bluuebunny/crossref_metadata_2025_split huggingface dataset:
Volatilome of the maize phytopathogenic fungus Fusarium verticillioides: potential applications in diagnosis and biocontrol
Authors: Achimón Fernanda , Pizzolitto Romina P 
Published: October 2024

AbstractBACKGROUNDFusarium verticillioides is a maize fungal phytopathogen and a producer of volatile organic compounds (VOCs) and fumonisin B1 (FB1). Our aim was to study the volatilome, conidial production, ergosterol and FB1 biosynthesis in maize cultures over a 30‐day incubation period (5, 10, 15, 20, 25, 30 days post inoculation [DPI]). The effect of pure VOCs on the same parameters was then evaluated to study their potential role as biocontrol agents.RESULTSIn total, 91 VOCs were detected, with volatile profiles being more similar between 5 and 10 DPI compared with 15, 20, 25 and 30 DPI. Ergosterol content increased steadily with incubation time, and three growth stages were identified: a lag phase (0 to 15 DPI), an exponential phase (15 to 20 DPI) and a stationary phase (20 to 30 DPI). The maximum concentration of FB1 was detected at 25 (0.030 μg FB1/μg ergosterol) and 30 DPI (0.037 μg FB1/μg ergosterol), whereas conidial production showed a maximum value at 15 DPI (4.3 ± 0.2 × 105 conidia/μg ergosterol). Regarding pure VOCs, minimal inhibitory concentration values ranged from 0.3 mm for 4‐hexen‐3‐one to 7.4 mm for 2‐undecanone. Pure VOCs reduced radial growth, conidial production and ergosterol and FB1 biosynthesis.CONCLUSIONSThe marked resemblance between VOC profiles at 5 and 10 DPI suggests that they could act as early indicators of fungal contamination, particularly 4‐ethylguaiacol, 4‐ethyl‐2‐methoxyanisole, heptanol and heptyl acetate. On the other hand, their role as inhibitors of fungal growth and FB1 biosynthesis prove their great potential as safer alternatives to control phytopathogenic fungi. © 2024 Society of Chemical Industry.
Macroinvertebrate Community Responses to Disturbance in a Fragmented River With Contrasting Legacies of Alteration
Authors: Baumann Karen A. , Scholl Eric A. , Rantala Heidi M. , Whiles Matt R. 
Published: October 2024

ABSTRACTFlow is a critical factor determining the riverine ecosystem structure and function. Widespread hydrologic alteration, however, has impacted the ecological integrity of rivers in ways that are not well understood, including responses of biological communities to increasingly frequent and severe climatic disturbances. Our study compared the responses of invertebrate communities on woody debris to large flooding and extreme drought in two highly contrasting segments of an impaired low‐gradient river. The upstream segment, which according to previous research has higher α‐diversity and production of large‐bodied and sensitive invertebrates, maintained higher flows and longitudinal connectivity throughout the 4‐year study. Communities in this upper segment resembled one another among sites (lower spatial turnover) but experienced greater temporal shifts in composition associated with hydrological disturbances. Conversely, invertebrate communities in the highly altered downstream segment, which is impaired by reduced flow, sedimentation, and hypoxia, were composed of smaller‐bodied and pollution‐tolerant taxa with lower α‐diversity. Unlike the upper segment, communities were patchily distributed among sites (higher spatial turnover), which made it more difficult to detect system‐wide temporal variation in composition throughout the study. Our study underscores the benefit of including measures of connectivity and spatial heterogeneity when assessing the ecological integrity of lotic systems. Understanding the system‐wide response to disturbances across longer time frames can help better predict and mitigate the impacts of climate change on ecosystem integrity in degraded rivers.
Advanced Hybrid Techniques for Cyberattack Detection and Defense in IoT Networks
Authors: Mahdi Zaed S. , Zaki Rana M. , Alzubaidi Laith 
Published: October 2024

