Modeling Approach Research Articles

Analyzing economic inflation's impact on food security and accessibility through econometric modeling

This study investigates the impact of economic inflation on food security and accessibility through the development of an econometric modeling approach. As inflation rates rise, the purchasing power of consumers diminishes, leading to increased food prices and potentially exacerbating food insecurity. This research aims to quantify the relationship between inflation and food security indicators, such as availability, access, utilization, and stability of food supplies. By employing time-series data and econometric techniques, the model captures the dynamic interactions between inflation rates, food prices, and socioeconomic factors affecting food security. The model incorporates key variables, including consumer price index (CPI), food inflation, income levels, and unemployment rates, to analyze their collective impact on food security across different demographics. The findings indicate that rising inflation significantly correlates with higher food prices, disproportionately affecting low-income households and vulnerable populations. This relationship highlights the necessity of understanding inflation's broader implications on food accessibility, especially in regions where food security is already a pressing issue. Future research directions are proposed, focusing on policy interventions aimed at stabilizing food prices and enhancing food security. Potential strategies include price controls, subsidies for staple foods, and targeted social safety nets for low-income households. Additionally, the study suggests further examination of supply chain factors contributing to food price volatility, such as transportation costs and global market dynamics, which can exacerbate inflation's effects on food security. This research contributes to the literature on food security by providing empirical evidence of inflation's impact on food accessibility and identifying critical areas for policy intervention. By addressing the complex interplay between inflation and food security, stakeholders, including policymakers and food industry leaders, can develop informed strategies to mitigate adverse effects and promote food security in inflationary environments.

Improving halalness and food safety management systems in the Indonesian broiler supply chain: an interpretive structural modeling and Bayesian network approach

Purpose By exploring the halalness and food safety risks from the perspective of technology and the relationship among them, this study aims to make quantitative predictions of such risks in the broiler supply chain to determine the critical control points (CCPs) in Hazard Analysis Critical Control Point (HACCP). Design/methodology/approach This study integrates Interpretive Structural Modeling (ISM) and Bayesian Network (BN) to achieve the objectives. Data were collected from focus group discussions (FGDs) with experts and direct observations at the broiler supply chain. Findings This paper identified 19 risks in the Indonesian broiler supply chain. The risk for halalness and food safety reached 30.92%, indicating that assuring halalness and food safety remains improbable or unlikely. The two CCPs of halalness and food safety are the knife’s sharpness and the vehicle’s storage temperature. Research limitations/implications This study quantifies the halalness and food safety risks in the Indonesian broiler supply chain, but it only involves one step forward and one step backward in the slaughterhouse’s chain. Practical implications The findings can provide insights for stakeholders, such as business owners, employees, management system auditors and consumers, regarding the critical control points of halalness and food safety in the broiler supply chain to improve the halalness and food safety management systems. Originality/value This study’s novelty lies in the examination of halalness and food safety risks using a risk prediction model to determine CCPs for the HACCP plan in the broiler supply chain in Indonesia.

An empirical analysis of user intention to use chatbots for airline tickets consultation

Purpose This study aims to empirically analyze the factors influencing users’ intention to use chatbots for airline ticket consultation. It seeks to introduce a comprehensive framework based on the technology acceptance model (TAM) that integrates key factors alongside traditional TAM constructs to understand what drives behavioral intention to use chatbots in the context of airline ticket consultation. Design/methodology/approach The study uses the partial least squares-structural equation modeling (PLS-SEM) approach to validate the proposed model empirically. Data were collected through a survey questionnaire distributed to potential users in Saudi Arabia, with 393 valid responses from a total of 409 received being included in the analysis. Findings The empirical analysis confirms the significance of perceived usefulness and user satisfaction as direct determinants of behavioral intention. Additionally, it reveals that factors such as perceived ubiquitous access, perceived completeness, perceived accuracy, perceived unbiased response and perceived convenience have both direct and indirect significant impacts on the behavioral intention to use chatbots for airline ticket consultation. Originality/value This research advances theoretical understanding and holds practical implications for designing and implementing effective chatbot services. By investigating the complex interplay of these factors, the study makes substantive contributions to both theoretical advancements and practical applications in the field, particularly in enhancing the user experience and acceptance of chatbots for airline ticket consultations.

