Exponential Growth Research Articles

Fractional-order crime propagation model: a comparison between logistic and exponential growth

Fractional-order crime propagation model: a comparison between logistic and exponential growth

Nuclear medicine imaging in non-seminomatous germ cell tumors: lessons learned from the past failures

AbstractThere is an unmet need for a more accurate molecular imaging radiotracer in the field of non-seminomatous germ cell tumors (NSGCT). The clinical problem is that no single imaging modality is able to differentiate teratoma from necrotic tissue in NSGCTs, which the nuclear medicine techniques are no exception. The exponential growth in the list of potentially promising radiotracers may hold promise in the future for imaging of NSGCTs. Here, we have reviewed the past efforts and potential future advances in this field.

Cost‐Effective DNA Storage System with DNA Movable Type

AbstractIn the face of exponential data growth, DNA‐based storage offers a promising solution for preserving big data. However, most existing DNA storage methods, akin to traditional block printing, require costly chemical synthesis for each individual data file, adopting a sequential, one‐time‐use synthesis approach. To overcome these limitations, a novel, cost‐effective “DNA‐movable‐type storage” system, inspired by movable type printing, is introduced. This system utilizes prefabricated DNA movable types‐short, double‐stranded DNA oligonucleotides encoding specific payload, address, and checksum data. These DNA‐MTs are enzymatically ligated/assembled into cohesive sequences, termed “DNA movable type blocks,” streamlining the assembly process with the automated BISHENG‐1 DNA‐MT inkjet printer. Using BISHENG‐1, 43.7 KB of data files are successfully printed, assembled, stored, and accurately retrieved in diverse formats (text, image, audio, and video) in vitro and in vivo, using only 350 DNA‐MTs. Notably, each DNA‐MT, synthesized once (2 OD), can be used up to 10000 times, reducing costs to $122/MB—outperforming existing DNA storage methods. This innovation circumvents the need to synthesize entire DNA sequences encoding files from scratch, offering significant cost and efficiency advantages. Furthermore, it has considerable untapped potential to advance a robust DNA storage system, better meeting the extensive data storage demands of the big‐data era.

The influence of students’ personality traits and their parents’ parenting style on Romanian students’ performance in science subjects from secondary to doctoral level

ABSTRACT With the exponential growth of technological innovation, new positions in science, technology, engineering, and mathematics (STEM) are emerging. Employees face new job demands, requiring more technical and mathematical capabilities than before. Educating the population in science subjects is becoming increasingly important, as is making science subjects available to students and identifying factors influencing the development of logical thinking, the basis of STEM subjects. This paper focuses on identifying significant relationships between students’ personality traits, their parents’ parenting style and students’ performance in STEM subjects in high school and college, within Urie Bronfenbrenner’s ecological systems framework. Using a questionnaire with standardized constructs, we surveyed Romanian students from a technical university and found that certain personality traits and parenting styles are significant mainly for the student’s performance in STEM subjects in high school, and these significant relationships differ for female students, compared to male students, possibly as a result of local cultural gender views. Our society aims to increase the participation of general public and female students in STEM majors and jobs, and our study informs the audience on how a student’s microsystem can nurture or hinder the development of logical thinking, as the basis of cognitive skills and performance in STEM fields.

Toxicological assessment of the effects of CuCl2 and CuO nanoparticles on early developmental stages of the South American toad, Rhinella arenarum by standardized bioassays.

