the mechanisms behind the complex interactions among four typical businesses in TBD. Evolutionary stability is also analyzed based on three different scenarios. Secondly, this paper examines the limited rationality of participants and sifts the impact of significant factors on the dynamic evolution process by using the cumulative prospect theory and the quantitative equation of the conformity effect. The paper validates the game model and main conclusions through realistic scenarios and numerical simulations. Finally, the four main types of parameters are extensively discussed. The findings suggest that the implementation of SPBEM could enhance the economic development of TBD. Furthermore, successful promotion of SPBEM in TBD demands coordinated efforts from the four types of businesses. Initial participation probability, proportion of parking slots, historical average customer flow, and cooperation revenue all positively influence participation behavior; and promoting SPBEM in TBD requires coordination between the four business types. These findings serve as valuable references for TBD managers and operators in their decision-making processes. • An economic model of shared parking is presented. • The mechanism of the quadratic evolutionary game in traditional business districts is discussed. • Four factors influencing the participation decisions of merchants are identified. [ABSTRACT FROM AUTHOR]

The fourth-generation Very High Temperature Reactor (VHTR) holds great promise as a reactor type for large-scale clean hydrogen (H 2) production in conjunction with the Sulfur-Iodine (SI) thermochemical process. However, limited research exists on the design and economic analysis of coupled VHTR and SI process nuclear hydrogen production systems, particularly when the combined cycle is incorporated as a power cycle within the system. To address this issue, we have developed and examined an advanced VHTR-driven hydrogen-electricity co-production system that adopts the SI process and combined cycle. The system has been modeled from both thermodynamic and economic perspectives, and its thermo-economic performance has been assessed under various operating conditions. Several parametric studies have been conducted to elucidate factors influencing the unit H 2 production cost. The simulation results demonstrate that the thermal efficiency of the proposed SI process is in the range of approximately 27.95%–35.28%, and under the baseline operating condition, the whole system can concurrently produce hydrogen at a rate of about 290 mol/s while generating around 103 MW of net electric power, with thermal efficiency, exergy efficiency, and unit H 2 production cost of about 37%, 36%, and 4.32 $/kg, respectively. The unit H 2 production cost of the proposed system is predicted to range between approximately $1.5/kg and $7/kg. Finally, it has been determined that increasing the reactor thermal power, extending the system lifetime, improving the cost capacity factor and unit electricity price, as well as decreasing the mass flow ratio and interest rate, all contribute to a reduction in the unit H 2 production cost. • An advanced nuclear-powered hydrogen-electricity co-production system is proposed. • A promising sulfur-iodine thermochemical hydrogen production process is developed. • A reliable economic evaluation model is established. • The economic characteristics and cost impact mechanism of the system are analyzed. • The system's unit hydrogen production cost is estimated to be 1.5–7 $/kg. [ABSTRACT FROM AUTHOR]

This study aimed to systematically review evidence on the cost-effectiveness of chimeric antigen receptor T-cell (CAR-T) therapies for patients with cancer. Electronic databases were searched in October 2022 and updated in September 2023. Systematic reviews, health technology assessments, and economic evaluations that compared costs and effects of CAR-T therapy in patients with cancer were included. Two reviewers independently screened studies, extracted data, synthesized results, and critically appraised studies using the Philips checklist. Cost data were presented in 2022 US dollars. Our search yielded 1809 records, 47 of which were included. Most of included studies were cost-utility analysis, published between 2018 and 2023, and conducted in the United States. Tisagenlecleucel, axicabtagene ciloleucel, idecabtagene vicleucel, ciltacabtagene autoleucel, lisocabtagene maraleucel, brexucabtagene autoleucel, and relmacabtagene autoleucel were compared with various standard of care chemotherapies. The incremental cost-effectiveness ratio (ICER) for CAR-T therapies ranged from $9424 to $4 124 105 per quality-adjusted life-year (QALY) in adults and from $20 784 to $243 177 per QALY in pediatric patients. Incremental cost-effectiveness ratios were found to improve over longer time horizons or when an earlier cure point was assumed. Most studies failed to meet the Philips checklist due to a lack of head-to-head comparisons and uncertainty surrounding CAR-T costs and curative effects. CAR-T therapies were more expensive and generated more QALYs than comparators, but their cost-effectiveness was uncertain and dependent on patient population, cancer type, and model assumptions. This highlights the need for more nuanced economic evaluations and continued research to better understand the value of CAR-T therapies in diverse patient populations. • Chimeric antigen receptor T-cell (CAR-T) therapies are a group of novel cancer therapeutics that have shown significant promise in the treatment of patients whose disease has relapsed or become refractory to treatment. However, these come at a significantly higher price than existing therapies, raising questions of their value for money. • This systematic review provides a comprehensive summary and critical evaluation of the available evidence on the economic value of CAR-T therapies. It encompasses a review of 47 studies that compare 7 distinct CAR-T therapies against standard cancer care practices, covering both pediatric and adult patient populations. • The findings indicate that CAR-T therapies tend to be more costly, but also more effective than their comparator treatments. However, the cost-effectiveness estimates for these therapies are highly uncertain, influenced by a range of factors including patient demographics, specific cancer types being treated, and underlying assumptions of the economic models used. Given the evolving evidence on the safety and efficacy of CAR-T therapies, it is crucial to update estimates as new evidence becomes available. [ABSTRACT FROM AUTHOR]