Exploring young customers’ purchasing intention for solar appliances in an emerging market: evidence from structural equation modeling approach

Purpose This study aims to investigate the impact of several constructs on young customers’ consumption of solar energy appliances in an emerging market by extending the theory of planned behavior (TPB). Design/methodology/approach This study collected primary data from 885 young customers in an emerging market, that is, Vietnam. Subsequently, this study used partial least squares structural equation modeling to investigate the relationships between examined variables. Findings The results indicated that personal innovativeness, environmental knowledge and renewable energy knowledge significantly improved attitudes toward solar energy appliances. In addition, purchasing intention is promoted by subjective norms and perceived behavioral control. Contradictorily, the perceived functional risk is a significant barrier to purchasing intention. It also negatively moderates two associations: attitude and purchasing intention, attitude and positive word-of-mouth. Despite being proven to influence word-of-mouth positively, attitude has no significant impact on purchasing intention. Originality/value These findings suggested several implications for enterprises, technology providers and policymakers to develop renewable energy appliance consumption.

Optimising Malaysia’s power mix for a sustainable future: a multi-scenario modelling approach

PurposeThis study employs advanced modelling to assess the effectiveness of Malaysia’s current energy policies in achieving a low-carbon future. By optimising a 100% renewable energy mix, including energy storage, the research identifies pathways to decarbonise the power sector while minimising costs. These findings will inform the development of future policies.Design/methodology/approachThis study employs the Stockholm Environment Institute-developed Low Emissions Analysis Platform (LEAP) and Next Energy Modeling system for Optimization (NEMO) to construct and optimise a comprehensive Malaysian power sector model. The model encompasses both electricity supply, including diverse electricity generation sources and demand across key sectors. Three scenarios – existing policy, optimised existing policy and more ambitious policy (near-zero emissions) – are analysed.FindingsSolar photovoltaic (PV) is the dominant technology, but realising its full potential requires significant grid upgrades. While natural gas expansion underpins Malaysia’s decarbonisation strategy, solar and storage offer a cleaner and potentially cost-effective alternative. Rapid technological advancements in clean energy increase stranded asset risk for new gas power plants. Malaysia’s abundant bioenergy resources need more tapping. This can contribute to decarbonisation and rural development. Transitioning to a fully renewable grid necessitates substantial investments in energy storage and grid infrastructure. While falling battery costs and regional interconnection can mitigate costs, careful consideration of potential disruptions and cost fluctuations is essential for resilience.Research limitations/implicationsEnergy sector modelling results are inherently dependent on input assumptions, such as future technology costs, resource availability and fossil fuel prices. These factors can be highly uncertain. While this study did not conduct sensitivity analyses to explore how variations in these assumptions might affect the results (e.g. cost variations across scenarios, technology mix fluctuations), the core findings provide valuable insights into potential decarbonisation pathways for Malaysia’s power sector. Future studies could build upon this work by incorporating sensitivity analyses to provide a more comprehensive understanding of how key results might change under a wider range of future possibilities.Originality/valueThis study co-optimises a 100% renewable energy mix for Malaysia, incorporating a comprehensive range of renewable resources, battery and pumped hydro storage. The research also provides a unique perspective on the interplay of philosophical underpinnings, psychological maturity and energy policy.