The release in aquatic environments of emergent contaminants such as copper oxide nanoparticles (CuO-NPs) has generated concerns on their short- and long-term toxicity and the potential risk for more vulnerable animal groups, such as amphibians. In this sense, the aim of this work was to evaluate the toxicity of CuO-NPs in comparison with its respective salt (CuCl2) in embryos and larvae of a native amphibian, Rhinella arenarum, by acute (96h) and chronic (504h) standardized bioassays. Lethality and sublethal effects such as developmental, morphological, and ethological alterations were assessed in a wide range of concentrations (0.001-100mg/L). Neurotoxic effects by acetyl (AChE) and butyrylcholinesterase (BChE) activity levels and changes in the lipid content were also assessed at sublethal concentrations. Results showed that CuCl2 caused higher lethality than CuO-NPs in both developmental periods. Embryos were more sensitive than larvae with LC50-96h = 0.080mg CuCl2/L and 1.26mg CuO-NPs/L and 0.21mg CuCl2/L and 20.17mg CuO-NPs/L, respectively. At acute exposure, embryos exhibited several developmental abnormalities such as developmental delay, edema, axial flexure, and microcephaly. Larvae presented spasmodic contractions and weak movements. Regarding neurotoxicity, a significant increase in AChE activity at low concentrations as well as an inhibition of BChE activity at all tested concentrations was evidenced for both substances at acute exposure. Moreover, an increment in phospholipid and triglyceride levels was observed at the highest concentration of CuO-NPs (10mg/L) at chronic exposure. The chromatographic separation of lipids showed no apparent differences in acylglycerols and free fatty acid bands, between the treatments and the control. The differences in toxicity between CuO-NPs and CuCl2 could be due to structural and physicochemical characteristics that influence their bioavailability and toxicity. Considering the exponential growth in the production and use of these substances, it is expected that the levels of contamination will rise considerably in the future, so that wildlife, particularly aquatic organisms, will be more increasingly exposed, representing a potential risk for their populations.

Subsampling Algorithms for Irregularly Spaced Autoregressive Models

With the exponential growth of data across diverse fields, applying conventional statistical methods directly to large-scale datasets has become computationally infeasible. To overcome this challenge, subsampling algorithms are widely used to perform statistical analyses on smaller, more manageable subsets of the data. The effectiveness of these methods depends on their ability to identify and select data points that improve the estimation efficiency according to some optimality criteria. While much of the existing research has focused on subsampling techniques for independent data, there is considerable potential for developing methods tailored to dependent data, particularly in time-dependent contexts. In this study, we extend subsampling techniques to irregularly spaced time series data which are modeled by irregularly spaced autoregressive models. We present frameworks for various subsampling approaches, including optimal subsampling under A-optimality, information-based optimal subdata selection, and sequential thinning on streaming data. These methods use A-optimality or D-optimality criteria to assess the usefulness of each data point and prioritize the inclusion of the most informative ones. We then assess the performance of these subsampling methods using numerical simulations, providing insights into their suitability and effectiveness for handling irregularly spaced long time series. Numerical results show that our algorithms have promising performance. Their estimation efficiency can be ten times as high as that of the uniform sampling estimator. They also significantly reduce the computational time and can be up to forty times faster than the full-data estimator.

Drivers of brand love for organic wine brands: moderating role of ethnocentrism

PurposeThe consumption of organic wine has witnessed exponential growth, mainly because of changing lifestyles, rising disposable income, modernity aspects and claimed health benefits. Understanding the motivations and attributes affecting organic wine consumption (OWC) provides a limited perspective on consumption and behavioral patterns.Design/methodology/approachThis study used a set of screening criteria to arrive at the final choice of fine-dining restaurants and bars that serve wine in their outlets. Based on the selected locations, we gathered responses from 558 consumers aged 18 years and above with prior experience of buying organic and non-organic wine. The hypothesized model was validated using covariance-based structural equation modeling (CB-SEM). From the perspective of organic wine consumption, the research findings exhibit significant links between the drivers.FindingsThe findings underscore the moderating impact of ethnocentrism toward shaping consumers’ attitudes and brand love. Additionally, gender and consumption frequency indicated significant variations among consumers of organic wine. Female consumers strongly believe that consumption of organic wine provides health benefits, societal acceptance and moments of joy. Additionally, men usually associate wine consumption with enhanced their affective, convivial and sensory pleasure.Originality/valueThis study examines the drivers and marketing outcomes of organic wine consumption using Behavioral Reasoning Theory (BRT) and the Theory of Hedonic Asymmetry (THA).