Health economic (HE) models are often considered as "black boxes" because they are not publicly available and lack transparency, which prevents independent scrutiny of HE models. Additionally, validation efforts and validation status of HE models are not systematically reported. Methods to validate HE models in absence of their full underlying code are therefore urgently needed to improve health policy making. This study aimed to develop and test a generic dashboard to systematically explore the workings of HE models and validate their model parameters and outcomes. The Probabilistic Analysis Check dashBOARD (PACBOARD) was developed using insights from literature, health economists, and a data scientist. Functionalities of PACBOARD are (1) exploring and validating model parameters and outcomes using standardized validation tests and interactive plots, (2) visualizing and investigating the relationship between model parameters and outcomes using metamodeling, and (3) predicting HE outcomes using the fitted metamodel. To test PACBOARD, 2 mock HE models were developed, and errors were introduced in these models, eg, negative costs inputs, utility values exceeding 1. PACBOARD metamodeling predictions of incremental net monetary benefit were validated against the original model's outcomes. PACBOARD automatically identified all errors introduced in the erroneous HE models. Metamodel predictions were accurate compared with the original model outcomes. PACBOARD is a unique dashboard aiming at improving the feasibility and transparency of validation efforts of HE models. PACBOARD allows users to explore the working of HE models using metamodeling based on HE models' parameters and outcomes. • Health economic evaluation guidelines emphasize the importance of health economic model validation, but there is currently no easy-to-use tool available to systematically validate (parts of) health economic models. • This article presents the development and testing of the Probabilistic Analysis Check dashBOARD, which is a unique online tool aimed at validating the plausibility of parameters and outcomes of health economic models and at exploring the working of health economic models, using interactive plots and metamodeling methods. • The Probabilistic Analysis Check dashBOARD is a useful tool for model developers to validate health economic models at different stages of model development, through uploading probabilistic parameters and outcomes of the health economic model. Also, it enables reviewers to efficiently evaluate health economic models. [ABSTRACT FROM AUTHOR]

This study aims to show the application of flexible statistical methods in real-world cost-effectiveness analyses applied in the cardiovascular field, focusing specifically on the use of proprotein convertase subtilisin-kexin type 9 inhibitors for hyperlipidemia. The proposed method allowed us to use an electronic health database to emulate a target trial for cost-effectiveness analysis using multistate modeling and microsimulation. We formally established the study design and provided precise definitions of the causal measures of interest while also outlining the assumptions necessary for accurately estimating these measures using the available data. Additionally, we thoroughly considered goodness-of-fit assessments and sensitivity analyses of the decision model, which are crucial to capture the complexity of individuals' healthcare pathway and to enhance the validity of this type of health economic models. In the disease model, the Markov assumption was found to be inadequate, and a "time-reset" timescale was implemented together with the use of a time-dependent variable to incorporate past hospitalization history. Furthermore, the microsimulation decision model demonstrated a satisfying goodness of fit, as evidenced by the consistent results obtained in the short-term horizon compared with a nonmodel-based approach. Notably, proprotein convertase subtilisin-kexin type 9 inhibitors revealed their favorable cost-effectiveness only in the long-term follow-up, with a minimum willingness to pay of 39 000 Euro/life years gained. The approach demonstrated its significant utility in several ways. Unlike nonmodel-based or alternative model-based methods, it enabled to (1) investigate long-term cost-effectiveness comprehensively, (2) use an appropriate disease model that aligns with the specific problem under study, and (3) conduct subgroup-specific cost-effectiveness analyses to gain more targeted insights. • Cost-effectiveness analysis utilizing electronic health records databases can offer valuable real-world evidence for drugs recently approved. However, the statistical aspects of economic-health evaluations in chronic illnesses using decision models are often overlooked. • We proposed the application of a flexible multistate decision model based on microsimulation to replicate a target trial using observational data, enabling the study of proprotein convertase subtilisin-kexin type 9 inhibitors cost-effectiveness. Notably, these methods overcome the limitations of standard Markov decision models by considering the dependence of individuals' healthcare paths on their past. • This study provides novel insights into the real-world cost-effectiveness of proprotein convertase subtilisin-kexin type 9 inhibitors in hyperlipidemia. Furthermore, the statistical approach used here could also be useful for other diseases, treatments, or healthcare systems. [ABSTRACT FROM AUTHOR]

Historically, economic models of memory have neglected a pivotal aspect: decay, the established notion that memories deteriorate over time, resulting in a loss of fidelity. In this paper we show that a framework of rational memory with decay can produce the recency effect and other intuitively appealing memory phenomena. We apply the framework to both finite time and dynamic programming settings, deriving a wide range of results with a focus on comparative statics and asymptotic behaviors. Many of our results can also be applied to multi-dimensional rational inattention settings where individuals have to split their attention across several information sources. [ABSTRACT FROM AUTHOR]

To evaluate the cost-effectiveness of repetitive transcranial magnetic stimulation (rTMS) as an adjunct to standard care from an Australian health sector perspective, compared to standard care alone for adults with treatment-resistant bipolar depression (TRBD). An economic model was developed to estimate the cost per disability-adjusted life-year (DALY) averted and quality-adjusted life-year (QALY) gained for rTMS added to standard care compared to standard care alone, for adults with TRBD. The model simulated the time in three health states (mania, depression, residual) over one year. Response to rTMS was sourced from a meta-analysis, converted to a relative risk and used to modify the time in the depressed state. Uncertainty and sensitivity tested the robustness of results. Base-case incremental cost-effectiveness ratios (ICERs) were $72,299 per DALY averted (95 % Uncertainty Interval (UI): $60,915 to $86,668) and $46,623 per QALY gained (95 % UI: $39,676 - $55,161). At a willingness to pay (WTP) threshold of $96,000 per DALY averted, the base-case had a 100 % probability of being marginally cost-effective. At a WTP threshold of $64,000 per QALY gained, the base-case had a 100 % probability of being cost-effective. Sensitivity analyses decreasing the number of sessions provided, increasing the disability weight or the time spent in the depression state for standard care improved the ICERs for rTMS. Dependent on the outcome measure utilised and assumptions, rTMS would be considered a very cost-effective or marginally cost-effective adjunct to standard care for TRBD compared to standard care alone. • The cost-effectiveness of repetitive transcranial magnetic stimulation (rTMS) added to standard care for treatment resistant bipolar depression (TRBD) was estimated. • The economic model used the available efficacy data on rTMS and standard care for TRBD. • rTMS was estimated to decrease morbidity at an additional cost. • rTMS was considered cost-effective for TRBD. [ABSTRACT FROM AUTHOR]