A strategy to what end? “The strategy of model building in population biology” in its programmatic context

Abstract“The Strategy of Model Building in Population Biology” published by Richard Levins in 1966 has been cited over 2500 times. For a paper concerned with modeling approaches in population biology a surprisingly large part of the attention. The Strategy received comes from history and philosophy of biology, and specifically from accounts on model and model formulation. The Strategy is an unusual paper; it presents neither new data nor a new formal model; at times it reads like a manifesto for some modeling approach, without specifying which broader program that approach intends to support. When these peculiarities of The Strategy are even mentioned, the philosophical literature tends to explain them away by invoking Levins’ Marxist commitments. In contrast, I argue that those peculiarities can be explained by examining the programmatic purpose of the paper; starting from his doctoral work, Levins was trying to establish a research program meant to account for the relations between fitness and environment in different terms than the prevalent lock-and-key view. My paper brings that program back to the discussion, explains its relation to competing approaches and examines Levins’ approach to modeling in light of that context

Unveiling Groundwater Potential in Hangu District, Pakistan: A GIS-Driven Bivariate Modeling and Remote Sensing Approach for Achieving SDGs

Sustainable groundwater development stands out as a contemporary concern for growing global populations, particularly in stressed riverine arid and semi-arid regions. This study integrated satellite-based (Sentinel-2, ALOS-DEM, and CHIRPS rainfall) data with ancillary lithology and infrastructure datasets using Weight of Evidence (WoE) and Frequency Ratio (FR) models to delineate Groundwater Potential Zones (GWPZs) in the Hangu District, a hydrologically stressed riverine region in northern Pakistan, to support the Sustainable Development Goals (SDGs). Ten key variables, including elevation, slope, aspect, distance to drainage (DD), rainfall, land use/land cover, Normalized Difference Vegetation Index, lithology, and road proximity, were incorporated into the Geographic information system (GIS) environment. The FR model outperformed the WoE model, achieving success and prediction rates of 89% and 93%, compared to 82% and 86%. The GWPZs-FR model identified 23% (317 km2) as high potential, located in highly fractured pediment fans below 550 m, with gentle slopes (<5 degrees), DD (within 200 m), and high rainfall in areas of natural trees and vegetation on valley terrace deposits. The research findings significantly support multiple SDGs, with estimated achievement potentials of 37.5% for SDG 6 (Clean Water and Sanitation), 20% for SDG 13 (Climate Action), 15% for SDG 8 (Decent Work and Economic Growth), 12.5% for SDG 9 (Industry, Innovation, and Infrastructure), and notable contributions of 10% for SDG 2 and 5% for SDG 3. This approach provides valuable insights for policymakers, offering a framework for managing groundwater resources and advancing sustainable practices in similar hydrologically stressed regions.

Case study of adjacent integral bridges supported on continuous secant piled walls

Integral bridges are often the preferred way of construction for short and medium span bridges in the UK. However, the behaviour of integral bridges is influenced by complex soil-structure interaction behaviour that may be cumbersome to predict and analyse when dealing with unusual structural arrangements. This paper presents a case study for the design of two single span bridges carrying a roundabout over a dual carriageway, supported on continuous secant piled walls. One of the bridges is fully integral while the adjacent structure is articulated at one end due to its skew. An alternative detail for the articulated end is proposed, to eliminate soil pressures and settlements at the back of the abutments as well as reduce the risk of water ingress to the bearings. The complex nature of the structural arrangement presented analytical challenges, that were solved by developing an advanced modelling approach, exploring two proposals. The first is to evaluate the geotechnical model for a range of imposed top of abutment displacements from the onset. The second, using unique non-linear springs and derived P-Y curves describes the more realistic variable nature of soil-structure interaction over the length of the walls leading to reduced soil pressures enhancing design feasibility.

Competing with Theories: Using Awareness and Confidence to Secure Resources and Rents

An assumption of factor market efficiency is often used to grant primacy to firms’ existing unique and valuable resources as the source of economic rents. But this assumption is difficult to reconcile with observed market outcomes. For instance, five of the six companies with the highest global market capitalization in 2022 were upstarts in their industries with few resources at their origins. More surprising, three of these entrants were assisted by incumbents with vastly superior resources in assembling the resources they required. In this paper we explore how entrants compete with theories to secure resources from incumbents and capture rents. We introduce a modeling approach in which theories with causal logic generate awareness of valuable potential future states and shape the beliefs about payoffs and probabilities associated with these states. We combine work in the theory-based view and value capture theory to distinguish among three distinct sources of economic rents that are potentially available to entrants: awareness rents, confidence rents, and resource rents. We explore the circumstances under which these three types of rents are available. By exploring the role of theories and awareness in value creation and capture, our paper seeks to deepen our understanding of how entrants both attract resources and secure rents.