ABSTRACTThe Internet of Things (IoT) represents a vast network of devices connected to the Internet, making it easier for users to connect to modern technology. However, the complexity of these networks and the large volume of data pose significant challenges in protecting them from persistent cyberattacks, such as distributed denial‐of‐service (DDoS) attacks and spoofing. It has become necessary to use intrusion detection systems and protect these networks. Existing intrusion detection systems for IoT networks face many problems and limitations, including high false alarm rates and delayed detection. Also, the datasets used for training may be outdated or sparse, which reduces the model's accuracy, and mechanisms may not be used to defend the network when any intrusion is detected. To address these limitations, a new hybrid deep learning and machine learning methodology is proposed that contributes to detecting DDoS and spoofing attacks, reducing false alarms, and then implementing the necessary defensive measures. In proposed hybrid methodology consists of three stages: the first stage is to propose a hybrid method for feature selection consisting of techniques (correlation coefficient and sequential feature selector); the second stage is to propose a hybrid model by integrating deep learning neural networks with a machine learning classifier (cascaded long short‐term memory [LSTM] and Naive Bayes classifier); and in the third stage, improving network defense mechanisms and blocking ports after detecting threats and maintaining network integrity. In training and evaluating the performance of the proposed methodology, three datasets (CIC‐DDoS2019, CIC‐IoT2023, and CIC‐IoV2024) were used, and these data were also balanced to obtain effective results. The accuracy of 99.91%, 99.88%, and 99.77% was obtained. Also, a cross‐validation technique was used with the test data to ensure no overfitting. The proposed methodology has proven its high performance in detecting attacks, as it provides a powerful solution to enhance the security of IoT networks and protect them from cyberattacks, as it can be applied in many fields and to other attacks.
Irreversibility analysis in an electro‐osmotically driven flow using ternary hybrid nanofluids in a microchannel with a porous material
Authors: Yusuf Tunde A. , Salawu Sulyman O. , Adesanya Samuel O. , Ukaegbu Joel C. 
Published: October 2024

AbstractFlow enhancement is one of the most significant challenges in microfluidics with extremely low permeability. Based on this, electrokinetics remediation for the double‐layer flow of hybrid ternary nanofluid is proposed based on the transport of ions under constant pumping pressure. The entropy generation volumetric rate relation is also modeled. The nonlinear system of equations is formulated, solved, and validated numerically by the collocation method and shooting Runge–Kutta method. Results are shown graphically to explore the impacts of governing parameters, such as the Darcy parameter, viscosity index, electrokinetic, and Joule heating effects, on the velocity, temperature, entropy, and Bejan number profiles. The flow and heat transmission in microchannels may be significantly changed and controlled by the electric double layer. The findings show that as the electrokinetic parameter's magnitude increases, the flow is slowed down, and thermal dispersion is impeded by nanoparticle collisions, which lowers the velocity field and heat transfer profile.
Nonlinear vibration and parametric excitation of magneto‐thermo elastic embedded nanobeam using homotopy perturbation technique
Authors: Selvamani Rajendran , Thangamuni Prabhakaran , Yaylacı Murat , Emin Özdemir Mehmet , Yaylacı Ecren Uzun 
Published: October 2024

AbstractThe present study focuses on the modeling and analyzing the nonlinear vibration patterns and parametric excitation of embedded Euler–Bernoulli nanobeams subjected to thermo‐magneto‐mechanical loads. The Euler–Bernoulli nanobeam is developed with external parametric excitation. The governing equation of motion is derived by utilizing nonlocal continuum theory and nonlinear von Karman beam theory. Subsequently, the homotopy perturbation technique is employed to determine the vibration frequencies. Finally, the modulation equation of Euler–Bernoulli nanobeams is derived for simply supported boundary condition. In order to validate our findings, we conduct a comparative analysis against existing literature, thereby underscoring the effectiveness and robustness of our proposed methodology. The influence of stress, magnetic potential, temperature, damping coefficient, Winkler coefficient, and nonlocal parameters are tested numerically on nonlinear frequency‐amplitude and parametric excitation–amplitude responses. The numerical examples indicate the significant impact of physical variables on the nonlinear frequency and parametric excitation. The primary objective of this study is to investigate the effects of external physical variables on the dynamic behavior of nanobeams, particularly in nonlinear regimes. This study provides insights into the design and control of nanostructures under complex load conditions, contributing to developing advanced materials and nanosystems.
Improving Social Justice, Environmental Integrity, and Geopolitical Resilience in EU Electric Mobility Transition
Authors: Lis-Plesińska Aleksandra , Ortar Nathalie , Szymanowski Rafał , Jaskólski Marek W. , Parteka Aleksandra , Buisson Christine 
Published: October 2024