Is driving an electric two-wheeler (E2W) safe? Analysing safety risk factors of E2W considering the quality and reliability criteria

PurposeThe purpose of this research is to identify and analyse the perceived risk factors affecting the safety of electric two-wheeler (E2W) riders in urban areas. Given the exponential growth of the global E2W market and the notable challenges offered by E2W vehicles as compared to electric cars, the study aims to propose a managerial framework, to increase the penetration of E2W in the emerging market, as a reliable, and sustainable mobility alternative.Design/methodology/approachThe perceived risk factors of riding E2Ws are relatively scanty, especially in the context of emerging economies. A mixed-method research design is adopted to achieve the research objectives. Four expert groups are interviewed to identify crucial safety risk E2W factors. The grey-Delphi technique is used to confirm the applicability of the extracted risk factors in the Indian context. Next, the Grey-Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique is employed to reveal the causal-prominence relationship among the perceived risk factors. The dominance and prominence scores are used to perform Cause and Effect analysis and estimate the triggering risk factors.FindingsThe finding of the study suggests that reckless adventurism, adverse road conditions, individual characteristics and distraction caused by using mobile phones, as the topmost triggering risk factors that impact the safety of E2Ws drivers. Similarly, reliability on battery performance low velocity and heavy traffic conditions are found to be some of the critical safety factors.Practical implicationsE2Ws are anticipated to represent the future of sustainable mobility in emerging nations. While they provide convenient and quick transportation for daily urban commutes, certain risk factors are contributing to increased accident rates. This research analyses these risk factors to offer a comprehensive view of driver and rider safety. Unlike conventional measures, it considers subjective quality and reliability parameters, such as battery performance and reckless adventurism. Identifying the most significant causal risk factors helps policymakers focus on the most prominent issues, thereby enhancing the adoption of E2Ws in emerging markets.Originality/valueWe have proposed an integrated framework that uses grey theory with Delphi and DEMATEL to analyse the safety risk factors of driving E2W vehicles considering the uncertainty. In addition, the amalgamation of Delphi and DEMATEL helps not only to identify the pertinent safety risk factors, but also bifurcate them into cause-and-effect groups considering the mutual relationship between them. The framework will enable practitioners and policymakers to design preventive strategies to minimize risk and boost the penetration of E2Ws in an emerging country, like India.

Delivery Methods of Radiopharmaceuticals: Exploring Global Strategies to Minimize Occupational Radiation Exposure.

In the world of nuclear medicine, health care professionals face the challenge of safeguarding themselves and their patients from occupational radiation exposure. As the field experiences exponential growth, driven by the surge in approvals of radiopharmaceuticals for diagnostic and therapeutic applications, it becomes vital to delve into the delivery methods of radiopharmaceuticals. Health care professionals take precautions during radiopharmaceutical administration, including maintaining distance from radioactive sources, using shielding, limiting exposure time, and monitoring radiation levels with badges. Regular evaluations provide compliance with recommended exposure limits, yet concerns persist, especially regarding the cumulative radiation exposure from manual injections over time. Understanding the long-term effects of radiation exposure has spurred the development of cutting-edge medical device technologies, such as autoinjectors, designed to administer radiopharmaceuticals accurately while minimizing total radiation dose to health care professionals. The U.S. Pharmacopeia 825 regulation refers to these devices as "direct infusion systems." Nuclear medicine technologists commonly refer to them as "autoinjectors," whereas device manufacturers may use terms such as injection system, radiopharmaceutical injector, or infusion system. Despite variations in terminology, these devices hold a pivotal role in shaping the future of radiopharmaceutical delivery. In an era of escalating demand for PET procedures worldwide, skilled health care professionals ensure the safe and precise dosing of radiopharmaceuticals. This article explores the state-of-the-art medical devices in radiopharmaceutical delivery, spotlighting transformative medical devices currently revolutionizing the nuclear medicine landscape in the global market.