Implications of Asymptomatic Carriers for Tuberculosis Transmission and Control in Thailand: A Modelling Approach

Tuberculosis (TB) is a regional and global bacterial illness that has been expanding and affecting individuals in every generation. An unknown percentage of asymptomatic hosts have TB, and the infection can spread while exhibiting no symptoms. These asymptomatic TB carriers, who contribute to the spread of the illness yet go mostly undetected, may make it more difficult to prevent transmission. In this study, we utilized the concept of symmetry to construct a manageable disease modelling framework for TB transmission and control. We developed a TB model to investigate the potential influence of asymptomatic carriers, symptomatic infections, and the entirety of TB prevalence on different approaches to treatment and prevention in Thailand. Annual TB incidence data from Thailand from 2000 to 2022 were used to calibrate the model parameters. We assessed the potential for reaching conflicting results about the management and spread of tuberculosis in Thailand. Our results showed that some TB strategies that were thought to be effective in reducing transmission may have the opposite impact, or that an intervention’s effectiveness might be overestimated, making it seem unfeasible in certain scenarios. For example, the objective of TB treatment, which attempts to decrease the occurrence of symptomatic TB infections, is to decrease the TB infection and propagation rates if the relative carrier (η) is less than one. Nonetheless, our results indicate that this strategy may increase the frequency of asymptomatic TB patients, symptomatic TB viral infections, and overall TB prevalence if η has been sufficiently understated. We also found that reducing only the progression rate of symptomatic TB infections cannot stop asymptomatic TB carriers and total TB prevalence, even when the relative infection of carriers (η) is less than unity. Our research provides a better understanding of the role of asymptomatic patients in spreading TB and highlights the need to accurately include bearers in models that guide Thailand’s TB control strategy.

Framework for urban flood risk assessment – a hydrological modelling approach: the case of Nilambur, Kerala

Framework for urban flood risk assessment – a hydrological modelling approach: the case of Nilambur, Kerala

Do network externalities and perceived gratifications boost WeChat continued use? Combining perspectives of network externalities and uses and gratifications.

Rapid burgeoning of mobile social media has become the primary channel by which individuals construct interpersonal networks and contact with each other recently. The primary objectives of this study are to explore how and whether network externalities would enhance WeChat users' distinct types of perceived gratifications, and how such perception of gratifications subsequently impacts their attitudes and continuous usage behavior. This article utilized a structured web-based survey questionnaire to conduct empirical research, and gathered and analyzed data of 788 WeChat users by structural equation modeling (SEM) approach. Perceived gratifications are categorized into three dimensions: hedonic gratifications, social gratifications, and utilitarian gratifications. Obtained outcomes reveal that both referent network size and perceived complementarity are positively and significantly associated with all three dimensions of perceived gratifications. Additionally, hedonic gratifications, social gratifications, and utilitarian gratifications are positively related to users' attitudes toward WeChat, which, in turn, are significantly correlated with their continuous usage behavior. These findings contribute to the growing body of literature on WeChat user behavior, offering novel theoretical insights for academics and practical implications for mobile social media operators.