This research aimed to develop best-practice recommendations for identifying the "standard of care" (SoC) and integrate it when it is the comparator in diagnostic economic models (SoC comparator). A multi-methods approach comprising 2 pragmatic literature reviews and 9 expert interviews was used. Experts rated their agreement with draft recommendations based on the authors' analysis of the reviews. These were refined iteratively to produce final recommendations. Fourteen best-practice recommendations are provided. Care pathway mapping (using quantitative, qualitative, or mixed-methods approaches) should be used for identifying the SoC comparator. Guidelines analysis can be integrated with expert opinion to identify pathway variability and discrepancies from clinical practice. For integrating the SoC comparator into the model, recommendations around structure, input sourcing, data aggregation and reporting, input uncertainty, and model variability are presented. For example, modelers should consider that the reference standard is not synonymous with the SoC, and the SoC may not be the only comparator. The comparator limitations should be discussed with clinical experts, but elicitation of its diagnostic accuracy is not recommended. Probabilistic sensitivity analysis is recommended when evaluating the overall input uncertainty, and deterministic sensitivity analysis is useful when there is high model uncertainty or SoC variability. Consensus could not be reached for some topics (eg, the role of real-world data, model averaging, and alternative model structures), but the reported discussions provide points for consideration. To our knowledge, this is the first guidance to support modelers when identifying and operationalizing the SoC comparator in diagnostic cost-effectiveness models. • Modeling the cost-effectiveness requires a comparison of the new diagnostic and patient management strategy with a comparator, often a complex standard of care (SoC) pathway. The new diagnostic test can replace or, more commonly, be integrated with the diagnostic SoC pathway. This presents 2 main challenges in obtaining useful estimates of cost-effectiveness: (1) identifying the diagnostic SoC pathway to define the comparator and (2) integrating it into the model. • We identified possible methodological approaches through pragmatic literature reviews and expert interviews. Some examples are to identify the SoC comparator via mapping the care pathway through qualitative, quantitative, or mixed-methods approaches; to select data on the diagnostic accuracy of the SoC comparator from studies in which the reference standard is the one used for the new test and report detailed information of the data source; and to assess the impact of the SoC pathway variability through scenario analysis. • We provide 14 recommendations that can support modelers to minimize the risk of a misrepresentation of the incremental clinical utility of the new diagnostic test because of the uncertainty and variability of the SoC comparator. We identified practice recommendations, gaps in knowledge, and areas where further research would advance the field. [ABSTRACT FROM AUTHOR]

Shortages in the physician anaesthesia workforce have led to proposals to introduce new staff groups, notably in the UK National Health Service (NHS) Anaesthesia Associates (AAs) who have shorter training periods than doctors and could potentially contribute to workflow efficiencies in several ways. We analysed the economic viability of the most efficient staffing model, previously endorsed by both the UK Royal College of Anaesthetists and the Association of Anaesthetists, wherein one physician supervises two AAs across two operating lists (1:2 model). For this model to be economically rational (something which neither national organisation considered), the employment cost of the two AAs should be equal to or less than that of a single supervisor physician (i.e. AAs should be paid <50% of the supervisor's salary). As the supervisor can be an autonomous specialty and specialist (SAS) doctor, this sets the economically viable AA salary envelope at less than £40,000 per year. However, we report that actual advertised AA salaries greatly exceed this, with even student AAs paid up to £48,472. Economically, one way to justify such salaries is for AAs to become autonomous such that they eventually replace SAS doctors at a lower cost. We discuss some other options that might increase AA productivity to justify these salaries (e.g. ≥1:3 staffing ratios), but the medico-political consequences of each of them are also profound. Alternatively, the AA programme should be terminated as economically nonviable. These results have implications for any country seeking to introduce new models of working in anaesthesia. [ABSTRACT FROM AUTHOR]

The main objective was to use discrete event simulation to model the impact of wait-time, defined as the time between leukapheresis and chimeric antigen receptor (CAR-T) infusion, when assessing the cost-effectiveness of tisagenlecleucel in young patients with relapsed/refractory acute lymphoblastic leukemia. The movement of patients through the model was determined by parametric time-to-event distributions, with the competing risk of an event determining the costs and quality-adjusted life-years (QALYs) assigned. Cost-effectiveness was expressed using the incremental cost-effectiveness ratio (ICER) for tisagenlecleucel compared with chemotherapy over the lifetime. The base case generated a total of 5.79 QALYs and $622 872 for tisagenlecleucel and 1.19 QALYs and $181 219 for blinatumomab, resulting in an ICER of $96 074 per QALY. An increase in mean CAR-T wait-time to 6.20 months reduced the benefit and costs of tisagenlecleucel to 2.78 QALYs and $294 478 because of fewer patients proceeding to infusion, reducing the ICER to $71 112 per QALY. Alternatively, when the cost of tisagenlecleucel was assigned pre-infusion in sensitivity analysis, the ICER increased with increasing wait-time. Under a payment arrangement where CAR-T cost is incurred post-infusion, the loss of benefit to patients is not reflected in the ICER. This may be misguiding to decision makers, where cost-effectiveness ratios are used to guide resource allocation. discrete event simulation is an important tool for economic modeling of CAR-T as it is amenable to capturing the impact of wait-time, facilitating better understanding of factors affecting service delivery and consequently informed decision making to deliver faster access to CAR-T for patients. • The main advantage of using discrete event simulation to model the cost-effectiveness of chimeric-antigen receptor T cell therapy (CAR-T) was the ability to capture the manufacturing time, from the point of leukapheresis to CAR-T infusion • In modeling this process, we have shown that extended wait-time substantially reduces both the benefit and cost of CAR-T because of fewer patients proceeding to infusion • The model highlights the importance of capturing wait-time in an economic evaluation because it has implications for how arrangements between manufacturers and payors could be structured to deliver faster access to CAR-T for patients. [ABSTRACT FROM AUTHOR]

In this paper we examine territorial behavior in the ecological conditions that foster conflict. We develop an economic model that isolates the effects of resource skew on territorial ranges, as well as their interactions with unequal appropriation abilities. We then conduct a controlled laboratory experiment to test the predictions of our model and find that observed behavior tends to cluster around the equilibrium predictions and that all comparative statics have the predicted sign. Additionally, we find that equally strong appropriators select more exclusive and less overlapping ranges than what is predicted with symmetric resources, while weaker appropriators choose more engulfed ranges than what is predicted with skewed resources. [ABSTRACT FROM AUTHOR]

With a fixed prize budget, to increase total effort, we design a two-stage lottery contest where heterogeneous agents face the prospect of promotion and the threat of demotion from one stage to the next. We develop two competing theoretical models to generate predictions about behavior: (i) the standard economic model and (ii) a behavioral model where agents derive non-monetary utility from winning. The experimental results provide strong support for the use of promotion and demotion in contests when abilities are homogeneous, however, they do not provide strong support for the use of promotion and demotion in contests when ability differences are large. Our experimental results are consistent with the predictions made by the behavioral model. [ABSTRACT FROM AUTHOR]