AbstractWe recommend improving social justice, environmental integrity, and geopolitical resilience in electric mobility transition. To achieve this policy recommendation, we propose the following: (1) Increase societal acceptance and justice of climate policies by engaging local stakeholders; (2) Prioritize sustainable mobility practices over replacement of internal combustion engine vehicle (ICEV) with battery electric vehicle (BEV); (3) Base resilience of global value and supply chains on a diversified network of suppliers and a balanced structure of domestic and foreign content of economic value; (4) Evaluate geo-political risks and environmental impacts of value and supply chains in non-European regions; (5) Create a geopolitical risk body to scrutinise geopolitical threats to the electric mobility supply chain; and (6) Increase the share of EU-based manufacturing in electric mobility related sectors.
Assessing Mobility Policy with AI-Driven Analysis of User-Generated Content
Authors: Tori Floriano , van Vessem Charlotte , Betancur Arenas Juliana , Ginis Vincent 
Published: October 2024

AbstractWe recommend assessing mobility policies with AI-driven analysis of user-generated content. To achieve this policy recommendation, we propose to take into account the following: (1) Using large language models to analyse user-generated content is a reliable methodology for gathering and analysing typically overlooked relevant information regarding citizens' perceptions in the implementation of sustainable mobility policies; (2) The substantial processing capacity of these models, coupled with their ability to gather a great amount of information, enables decision-makers to supplement and enhance the often-limited traditional data collection methods. As exposed in the following case study, this methodology can provide historical perceptual information on transport modes, mobility policies, and infrastructure, among others; and (3) The ease of applying this methodology through AI open-source recent developments such as ChatGPT allows decision-makers and their teams to rapidly generate and assess a great amount of relevant data. This can facilitate policymakers' effectiveness and efficiency in the decision-making processes in urban mobility planning. However, policymakers should be aware of the characteristics of their selected population and use this as a complementary and evaluative method.
Thermodynamics of the α-FeOOH (goethite)-ScOOH solid solution
Authors: Majzlan Juraj 
Published: October 2024

AbstractScandium (Sc) is a rare element that finds uses in modern technologies. Thermodynamic properties of Sc phases could help in the development of innovative technologies to extract Sc from mining waste. In this work, we investigated the FeOOH–ScOOH solid solution with the goethite structure. The end members and five intermediate compositions were synthesized and characterized. The lattice parameters show that the solid solution is non-ideal, with complex behavior induced by the Fe–Sc substitution. The excess unit-cell volume deviates negatively for the Sc-rich region, and positively for the Fe-rich region from the ideal behavior (Vegard’s law). Enthalpies of dissolution were determined by acid-solution calorimetry in 5 mol$$\cdot \hbox {dm}^{-3}$$

·

dm

-
3

HCl at T = 343.15 K. Enthalpies of mixing ($$\Delta _{mix}H$$

Δ

mix

H

), calculated from the experimental data, are small and positive. The available data allow for fitting the data as $$\Delta _{mix}H = W x (1-x)$$

Δ

mix

H
=
W
x

(
1
-
x
)

, with the mixing parameter $$W = 15.2\pm$$

W
=
15.2
±

1.0 kJ$$\cdot \hbox {mol}^{-1}$$

·

mol

-
1

. Using $$\Delta _fG^o$$

Δ
f

G
o

of ScOOH from earlier literature, we calculated a Lippmann diagram that shows that Sc should strongly partition into the aqueous phase upon goethite precipitation. The field observations from lateritic profiles show that Sc is primarily harbored by goethite via adsorption. It seems that under weathering conditions, thermodynamically driven partitioning of $$\hbox {Sc}^{3+}$$