The triple-helix model as foundation of innovative entrepreneurial ecosystems

Purpose Recommend ways to increase the entrepreneurial performance score for city-centered entrepreneurial ecosystems (EES) and the possible role within the triplex helix concept. The former applies to lower-ranked EESs. For the latter, the authors hypothesize that the standard triple helix model of counting on some existing, well known multi-party interest in bringing together businesses and other stakeholders (especially universities and government) is insufficient. Including more players and alternative cooperation models may truly enable a long lasting productive interplay of cooperative and competitive forces leading to genuinely innovative (non-marginal, non-opportunistic) businesses and also to more regional well-being. This study aims at leveraging the city-based view on entrepreneurial ecosystems, to enable new ways of boosting the functionality of triple-helix minded programs, especially so for emerging economies and their cross-border regions. Design/methodology/approach Methodology is dual: (1) paying tribute to the history of entrepreneurial behavior and reviewing the diverse sources of support (institutional and otherwise), eventually leading to today’s concentrations of successful innovative business, and (2) analyzing modern data on performance of city-centered EESs. Putting emphasis on path-dependence (meaning that history matters) the authors analyze data distributions of measures concerning city-centered EESs and also nation-wide entrepreneurial aggregates, searching signs of long-tail statistic, an indicator of path dependence. Furthermore the authors statistically analyze if and to what extend, key university performance indices translate into successful EESs. From these results, recommendation follow. Findings Historical developments and cultural backgrounds of different countries lead to different ways of support for new ideas and approaches. Entrepreneurship success is path-dependent and there are entrepreneurial approaches more easy – but others way more difficult – to imitate (e.g. “Hidden Champions”). Statistical analysis of entrepreneurial performance data confirms power law decay, which confirms the action of path-depend processes. Statistical models show that university performance is just weakly influencing entrepreneurial success. This leads to proposing a new, polycentric approach for organizing robust cooperation between the stakeholders, potentially capable of lifting low-score EESs into a more productive regime. Research limitations/implications Research limitation primarily concern data availability, as potentially useful information is not publicly available. The findings lead to further questions, and to questioning too optimistic expectations about cooperation readiness of the implied triple helix stakeholders. As pointed out repeatedly, other important players are non-university research organizations with more focused goals (national labs, etc.), which should be explicitly accounted for. Another directions is distinguishing between support for (a) short-term high-tech, and for (b) longer term, deep-tech entrepreneurs. The latter may require new evaluation techniques and specially tailored private-public partnerships. Finally, polycentric and polycentric cross-border cooperation requires more research into networked organizations. Practical implications Triple-helix based, cooperative agreements should rethink the effective functionality of EESs. City-centered, EESs tend to be most expressive in their projects but also subject to a stronger long tail-effect. This implies “success-breads-success” for the front-runners, enjoying very low ranking mobility. Lower-positioned EESs may profit from the mobility within this score region. However, the still lower positioned ones face strong downward rank mobility, implying that special effort (support) is needed. The authors’ proposal of polycentric cooperation, especially the cross-border variant, would credibly enable such support by bringing in both, more players and more levels of play, helping robust networking. Social implications This research has potentially profound social implications. Acknowledging the path-dependence of intellectual capital formation and emergence of entrepreneurial spirit in the modern sense helps to understand which techno-entrepreneurial endeavors would have increased chance of success of being brought up in the respective EES. It is also useful to identify the oversold (over-hyped) entrepreneurial projects. Concerning the cross-border polycentric organizations harboring EESs one may have to concede that national borders are sub-optimal, at least with regard to lifting up the entrepreneurial reputation of border-adjacent regions. Implicitly, opportunistic and marginal entrepreneurship (e.g. in Eastern Europe) would reduce. Originality/value This research claims originality for combining a qualitative-historical approach with a statistical modeling approach, which can explain the dynamic nature of the involved entrepreneurial processes (long-tails). While the historical approach is deemed to be necessary for understanding the reasons for the large differences in entrepreneurial success across nations and regions, the statistical modeling is helping to identify lower-score intervals within the entrepreneurial score hierarchy which are more easy, or, alternatively, very hard to escape. This in turn leads to adapted recommendations and mobilizing special efforts for creating new, potentially robust, cooperative arrangements beyond the triple-helix concept.