• Employment is wage-constrained and real depreciation raises exports. • Neither the real exchange rate nor exports affect domestic sales. • There is a lack of transmission from investment to growth. • Volatility effects are weak for exports and inconsistent for investment. • There is little evidence of an interest rate effect for investment. This paper evaluates South African manufacturing performance over 25 years. It reports the evolution of five basic variables: employment, mark-ups, exports, domestic sales, and investment, using an aggregated sample of firms from a reliable business database. The approach differs from other economic models by the complementary use of management perceptions in estimated equations. The results reinforce some previous findings; for example, wage pressure tends to constrain domestic sales while the relative wage incentivizes capital investment. The exchange rate matters for exports and investment is constrained by skill shortages. Other findings add evidence to contested issues such as the importance of the interest rate level for investment and exchange rate stability for export growth. Relationships between key variables can help to identify growth constraints and the potential for manufacturing jobs. In particular, the lack of transmission from exports to employment or to domestic sales and the response of the mark-up to investment suggest institutional failures in coordinating market activity. [ABSTRACT FROM AUTHOR]

Tuberculosis remains a major public health problem in South Africa, with an estimated 300,000 cases and 55,000 deaths in 2021. New tuberculosis vaccines could play an important role in reducing this burden. Phase IIb trials have suggested efficacy of the M72/AS01 E vaccine candidate and BCG-revaccination. The potential population impact of these vaccines is unknown. We used an age-stratified transmission model of tuberculosis, calibrated to epidemiological data from South Africa, to estimate the potential health and economic impact of M72/AS01 E vaccination and BCG-revaccination. We simulated M72/AS01 E vaccination scenarios over the period 2030–2050 and BCG-revaccination scenarios over the period 2025–2050. We explored a range of product characteristics and delivery strategies. We calculated reductions in tuberculosis cases and deaths and costs and cost-effectiveness from health-system and societal perspectives. M72/AS01 E vaccination may have a larger impact than BCG-revaccination, averting approximately 80% more cases and deaths by 2050. Both vaccines were found to be cost-effective or cost saving (compared to no new vaccine) across a range of vaccine characteristics and delivery strategies from both the health system and societal perspective. The impact of M72/AS01 E is dependent on the assumed efficacy of the vaccine in uninfected individuals. Extending BCG-revaccination to HIV-infected individuals on ART increased health impact by approximately 15%, but increased health system costs by approximately 70%. Our results show that M72/AS01 E vaccination or BCG-revaccination could be cost-effective in South Africa. However, there is considerable uncertainty in the estimated impact and costs due to uncertainty in vaccine characteristics and the choice of delivery strategy. This work was funded by the Bill & Melinda Gates Foundation (INV-001754). This work used the Cirrus UK National Tier-2 HPC Service at EPCC (https://www.cirrus.ac.uk) funded by the University of Edinburgh and EPSRC (EP/P020267/1). [ABSTRACT FROM AUTHOR]

Based on a Greenpeace International survey, Fast Moving Consumer Goods (FMCG) companies are the dominant force behind the single-use economic model that drives the plastic waste crisis originating from consumption and production by producing industrial waste that must be handled appropriately with the concept of sustainable supply chain management (SSCM). This study discusses SSCM practices in one of the FMCG companies, namely PT XYZ, and focuses on sustainable packaging supply chains, intending to know the application of SSCM in the supply chain and improvements that can be made to reduce waste and its negative impacts. The exploratory research was done with a case study type and used a mixed-method approach to formulate the development that can be done to reduce the waste and negative impact of the packaging supply chain. The assessment resulted from calculating the Life Cycle Assessment software, Simapro, with the CML-IA baseline V3.06/EU25 method. This method represents the environmental impact using 11 indicators. The most significant adverse environmental impacts are global warming, human toxicity, and marine aquatic ecotoxicity. The most significant contribution to the cause of the negative environmental impact is the consumption of electricity and water, which produce excess CO2 and boiler engines which produce excess NO2. Improvements can be made by reducing CO2 gas and using alternative fuels for environmentally friendly boilers. [ABSTRACT FROM AUTHOR]

The present work is to exploit the Gudermannian neural network (GNN) using the global competency of genetic algorithm (GA) and quick local refinements of sequential quadratic programming approach (SQPA), i.e., GNN-GA-SQPA for the nonlinear economic and environmental system. The differential form of the nonlinear system depends upon three classes, system capability of industrial elements, implementation cost of control values and a new diagnostics technical elimination cost. An error-based fitness function is constructed using the differential system and then optimized by using the hybrid competency of the GA-SQPA. Ten numbers of neurons, a merit Gudermannian function, and the suitable weight vectors are presented in the neural network construction. The accuracy of the GNN-GA-SQPA is assessed through the comparisons and the negligible performances of absolute error. The statistical observations using single and multiple trials validate the stability of the scheme. [ABSTRACT FROM AUTHOR]

Supercritical water gasification is a promising technology for renewable hydrogen production from high moisture content biomass. This work produces a machine learning surrogate model to predict the Levelised Cost of Hydrogen over a range of biomass compositions, processing capacities, and geographic locations. The model is published to facilitate early-stage economic analysis (doi.org/10.6084/m9.figshare.22811066). A process simulation using the Gibbs reactor provided the training data using 40 biomass compositions, five processing capacities (10–200 m3/h), and three geographic locations (China, Brazil, UK). The levelised costs ranged between 3.81 and 18.72 $/kg H2 across the considered parameter combinations. Heat and electricity integration resulted in low process emissions averaging 0.46 kgCO 2 eq/GJ H2 (China and Brazil), and 0.37 kgCO 2 eq/GJ H2 (UK). Artificial neural networks were most accurate when compared to random forests and support vector regression for the surrogate model during cross-validation, achieving an accuracy of MAPE: <4.6%, RMSE: <0.39, and R2: >0.99 on the test set. [Display omitted] • A techno-economic surrogate model for supercritical water gasification is created. • Model predicts the LCOH for different biomass compositions, scales, and locations. • RF, SVR, and ANN algorithms were compared for the surrogate model. • ANNs achieved the highest prediction accuracy during cross-validation. • Final model is published to facilitate early-stage feedstock evaluation. [ABSTRACT FROM AUTHOR]