Anomaly Detection and Analysis in Nuclear Power Plants

Industries are increasingly adopting digital systems to improve control and accessibility by providing real-time monitoring and early alerts for potential issues. While digital transformation fuels exponential growth, it exposes these industries to cyberattacks. For critical sectors such as nuclear power plants, a cyberattack not only risks damaging the facility but also endangers human lives. In today’s digital world, enormous amounts of data are generated, and the analysis of these data can help ensure effectiveness, including security. In this study, we analyzed the data using a deep learning model for early detection of abnormal behavior. We first examined the Asherah Nuclear Power Plant simulator by initiating three different cyberattacks, each targeting a different system, thereby collecting and analyzing data from the simulator. Second, a Bi-LSTM model was used to detect anomalies in the simulator, which detected it before the plant’s protection system was activated in response to a threat. Finally, we applied explainable AI (XAI) to acquire insight into how distinctive features contribute to the detection of anomalies. XAI provides valuable explanations of model behavior by revealing how specific features influence anomaly detection during attacks. This research proposes an effective anomaly detection technique and interpretability to better understand counter-cyber threats in critical industries, such as nuclear plants.

A Proposed School for Traditional Building Arts & Crafts in Kalongo, Uganda

Uganda is headed for exponential growth both in its population and in its building stock. The buildings of small Ugandan market communities such as Kalongo, a remote village in the north, reflect two distinct construction systems, as contemporary building practices have turned their back on tradition. Interventions by foreign NGOs in the area have contributed to the stigmatization of local building traditions as representing underdevelopment. This proposed design project for a School for Traditional Building Arts & Crafts in Kalongo seeks to bridge the disconnect between building traditions and the growing requirement for durable, sustainable buildings. The proposal sets out the concept of an innovative way of building through the elevation of local materials and traditions on a new scale.

Ester-Modified Sodium Silicate Grout Material for Moraine Stabilization: Synthesis and Freeze-Thaw Resistance

To achieve effective consolidation of fine particles in moraine and enhance the freeze-thaw resistance of the consolidated body, this study developed a novel grouting material using sodium silicate, lipid-based curing agents, and acidic catalysts. The gelation time and rheological properties of this material were tested. The freeze-thaw resistance was studied through changes in uniaxial compressive strength (UCS) after freeze-thaw cycles, while the consolidation mechanism was analyzed using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The experimental results indicate that the material’s gelation time can be controlled between 30s and 1600s, with an initial viscosity ranging from 5.9 to 9.8 mPa·s. Predictive models for these two indicators were established, and variance analysis revealed the influence ranking for gelation time: phosphoric acid dosage had the greatest effect, followed by EGDA content, with the Baume degree of sodium silicate having the least effect. The initial viscosity positively correlated with the Baume degree of sodium silicate and exhibited exponential growth over time. EGDA addition enhanced UCS by over 450%, reaching 1.2 MPa. During freeze-thaw cycles, strength degradation of the consolidated body was reduced by 10% to 30%. Microstructural tests showed that EGDA promotes silica gel formation and creates a network structure with unreacted sodium silicate, forming a dense consolidated body with moraine fine particles, thereby enhancing freeze-thaw resistance. These findings provide design references and theoretical support for moraine grouting in cold regions.

The econophysical model of innovation diffusion

Analysis and evaluation of innovation efficiency require the development of tools to model their dissemination process within the industry. This paper presents a model of innovation diffusion based on physical approaches, describing stages of accelerating and decelerating growth. An exponential growth is described using a diffusion model, while a logarithmic one employs an electrical engineering model. The paper presents the correspondence of physical parameters with their economic counterpart: size of a company; characteristic of speed of information exchange between firms; company’s willingness to innovate; inter-firm influence and the breakthrough level of innovation. The theoretical model obtained was tested on historical data of innovation implementation in the fuel and energy complex, followed by adjustments of coefficients depending on the branch of innovation implementation. The developed model is applicable for describing the process of innovation dissemination in any industry in the country, as well as for investment and business planning in companies and decision-making on investments in innovation projects. When applied in industries with low levels of innovation activity, an increase in the level of high-tech production and the share of organizations implementing technological innovations is predicted. Using the example of Russia’s fuel and energy sector, rising in the technological level of enterprises and a decrease in import dependence are forecasted.