Sc

3
+

into the aqueous phases and its subsequent adsorption onto goethite surfaces controls the mobility of Sc in the weathering profiles.
Evaluating the accuracy of population-specific versus generic stature estimation regression equations in a South African sample
Authors: Bidmos Mubarak , Brits Desiré 
Published: October 2024

Abstract
Accurate estimates of stature play an important role in the personal identification of unknown decedents, however a drawback in the application of many stature estimation equations is the need for known sex and population, the assignment of which can be challenging. Researchers have formulated equations for stature estimation that are neither population- nor sex-specific and thereof the aim of this study was to assess the applicability of these stature estimation equations proposed by Albanese et al.. (2016) (Albanese J, Tuck A, Gomes J, Cardoso HFV (2016) An alternative approach for estimating stature for long bones that is not population- or group-specific. Forensic Sci Int 259:59–68). The physiological length of the femur, condylar malleolar length of the tibia and a combination of these measurements, collected from Magnetic Resonance Imaging Scanograms of adult (20–60 years) White South African males (n = 30) and females (n = 44) were used to assess the accuracy of the Albanese et al. (Albanese J, Tuck A, Gomes J, Cardoso HFV (2016) An alternative approach for estimating stature for long bones that is not population- or group-specific. Forensic Sci Int 259:59–68). sex-specific and generic stature estimation equations. The stature estimates were compared with measured living stature (LSM), using paired t-tests. Results indicated that the Albanese et al. (Albanese J, Tuck A, Gomes J, Cardoso HFV (2016) An alternative approach for estimating stature for long bones that is not population- or group-specific. Forensic Sci Int 259:59–68). equations underestimated living stature by between 1.1 and 5.0 cm. These underestimations were significantly different between the LSM and the sex-specific estimates for females and the LSM and the generic estimates for males and the tibia for sex-specific equation. All stature estimates however fell in between two standard error of estimates for the sex-specific equations for males and the generic equations for the females. Although, the equations by Albanese et al. (Albanese J, Tuck A, Gomes J, Cardoso HFV (2016) An alternative approach for estimating stature for long bones that is not population- or group-specific. Forensic Sci Int 259:59–68). can be used to estimate stature in White South Africans in certain cases, the use of sex/population-specific equations remains the method of choice.
A sarcoptic mange outbreak drives long-term patterns of a fitness trait in an exotic ungulate
Authors: Pascual-Rico Roberto , Sánchez-Zapata José A. , Candela Mónica G. , Eguía Sergio , Barbosa Jomar M. 
Published: October 2024

AbstractSpecies phenotypes are driven by persistent selective pressures that condition their adaptation to the environment. However, stochastic critical events, such as disease outbreaks, may also act as selective pressures because of drastic population decline. External structures like horns of ungulate species may reflect the consequences of these selective pressures on animal fitness. Using a generalized linear model approach, we analysed how a massive mortality event caused by a sarcoptic mange outbreak in 1992 affected the horn size of an Iberian aoudad population (dataset from 1980 to 2014) by comparing horn length before and after the outbreak. We found that this episodic, albeit massive, outbreak changed long-term trends in age-size horn relations. Both females and males presented shorter horns after the sarcoptic mange outbreak, although more marked in males. Even when animals reached mature ages, horn length did not increase with age to the same degree as before the outbreak. We consider that two processes may have acted on the population: a bottleneck favoured “shorter horns” phenotype and a post-mange enzootic period limited horn growth, as infected animals may invest more resources in the immune system. Overall, our results show a top-down regulation of a fitness trait for an ungulate population mediated by a parasite. This disease outbreak showed long-lasting effects on the ungulate population, with ecological and management implications.
Graphical Abstract
Modelling crop management and environmental effects on the development of Leptosphaeria maculans pseudothecia
Authors: Bondad Jamina J , Whish Jeremy P. M. , Sprague Susan J. , Van de Wuow Angela P. , Barry Kara M. , Harrison Matthew T. 
Published: October 2024