Tracking model predictive control (MPC) and economic model predictive control (EMPC) are essential techniques in process control. Economic model predictive control with zone tracking offers an effective means of concurrently addressing both tracking MPC and EMPC objectives. However, the aggregated conflicting objectives do not always align with the prioritization of critical tasks, such as safety, stability, quality, and economy. To address this issue, this study introduces a lexicographic approach for EMPC with zone tracking, which aims at balancing the competing zone tracking and economic objectives. The work also explores a generalized lexicographic multi-objective MPC (MoMPC) formulation and presents lexicographic zone economic model predictive control to accommodate multiple tracking and economic objectives. The advantages, disadvantages, and effectiveness of the proposed approach are validated and showcased through extensive simulation experiments. • A lexicographic zone economic model predictive control (ZEMPC) method is proposed. • Lexicographic ZEMPC encompassing multiple zone and economic objectives is developed. • The effectiveness of the proposed approach is supported by extensive experiments. [ABSTRACT FROM AUTHOR]

Probabilistic sensitivity analysis (PSA) has been shown to reduce bias in outcomes of health economic models. However, only 1 existing study has been identified that incorporates PSA within a resource-constrained discrete event simulation (DES) model. This article aims to assess whether it is feasible and appropriate to use PSA to characterize parameter uncertainty in DES models that are primarily constructed to explore the impact of constrained resources. PSA is incorporated into a new case study of an Emergency Department DES. Structured expert elicitation is used to derive the variability and uncertainty input distributions associated with length of time taken to complete key activities within the Emergency Department. Potential challenges of implementation and analysis are explored. The results of a trial of the model, which used the best estimates of the elicited means and variability around the time taken to complete activities, provided a reasonable fit to the data for length of time within the Emergency Department. However, there was substantial and skewed uncertainty around the activity times estimated from the elicitation exercise. This led to patients taking almost 3 weeks to leave the Emergency Department in some PSA runs, which would not occur in practice. Structured expert elicitation can be used to derive plausible estimates of activity times and their variability, but experts' uncertainty can be substantial. For parameters that have an impact on interactions within a resource-constrained simulation model, PSA can lead to implausible model outputs; hence, other methods may be needed. • Probabilistic sensitivity analysis (PSA) is standard practice in health economic models, but it has rarely been used in resource-constrained cost-effectiveness simulation models. • Structured expert elicitation can be used to derive plausible estimates of resource-related parameters and their variability, but experts' uncertainty can be substantial, limiting their suitability for use in this context. • For some parameters, such as costs and utilities, existing PSA methods are likely applicable, but for parameters that have an impact on interactions within a resource-constrained simulation model, PSA can substantially alter and lead to implausible model outputs; hence, alternative methods may be needed. [ABSTRACT FROM AUTHOR]

I analyze the decisions of a β − δ consumer who, through effort invested in focusing on the future, sets the δ that will apply to her self in the next period. She has access to no other commitment technology. Because the model interprets dynamic inconsistency in a way that gives rise to the demand for costly self-control, it disambiguates the welfare benefit of commitment devices that limit future options. It explains why cognitive loading is associated with impulsivity, why U.S. savings rates have exhibited increased income stratification since the 1980s, and what visionary leadership and role models signify in economic terms. [ABSTRACT FROM AUTHOR]

The usefulness of transportation project evaluation depends on the completeness of its benefit measures. Since transportation networks are intrinsically spatial, transportation improvement projects have spatial access and location characteristics that can lead to a variety of non-user economic benefits. Recent research has enabled us to better understand how spatial context and spatial heterogeneity play further roles in generating efficiency gains for non-users, in the form of productivity, income, and cost savings for both private and public sectors of the economy. This paper draws upon that body of research to expand our understanding of the means by which transportation projects can generate economic efficiency gains, and approaches needed to measure them. It covers topics beyond those captured by current definitions of "wider economic benefits," including additional sources of scale economies associated with freight distribution and connectivity, and further public and private sector economic gains enabled by environmental and social inclusion improvement. It points to ways that non-user economic benefits can be more comprehensively defined and better measured by recognizing their spatial scale, context, and threshold effects. It also identifies ways that current benefit measurement methods introduce unintended bias into transportation investment decision-making through omission and mismeasurement. The result is a case for a refresh of thinking about how we classify and recognize non-user economic benefits in transportation evaluation, and how we apply transportation planning and economic models to support their measurement. • Transport decisions biased when non-user benefits are ignored or mis-measured. • Non-user economic benefits depend on spatial access, proximity, or connectivity. • Spatial scale, context, and heterogeneity affect measurement of non-user benefit. • Benefits from freight density, virtual density, effective density, non-user cost. • Rigid travel modeling standards hold back non-user benefits. [ABSTRACT FROM AUTHOR]

The objective of this study was to systematically review the literature related to the economic evaluation of kidney transplantation to determine the extent of current research and identify gaps for future research. We searched 4 medical and 2 economic electronic databases as well as hand-searching reference lists of review articles and other pertinent articles. Exclusion criteria included articles that did not include original work (ie, reviews), were not in English, and were not journal articles or economic working papers (eg, commentaries, theses, abstracts). Full-text data abstraction included qualitative and quantitative parameters with the intent to perform a gap analysis for future research. A total of 299 articles were included and spanned a 48-year period from 1968 to 2016, with >73% published in 2000 or after. The most common topics included immunosuppression drugs, dialysis vs kidney transplantation, organ allocation, and the potential market for donor organs. Most articles were from the United States and originated from 73 medical journals and 34 economic journals or working paper centers. There were 58 articles dealing with costing, 153 using cost-effectiveness, 69 using economic modeling, 6 performing systematic reviews with meta-analyses, and 13 exploring the qualitative financial environment of individuals and the economy. Research gaps were identified in every parameter used to evaluate the studies, and a new system of gap analysis for scoping reviews was also proposed. [ABSTRACT FROM AUTHOR]