Harnessing AI for advancing pathogenic microbiology: a bibliometric and topic modeling approach

IntroductionThe integration of artificial intelligence (AI) in pathogenic microbiology has accelerated research and innovation. This study aims to explore the evolution and trends of AI applications in this domain, providing insights into how AI is transforming research and practice in pathogenic microbiology.MethodsWe employed bibliometric analysis and topic modeling to examine 27,420 publications from the Web of Science Core Collection, covering the period from 2010 to 2024. These methods enabled us to identify key trends, research areas, and the geographical distribution of research efforts.ResultsSince 2016, there has been an exponential increase in AI-related publications, with significant contributions from China and the USA. Our analysis identified eight major AI application areas: pathogen detection, antibiotic resistance prediction, transmission modeling, genomic analysis, therapeutic optimization, ecological profiling, vaccine development, and data management systems. Notably, we found significant lexical overlaps between these areas, especially between drug resistance and vaccine development, suggesting an interconnected research landscape.DiscussionAI is increasingly moving from laboratory research to clinical applications, enhancing hospital operations and public health strategies. It plays a vital role in optimizing pathogen detection, improving diagnostic speed, treatment efficacy, and disease control, particularly through advancements in rapid antibiotic susceptibility testing and COVID-19 vaccine development. This study highlights the current status, progress, and challenges of AI in pathogenic microbiology, guiding future research directions, resource allocation, and policy-making.

Multi-scale finite element simulation of needle-punched quartz fiber reinforced composites

Abstract To investigate the effects of different needling parameters on the mechanical properties of quartz needled felts and their composites, this paper proposes a multi-scale modeling approach to simulate and calculate the mechanical properties of needled quartz fiber-reinforced composites. Firstly, based on the characteristics of needle-punching technology, the morphology of needle-punched composites was analyzed at a microscopic scale, and the quartz fiber structure was divided into three typical representative regions. Then, a periodic single-cell model of needled composites was established. Meanwhile, this article also analyzes the influence of parameters such as needling density, needle type, and needling depth on the mechanical properties of needled composites.

Linking demand conditions to competitive advantage: the role of government support programs in the halal cosmetic and personal care industry

Purpose This study aims to examine the mediating role of government support programs in the halal cosmetics and personal care industry between local demand conditions and competitive advantage. Design/methodology/approach Data were collected from 96 companies in the cosmetics and personal care industry in Malaysia, and the analysis was conducted using the partial least squares structural equation modeling approach. Findings The results indicate that demand conditions do not have a direct effect on competitive advantage in the halal cosmetics and personal care industry. However, government support programs, specifically regulatory and innovation programs, play a crucial mediating role between demand conditions and competitive advantage. This highlights the importance of both regulatory and innovation programs in shaping the halal market ecosystem. Practical implications The halal industry policy should prioritize innovation and regulatory programs to ensure that nonfood halal products, including beauty products, are evaluated not only based on ingredient content but also on broader aspects such as product effectiveness, quality, safety and affordability. Originality/value This study offers a unique perspective by highlighting the often-overlooked role of government support programs as key drivers in shaping the halal market ecosystem and enhancing competition in the halal cosmetics and personal care industry. While the government’s role is frequently neglected in market dynamics, this research emphasizes how government intervention, when implemented through effective policy, can significantly contribute to industry growth and competitiveness.

Willingness to pay of Portuguese sparkling wine consumers: Econometric and machine learning approaches

Abstract Understanding consumer choices and their drivers of willingness to pay (WTP) for a bottle of wine has been a research challenge in wine economics, particularly in niche markets such as sparkling wine. This study investigates the determinants of WTP for sparkling wine based on data from Portuguese consumers. The results provided by two alternative methodologies are compared: a traditional econometric model, based on the estimation of an ordered probit model; and a modelling approach based on data-driven and using machine learning algorithms. Both approaches present similar results, highlighting the relevance of some determinants including income, Champagne brand, not being a protected designation of origin and being a red wine consumer as main predictors of WTP for sparkling wine in Portugal.