Bibliometric Insights into Microplastic Pollution in Freshwater Ecosystems

Microplastic pollution in freshwater ecosystems has emerged as a significant environmental concern, warranting comprehensive investigation, and understanding. This study employs bibliometric analysis to systematically review and synthesize the existing literature on microplastic pollution in freshwater environments from 2013 to 2023. The exponential growth in research output was uncovered by analyzing 885 documents sourced from the Web of Science database, with an average annual growth rate of 73.13% and an average document citation of 30.17. Our findings highlight the dominance of primary and secondary microplastics as pollutants, their ecological consequences, and the resultant socio-economic implications. Notably, the Science of the Total Environment and Environmental Pollution journals emerge as leading publication venues, while China, Germany, and the USA lead in research contributions, underlining the global nature of microplastic pollution research. The analysis further outlines the most commonly cited works, identifying pivotal studies that have shaped current understanding and future research directions. This bibliometric analysis provides a comprehensive overview of the research landscape on microplastic pollution in freshwater ecosystems, helping researchers to identify knowledge gaps and emerging trends. These insights can guide future research directions and inform policymakers and stakeholders on where scientific efforts should be concentrated to better understand and address the impacts of microplastic pollution.

Crowd-sourced trait data can be used to delimit global biomes

Abstract. Terrestrial biomes and their biogeographic patterns have been derived from a large variety of variables including species distributions and bioclimate or remote sensing products. However, classifying the biosphere into biomes from a functional perspective using biophysical traits has rarely been tested. Such a trait-based biome classification has been limited by data availability. Here, we aimed to exploit crowd-sourced plant observations and trait databases to systematically assess which traits are most suitable for biome classification. We derived global patterns of 33 biophysical traits covering around 50 % of the land surface by combining crowd-sourced species distribution data from the Global Biodiversity Information Facility (GBIF) and trait observations from the TRY database. Using these trait maps as predictors for supervised cluster analyses, we tested to what extent we can reconstruct 31 published biome maps. A sensitivity analysis with randomly sampled combinations of traits was performed to identify the traits that are most appropriate for biome classification. Performance was quantified by comparing modeled biome maps and the respective observation-based biome maps. Finally, spatial gaps in the resulting biome maps were filled using species distribution models to obtain continuous global biome maps. We showed that traits can be used for biome classification and that the most appropriate traits are conduit density; rooting depth; height; and different leaf traits, including specific leaf area and leaf nitrogen content. The best performance of the biome classification was obtained for biome maps based on biogeographic zonation and species distributions, in contrast to biome maps derived from optical reflectance. The availability of crowd-sourced plant observations is heterogeneous, and, despite its exponential growth, large data gaps are prevalent. Nonetheless, it was possible to derive biome classification schemes from these data to predict global biome patterns with good agreement. Therefore, our analysis is a valuable approach towards understanding biome patterns based on biophysical traits and associated ecological strategies.

Lymph Node Metastasis of Head and Neck Cancer: A Bibliometric Analysis From 2000 to 2022.

Lymph node metastasis (LNM) is a significant prognostic factor in head and neck cancer (HNC) patients. To obtain a better understanding of the worldwide prevalence and current research status, the authors conducted a comprehensive bibliometric analysis of literature published from 2000 to 2022. The contributions of institutions, journals, countries or regions, cited literature, keywords, and authors in global publications were concisely summarized using the COOC and VosViewer software tools. The data were extracted from the expansive Web of Science database. A total of 5478 papers were collected for analysis, and the number of publications has exhibited exponential growth over the last 22 years. The United States emerged as the most productive country, closely followed by China. Noteworthy institutions for their high productivity include the Sloan-Kettering Cancer Center, Sun Yat-Sen University, and the University of Texas MD Anderson Cancer Center. The Head & Neck and Oral Oncology journals lead in terms of publication volume. The main areas of research in this field were prognostication, radiotherapy, survival rates, sentinel lymph node biopsy, and the human papillomavirus. In addition, the analysis of author collaboration networks yielded valuable insights into the collaborative relationships within this research domain. Our research has identified the primary characteristics of highly impactful studies on LNM in HNC, providing significant insights into the advancements made in this area of research.

Planar Schrödinger equations with critical exponential growth

Planar Schrödinger equations with critical exponential growth

Azotobacter vinelandii N2 fixation increases in co-culture with the PGPR Bacillus subtilis in a nitrogen concentration-dependent manner.