Economic models and experiments frequently use lotteries with only a few outcomes. We study the correlation of such lotteries and discuss its relevance for economic applications. In particular, we fully characterize the joint distribution of two binary lotteries via their first three univariate moments and their correlation coefficient. As we illustrate alongside several examples, the resulting parametrization may be useful for economic modeling and experimental design. [ABSTRACT FROM AUTHOR]

A major concern with Bayesian decision making under uncertainty is the use of a single probability measure to quantify all relevant uncertainty. This paper studies prior robustness as a form of continuity of the value of a decision problem. I show that this notion of robustness is characterized by a form of stable choice over a sequence of perturbed decision problems, in which the available acts are perturbed in a precise fashion. I then introduce a choice-based measure of prior robustness and apply it to models of climate mitigation and portfolio choice. • Belief Robustness and Continuity: Beliefs are "robust" if minor changes in beliefs lead to minor changes in choices. This notion can be tested by evaluating perturbations of feasible bets. • Measure of Robustness: A comparative measure of belief robustness can quantify the sensitivity of optimal choices to parametric assumptions. • Impact on Key Economic Models: The measure shows that heavy-tailed distributions yield more robust choices in portfolio and economy-climate models, highlighting its practical importance. [ABSTRACT FROM AUTHOR]

People who are at ultra-high risk (UHR) for psychosis receive clinical care with the aim to prevent first-episode psychosis (FEP), regardless of the risk of conversion to psychosis. An economic model from the Canadian health system perspective was developed to evaluate the cost-effectiveness of treating all with UHR compared to risk stratification over a 15-year time horizon, based on conversion probability, expected quality-of-life and costs. The analysis used a decision tree followed by a Markov model. Health states included: Not UHR, UHR with <20 % risk of conversion to FEP (based on the North American Prodrome Longitudinal Study risk calculator), UHR with ≥20 % risk, FEP, Remission, Post-FEP, and Death. The analysis found that: risk stratification (i.e., only treating those with ≥20 % risk) had lower costs ($1398) and quality-adjusted life-years (0.055 QALYs) per person compared to treating all. The incremental cost-effectiveness ratio for 'treat all' was $25,448/QALY, and suggests treating all may be cost-effective. The model was sensitive to changes to the probability of conversion. [ABSTRACT FROM AUTHOR]

This paper investigates the conditions for airline coalition frequent flyer program (FFP) to exist. A stylized economic model is proposed to analyze both stand-alone and coalition FFP. With the help of numerical analysis, we identify the profit-maximizing conditions for both types of FFP and recognize critical thresholds for a profitable coalition FFP. We find that a coalition FFP would not be profitable if the reward value were far less than the total price of airfare and partner product. In addition, the optimal reward of a coalition FFP will increase as the total price rise. Finally, coalition FFP is unlikely to be more socially efficient than stand-alone FFP. Based on the analytical results, we provide policy implications and highlight the importance of optimal rewards, partner price coordination and market supervision for the successful and profitable airline coalition FFP. • We investigate the conditions for the existence of coalition frequent flyer programs (FFP). • A stylized economic model is proposed to analyze both stand-alone and coalition FFPs. • A coalition FFP would not be profitable if the optimal reward value was too low. • The coalition FFP could be profitable when the commercial partner's price is at a median level. • Profitability of a coalition FFP hinges on aligning reward value with total costs. [ABSTRACT FROM AUTHOR]

Present work covers the treatment of lignin enriched paper industry wastewater (LEPIW) using electrocoagulation (EC) process with stainless steel (SS) electrodes. In this study, EC operation is optimized in term of % chemical oxygen demand (COD) removal and treatment cost (USD/kg COD removed). Single parameter study has been performed to study the effect of process parameters on % COD removal and treatment cost. Central composite design (CCD) of design of expert (DOE) has been used to corelate the input (time, initial COD, solution pH and current) and output parameters (% COD removal and treatment cost). Single parameter study states that maximum % COD removal of 84.4 & 77% is achieved in 40 & 60 min for initial COD:500 &1000 mg/L while 74, 66.7 & 58% can be achieved in 100 min for initial COD of 2000, 3000 & 4000 mg/L, respectively under optimum condition (solution pH:7, current: 1 A). Cost analysis summarizes that treatment cost decreases with increase in initial organic load (2.036, 2.075, 1.554, 1.247 & 1.127 USD/kg COD removed for initial COD of 500, 1000, 2000, 3000 & 4000 mg/L, respectively) at optimum condition. The caloric study states 2.31and 3.25 J/mg can be generated from the sludge and scum produced during EC process. DOE software suggests − 6.66–6.79% & − 16.73–7.95% error between experimental and designed value for % COD removal and treatment cost. [Display omitted] • COD removal range 84.4–58% is noticed for initial COD 500–4000 mg/l. • Treatment time increases from 60 to 100 min for initial COD range of 500–4000 mg/l. • Treatment cost 1.12–2.07 USD/kg COD R is noted for COD range of 500–4000 mg/l. • 2.31 and 3.25 J/mg energy is found from generated sludge and scum respectively. • Model predicts − 6.66–6.79% & − 16.73–7.95% error for COD removal & treatment cost. [ABSTRACT FROM AUTHOR]

A correlation model was explored and established for the first time, linking the properties of entrainers to the process economics of extractive distillation separation for ternary azeotropes. Firstly, the extraction process of ternary azeotrope (methyl tert-butyl ether/ethanol (EtOH)/water) with common entrainers was optimized using a multi-objective optimization method based on a genetic algorithm. The optimal process parameters were obtained, and dimethyl sulfolone emerged as the best entrainer for the system. An economic correlation model was developed using machine learning to link the properties of entrainers and total annual cost (TAC). The model exhibited a determination coefficient of 0.993 and a single percentage error of less than 2% for each data set, indicating a significant fitting degree and prediction accuracy. The feasibility of selecting the optimal entrainer and calculating the economic benefit of the model was verified through another ternary azeotrope system (i.e., tetrahydrofuran/EtOH/water). The model provides valuable insights into energy savings and entrainer screening in extractive distillation. Additionally, the influence of the heat integration process with different entrainers on the economic benefit was analyzed, and the optimum entrainer changed to glycerol after the heat integration process. This finding suggests that determining the optimum entrainer should consider the possible heat integration process design. Finally, the relationship between the intermolecular interaction mechanism and separation effect was revealed through quantum chemical calculations. [ABSTRACT FROM AUTHOR]