Abstract
The timing of ascospore release is critical in the prediction of blackleg infection, particularly if the timing of spore release coincides with early development of canola seedlings. Historically, prediction models have used average daily temperature and an environment calibration to estimate a minimum rainfall amount to trigger development. This paper describes a different approach based on hydro-thermal time, where soil evaporation and rainfall are used as a surrogate to estimate when the stubble is wet, and temperature is accumulated on an hourly basis. Furthermore, the stubble orientation due to differing harvest management practices is considered, as stubble knocked down has greater contact with the soil compared to stubble which remains in a standing position. Pseudothecia and ascospore development in the standing and lying treatments was monitored weekly to measure the rate of development in diverse environments. The new modelling approach was used to describe the pseudothecial maturation rate and predict the timing of ascospore release. Subsequently, a range of Australian and international datasets were used to assess the robustness and accuracy of this new model’s predictions. When tested across multiple locations and seasons globally, the hydro-thermal time approach had similar performance (R2 = 0.94, RMSD = 16 days) to the existing Sporacle Ezy model (R2 = 0.90, RMSD = 22 days), but without the need to calibrate in different environments and account for the delayed rate of development in standing stubble. Integrating this new approach into early warning systems for canola growers will help in the management of control measures.
Cut the scrap? the impact of truck age on driver retention, driving safety, and driving productivity
Authors: de Vries Jelle , Roy Debjit 
Published: October 2024

AbstractIn many countries, vehicle replacement policies are implemented to reduce the average age of the vehicles on the road. Through these policies, policymakers typically aim to reduce emissions and to stimulate demand for automobiles through vehicle renewal. Not much is known however, about the more detailed operational consequences of vehicle age in truck transportation. In this study, we empirically address this issue by analyzing data obtained from 27 thousand trips made by 916 drivers in 355 unique trucks, over a period of 346 days. Using this data, we test the relationship between truck age and driver retention, productivity, and unsafe driving behavior. Our results demonstrate that truck age significantly impacts driver turnover, with every additional year of truck age relating to an approximate 5% higher risk of leaving the job at a given point in time. Contrarily, drivers with older trucks drove significantly less volatile, which suggests that they drive more safely. The results illustrate that vehicle age influences a broader spectrum of outcome measures than typically considered when assessing the expected impact of replacement policies. Policymakers and trucking companies can use these results to make more informed decisions about vehicle replacement, thereby also addressing the widespread issue of driver shortage.
Save for a rainy day? How regional household savings constrain entrepreneurship after a natural disaster
Authors: Zhang Jiabin , van Hugten Joeri , Stam Wouter 
Published: October 2024

AbstractWhy do some entrepreneurial ecosystems successfully adjust amid adversity while others languish? By integrating prospect theory into the entrepreneurial ecosystem literature and using a quasi-natural experimental design with a difference-in-difference-in-differences model, our theory and findings reveal that earthquakes reduce entrepreneurship in regions with high household savings, but increase entrepreneurship in regions with low savings, and these between-area differences increase over time. Reconceptualizing the meaning of savings from a resource into a key driver of loss aversion, we thus identify the surprising constraining influence of financial capital in times of adversity, yielding important implications for entrepreneurship research and policymakers.
Distinguishing two kinds of fictionalism: metaphor, autism, and the imagination
Authors: Lane Elek 
Published: October 2024

AbstractFictionalist theories of metaphor hold that metaphorical utterances aim at fictionality. Fictionalism successfully explains speaker judgments about the truth and aptness of metaphorical utterances, and it also accurately predicts the data around metaphor and autistic individuals (who have deficits in both imaginative play and metaphor comprehension). But fictionalism is not a viable theory of metaphor, despite these merits, because of (what I call) the problem of semantic entailment: semantic entailments that are normally valid fail under metaphorical interpretation, but fictionalism predicts otherwise. I argue this to ultimately show that theorists of metaphor should reject the linguistic side of the fictionalist story; but this leaves open the possibility of accepting psychological fictionalism, i.e., the hypothesis that fiction/make-believe is central to the cognitive processing of metaphor. Coupling psychological fictionalism with a different theory of metaphorical meaning and content (such as contextualism) promises to keep the explanatory upsides of traditional fictionalism while avoiding the problem of semantic entailment.