Reducing inputs of chemical N fertilizers is essential to develop a more sustainable agriculture. The stimulation of biological nitrogen fixation by N2 fixers in multispecies cultures, here the plant growth-promoting rhizobacteria Azotobacter vinelandii and Bacillus subtilis, opens opportunities for the formulation of biofertilizers consortia. While most research on N2 fixation historically focussed on the exponential growth phase of microorganisms, we observed that Bacillus subtilis stimulated Azotobacter vinelandii N2 fixation mostly during the stationary phase. This result highlights that more research on the factors controlling N2 fixation repression during the stationary growth phase, especially bacteria-bacteria interactions, is eagerly needed.

Blockchain in Luxury Resale: The Impact of Blockchain Technology Through Regulatory Focus and Uncertainty Reduction Theories

ABSTRACTThe exponential growth of the online luxury resale market has spurred a notable shift toward a circular economy, reflecting the increasing consumer preference for pre‐owned luxury items. Nevertheless, this growth presents challenges related to product authenticity and seller credibility. In response to these concerns, blockchain technology (BT) emerges as a promising solution, leveraging a decentralized ledger to enhance transparency and reduce information asymmetry. This allows for the traceability of pre‐owned luxury goods, addressing issues of provenance and authenticity in the online resale space. By incorporating regulatory focus theory into the uncertainty reduction theory, this study examines how approach and avoidance motivations impact evaluations of BT‐enabled platforms to effectively mitigate consumer uncertainties and influence trust. The collected data (N= 511) was analyzed through partial least squares structural equation modeling (PLS‐SEM; study 1), and a complementary qualitative study (study 2) was additionally conducted. Results reveal that distinct motivations coexist, each following separate pathways to build consumer trust. Findings indicate that an approach orientation mindset highly values the reliability of BT‐enabled information, while an avoidance orientation focuses on risk mitigation and expresses heightened uncertainty in online transactions. Consequently, BT is found to be instrumental in reducing consumer concerns about purchasing pre‐owned luxury products. The study contributes to the existing literature by shedding light on the psychological dynamics influencing consumer trust in BT‐enabled platforms, has implications for luxury retailers contemplating BT integration, and offers insights into consumer behavior that can inform strategies to enhance perceived trust in online luxury resale.

Aperiodic Optimal Chronotherapy in Simple Compartment Tumour Growth Models Under Circadian Drug Toxicity Conditions

Cancer cells typically divide with weaker synchronisation with the circadian clock than normal cells, with the degree of decoupling increasing with tumour maturity. Chronotherapy exploits this loss of synchronisation, using drugs with circadian-clock-dependent activity and timed infusion to balance the competing demands of reducing toxicity toward normal cells that display physiological circadian rhythms and of efficacy against the tumour. We analysed optimal chronotherapy for one-compartment nonlinear tumour growth models that were no longer synchronised with the circadian clock, minimising a cost function with a periodically driven running cost accounting for the circadian drug tolerability of normal cells. Using Pontryagin’s Minimum Principle (PMP), we show, for drugs that either increase the cell death rate or kill dividing cells, that optimal solutions are aperiodic bang–bang solutions with two switches per day, with the duration of the daily drug administration increasing as treatment progresses; for large tumours, optimal therapy can in fact switch mid treatment from aperiodic to continuous treatment. We illustrate this with tumours grown under logistic and Gompertz dynamics conditions; for logistic growth, we categorise the different types of solutions. Singular solutions can be applicable for some nonlinear tumour growth models if the per capita growth rate is convex. Direct comparison of the optimal aperiodic solution with the optimal periodic solution shows the former presents reduced toxicity whilst retaining similar efficacy against the tumour. We only found periodic solutions with a daily period in one-compartment exponential growth models, whilst models incorporating nonlinear growth had generic aperiodic solutions, and linear multi-compartments appeared to have long-period (weeks) periodic solutions. Our results suggest that chronotherapy-based optimal solutions under a harmonic running cost are not typically periodic infusion schedules with a 24 h period.