In this article, we propose to build a statistical model for factor productivity and illustrate our predictions on a common toy model : DICE. Data show that the variation of primary exergy , or simply called exergy is a good predictor of the TFP variation. That remark allows us to design new economic scenarios that respect the Paris Agreement. These scenarios are of particular interest for policy makers. Moreover, our model is capable to reconcile different projections by the introduction of environmental constraints. On one hand, if exergy increases, we have similar projections with standard economic models. On the other hand, if exergy decreases, we obtain projections closer to other Integrated Assessment Models, where economic output declines (Meadows et al., 2013; Capellán-Pérez et al., 2020). • Factor productivity variations are linked to exergy variations. • Our scenarios are more pessimistic than traditional ones due to exergy integration. • Great out of sample predictions achieved during the Covid crisis. [ABSTRACT FROM AUTHOR]

Public subsidy, a frequently applied tool of economic development is often provided to the business sector assuming that it promotes investments, employment, and income generation. In this paper a micro economic model based empirical analysis is presented that shows the possible impact of public subsidy on economic growth. The outcomes are derived by investigating the investment decision of the enterprise with and without public subsidy. It is demonstrated that public subsidy may increase social welfare, but under certain circumstances it also may decrease it, partly because authorities deciding about them fail to consider the information on the investment projects that determines the outcome. The empirical analysis of corporate subsidies proves that both cases occur. The number of firms that performed well and presumably had not enough own resources to fund the investment was less than 10% of all subsidized firms. The programs had an overall negative impact on economic growth. We provide recommendations on how methods of evaluations, project selection and monitoring should be modified to achieve better results of subsidy programs. [ABSTRACT FROM AUTHOR]

Economic model predictive control (EMPC) has attracted an abundance of interest in both academic and industrial communities in recent years because it is able to increase the economic profits of dynamic systems. For greater computational efficiency, two-layer EMPC schemes are applied in some complex process control. However, the performance of two-layer EMPC is significantly influenced by the accuracy of the chosen process model. Reinforcement learning (RL) has been studied as a model-free strategy of model-based control approaches, but its safety and stability remain a concern. In order to estimate the model parameters of nonlinear dynamic systems in real time, this work introduces a unique scheme for merging two-layer EMPC and RL. In this scheme, the two-layer EMPC technique maintains closed-loop stability and recursive feasibility while operating the closed-loop dynamic system optimally. And the RL agent continually compares the observed states to the predictions made by the EMPC and modifies the time-varying parameters as necessary. The usability of the proposed scheme is shown on a chemical process of ethylene oxide production in dynamic environment. This work enables online and continuous control, optimization, and model correction, and makes process production optimization more feasible and profitable. [Display omitted] A two-layer economic model predictive control scheme is considered. A RL agent is integrated to estimate the time-varying parameters. Lyapunov-based stability analysis is provided. A chemical production simulation is utilized to verify the efficiency. [ABSTRACT FROM AUTHOR]

Health economic models commonly apply observed general population mortality rates to simulate future deaths in a cohort. This is potentially problematic, because mortality statistics are records of the past, not predictions for the future. We propose a new dynamic general population mortality modeling approach, which enables analysts to implement predictions of future changes in mortality rates. The potential implications of moving from a conventional static approach to a dynamic approach are illustrated using a case study. The model utilized in National Institute for Health and Care Excellence appraisal TA559, axicabtagene ciloleucel axi for diffuse large B-cell lymphoma, was replicated. National mortality projections were taken from the UK Office for National Statistics. Mortality rates by age and sex were updated each modeled year with the first modeled year using 2022 rates, the second modeled year 2023 and so on. A total of 4 different assumptions were made around age distribution: fixed mean age, lognormal, normal, and gamma. The dynamic model outcomes were compared with those from a conventional static approach. Including dynamic calculations increased the undiscounted life-years attributed to general population mortality by 2.4 to 3.3 years. This led to an increase in discounted incremental life-years within the case study of 0.38 to 0.45 years (8.1%-8.9%), and a commensurate impact on the economically justifiable price of £14 456 to £17 097. The application of a dynamic approach is technically simple and has the potential to meaningfully affect estimates of cost-effectiveness analysis. Therefore, we call on health economists and health technology assessment bodies to move toward use of dynamic mortality modeling in future. • Health economic models commonly apply observed general population mortality rates to simulate future deaths in a cohort. This is potentially problematic, because mortality statistics are records of the past, not predictors of the future. • We propose a new dynamic general population mortality modeling approach, which enables analysts to implement predictions of future changes in mortality rates. We demonstrate the potential impact of this approach using a replication of the axicabtagene ciloleucel model from National Institute for Health and Care Excellence appraisal TA559. • Including dynamic calculations increased the undiscounted life-years attributed to general population mortality by 2.4 to 3.3 years with a potentially meaningful impact on the economically justifiable price of £14 456 to £17 097. [ABSTRACT FROM AUTHOR]

This study estimated the direct costs of managing renal cell carcinoma, the seventh most common neoplasm in high-income countries, through the development of a whole disease model based on clinical pathways, pondering the probabilities of all diagnostic-therapeutic procedures and linking the reimbursement tariff to each procedure. The results of this work could provide useful insights for policy-makers planning healthcare resources allocation. Background: Renal cell carcinoma (RCC) is the seventh most common neoplasm in high-income countries. New clinical pathways have been developed to deal with this tumor, which includes costly drugs that pose an economic threat to the sustainability of healthcare services. This study provides an estimate of the direct costs of care for patients with RCC by stage of disease (early vs . advanced) at diagnosis, and disease management phase along the pathway recommended by local and international guidelines. Materials and Methods: Considering the clinical pathway for RCC adopted in the Veneto region (north-east Italy) and the latest guidelines, we developed a very detailed "whole-disease" model that covers the probabilities of all potentially necessary diagnostic and therapeutic actions involved in the management of RCC. Based on the cost of each procedure according to the Veneto Regional Authority's official reimbursement tariffs, we estimated the total and average per-patient costs by stage of disease (early or advanced) and phase of its management. Results: In the first year after diagnosis, the mean expected cost of a patient with RCC is €12,991 if it is localized or locally-advanced and reaches €40,586 if it is advanced. For early disease, the main cost is incurred by surgery, whereas medical therapy (first and second line) and supportive care become increasingly important for metastatic disease. Conclusion: It is crucially important to examine the direct costs of care for RCC, and to predict the burden on healthcare services of new oncological therapies and treatments, as the findings could be useful for policy-makers planning the allocation of resources. [ABSTRACT FROM AUTHOR]