Driving Digital Transformation: The Impact of SME Digitalization on Technology Acceptance and Usage in Small and Medium Enterprises of Yemen

This research investigates the relationships between digitalization, perceived usefulness, attitudes toward using technology, and actual system use of technologies within the context of small and medium-sized enterprises (SMEs) in Yemen. Using a two-step structural equation modelling approach, the research investigates both direct and mediating effects. Data were gathered from 392 SMEs in Yemen by employing a survey research design. The measurement model was estimated to evaluate the constructs' accuracy, while the structural model was analyzed to investigate the proposed relationships. Findings reveal that SME digitalization significantly enhances perceived usefulness, which positively influences users' attitudes toward technology adoption and subsequently drives actual system use. Specifically, the analysis shows that improvements in digitalization practices lead to heightened perceptions of usefulness and favorable attitudes, ultimately resulting in increased actual system use. Moreover, the results indicate that perceived usefulness and attitudes serve as significant mediators between digitalization and system use. This research contributes to understanding how enhancing perceived usefulness and fostering positive attitudes can facilitate technology adoption in SMEs, providing important implications for practitioners, policymakers, and researchers focused on digital transformation. Overall, the findings emphasize the importance of strategic digitalization efforts to improve operational efficiency and promote successful technology acceptance in small and medium enterprises.

Viscoelastic negative stiffness metamaterial with multistage load bearing and programmable energy absorption ability

ABSTRACT The mechanical properties of negative stiffness (NS) metamaterial could be customized and tuned in a wide range for various requirements, achieving programmable performances by the design from the aspect of structure and material. This work investigates the viscoelastic NS metamaterial based on double curved beams using a combined approach of experiments, simulations, and analytical modeling with an emphasis on multistage loading bearing and programmable energy absorption ability. Numerical simulations are first implemented based on the finite element models of three types of metamaterial cells, which provide comparisons of load bearing and energy absorption properties. Further, the effects of geometric parameters of multistage metamaterial element and the mechanisms are analyzed. An analytical discrete model is then innovatively developed to provide straightforward understandings of the geometric effects and reveal the role of viscoelasticity by examining the instantaneous loading responses and rate-dependent behaviors. Experimentally, we fabricate the metamaterial samples using 3D-printing technique and perform compression tests to validate the properties based on different boundary conditions, loading rates and cyclic loading and unloading. Results of this work show the potential of wide programmable room for mechanical properties through structure and functional material design, such as multistage load bearing capacity and energy absorption ability.

Threshold Modeling for Antibiotic Stewardship in Oman.

Antimicrobial stewardship supports rational antibiotic use. However, balancing access to antibiotic treatment while controlling resistance is challenging. This research used a threshold logistic modelling approach to identify targets for antibiotic usage associated with carbapenem-resistant Acinetobacter baumannii (CRAb), carbapenem-resistant Klebsiella pneumonia (CRKP), and extended-spectrum β-lactamases- producing Escherichia coli (ESBL-producing E. coli) incidence in hospitals. This study utilises an ecological population-level design. Monthly pathogen cases and antibiotic use were retrospectively determined for inpatients between January 2015 and December 2023. The hospital pharmacy and microbiology information systems were used to obtain this data. Thresholds were identified by applying nonlinear modelling and logistic regression. Incidence rates of 0.199, 0.175, and 0.146 cases/100 occupied bed-days (OBD) for CRAb, CRKP, and ESBL-producing E. coli, respectively, were determined as the cutoff values for high (critical) incidence rates. Thresholds for aminoglycosides (0.59 defined daily dose (DDD)/100 OBD), carbapenems (6.31 DDD/100 OBD), piperacillin-tazobactam (3.71 DDD/100 OBD), third-generation cephalosporins (3.71 DDD/100 OBD), and fluoroquinolones (1.91 DDD/100 OBD), were identified. Exceeding these thresholds would accelerate the gram-negative pathogens' incidence rate above the critical incidence levels. Employing the threshold logistic approach enabled near real-time performance monitoring feedback, risk scores and alert signals for when the incidence of the selected pathogens are entering critical levels. Threshold logistic models can help inform and implement effective antimicrobial stewardship interventions to manage resistance within hospital settings.