Economic model predictive control and tracking model predictive control are two popular advanced process control strategies used in various of fields. Nevertheless, for a given process, which controller should be chosen to achieve better performance is uncertain when noise exists. To this end, a sensitivity-based performance assessment approach is proposed to pre-evaluate the dynamic economic and tracking performance of them and guide the controller selection in this work. First, their controller gains around the optimal steady state are evaluated using the sensitivities of corresponding constrained dynamic programming problems. Second, the controller gains are substituted into the control loop to derive the propagation of process and measurement noise. Subsequently, the Taylor expansion is introduced to simplify the calculation of variance and mean of each variable. Finally, the tracking and economic performance surfaces are plotted and the performance indices are precisely calculated through integrating the objective functions and the probability density functions. Moreover, boundary moving (i.e., back off) and target moving can be pre-configured to guarantee the stability of controlled processes based on the proposed approach. Extensive simulations under different cases prove that the proposed approach can provide useful guidance on performance assessment and controller design. • An approach to determine the potential performance of economic model predictive control in the presence of noise. • Guidelines for controller selection are provided based on the potential achievable performance. • Extensive simulations to illustrate how to use the proposed approach and its applicability. [ABSTRACT FROM AUTHOR]

Large-scale hydrogen production with wind power generation has been gaining increasing attention and applications. Achieving a good balance between the capacity and cost of wind power generation however remains as a critical challenge restricting the development of wind-hydrogen integrated energy systems (WHIES). In addition, the aging factor may come in over time, making negative impacts on the efficiency and cost of WHIES. In this work, a method is proposed to seek a good balance between the capacity and cost of WHIES. Specifically, by comparing operational data and equipment condition, we evaluate the aging status of the wind power generation system and the hydrogen production system, then the aging economic model of WHIES is proposed. By taking into account the actual operating conditions in constructing the WHIES objective function with the aging factor, the proposed model allows striving to maximize the production capacity with the minimum cost. An improved multi-objective gray wolf optimizer algorithm is developed to solve the WHIES cost optimization problem. Finally, case studies are carried out via MATLAB based on the configuration and experimental data for a specific wind farm located in Ningxia, China. Our results help achieve a balance between maximizing capacity and minimizing cost under various conditions. [Display omitted] • The proposed method provides operation program for different energy systems. • Cost models are used to evaluate the aging status of WHIES. • An IMOGWO is used to solve nonlinear benefit-cost coupling problems. • The balance between production and cost of WHES is discussed. [ABSTRACT FROM AUTHOR]

To determine the effect of socioeconomic status on efficacy and cost thresholds at which theoretical diabetes prevention policies become cost-effective. We designed a life table model using real-world data that captured diabetes incidence and all-cause mortality in people with and without diabetes by socioeconomic disadvantage. The model used data from the Australian diabetes registry for people with diabetes and the Australian Institute of Health and Welfare for the general population. We simulated theoretical diabetes prevention policies and estimated the threshold at which they would be cost-effective and cost saving, overall, and by socioeconomic disadvantage, from the public healthcare perspective. From 2020 to 2029, 653 980 people were projected to develop type 2 diabetes, 101 583 in the least disadvantaged quintile and 166 744 in the most. Theoretical diabetes prevention policies that reduce diabetes incidence by 10% and 25% would be cost-effective in the total population at a maximum per person cost of Australian dollar (AU$) 74 (95% uncertainty interval: 53-99) and AU$187 (133-249) and cost saving at AU$26 (20-33) and AU$65 (50-84). Theoretical diabetes prevention policies remained cost-effective at a higher cost in the most versus least disadvantaged quintile (eg, a policy that reduces type 2 diabetes incidence by 25% would be cost-effective at AU$238 [169-319] per person in the most disadvantaged quintile vs AU$144 [103-192] in the least). Policies targeted at more disadvantaged populations will likely be cost-effective at higher costs and lower efficacy compared to untargeted policies. Future health economic models should incorporate measures of socioeconomic disadvantage to improve targeting of interventions. • Inequality in health for chronic diseases are well described. Nevertheless, health economic models that are designed to include measures of equity are scant. • We use theoretical simulations to show that targeting public health policies to more disadvantaged groups in society greatly increases the maximum cost of the policy that would be cost-effective. Similarly, less effective policies are much more likely to be cost-effective, and a given policy comes at a lower net cost when targeted at more disadvantaged groups. • These findings underscore the utility of accounting for socioeconomic disadvantage in the assessment, development, and implementation of health policy. [ABSTRACT FROM AUTHOR]

Air separation units (ASUs) integrated with liquid air energy storage (LAES) have the potential to balance grid demand and improve production profits. This study aims to enhance the demand response of a novel co-production air separation system (NCASS) by maximizing the energy arbitrage of a LAES system. We developed a mixed-integer nonlinear programming model to minimize operating costs by using a proxy model to represent the ASU production space and a black box model to represent the material and energy flow balance of LAES. The model is based on rigorous mathematical programming and, considers material and energy flow balance, analyzes the production and delivery processes and constraints for each product, and matches equipment start-up and shutdown time constraints. The case study shows that the model achieves a high level of matter and energy matching between the distillation process and the LAES process, maximizing the LAES peak-shaving capacity and improving system economics. During the 24 h schedule period, the total electricity consumption of NCASS increases by 18.94% during the valley electricity period and decreases by 20.59% during the flat and peak electricity period. The economic benefits increase by 9.51 k$, accounting for 14.29% of the total costs. This study contributes to the wider application of NCAS with LAES technology for sustainable energy management. [Display omitted] • A novel economic scheduling model is proposed to minimize gas production costs. • A black box model represents the conversion process of liquid air energy storage. • High-performance operation of air compressors and zero gas emission are achieved. • The time-of-day tariff is utilized to maximize profits and minimize operating costs. • Liquide air energy storage achieves around 20% power load shifting. [ABSTRACT FROM AUTHOR]