bluuebunny/crossref_metadata_2025 huggingface dataset:
Elastostatic Performance Evaluation of a Full-Mobility Parallel-Kinematics Machine With Flexible Links
Authors: Sun Qi , Angeles Jorge
Published: January 2025

The subject of this article is the elastostatics of a novel three-limb, full-mobility parallel-kinematics machine (PKM) with flexible links, intended for high-frequency, small-amplitude operations. The objective is to establish the Cartesian stiffness model and performance indices capable of guiding the structural design of the machines of interest. We base our analysis on what we term an elastostatic Cartesian model: the light-weight limb rods are modeled as identical, massless, linearly elastic beams; the motor shafts and couplings are modeled likewise, with the beams replaced by identical, massless, linearly elastic torsional springs, both link flexibility and actuator flexibility thus being considered. The moving platform is assumed to be the only moving rigid body of the machine. This platform is thus regarded as a rigid body elastically mounted onto the base platform via a six-degree-of-freedom (six-DoF) Cartesian spring. Then, the PKM 6×6 Cartesian stiffness matrix, considering the flexibility of both limb rods and motor shafts, is derived via the pertinent kinetostatic relations. Moreover, three alternative indices are defined from this model to evaluate the robot stiffness, which allows us to choose the most appropriate one for specific applications.
Active Cables Selection for Collocated Vibration Control of Small-Sized Overconstrained Cable-Driven Parallel Robots
Authors: Garcia Thibault , Rémond Didier , Chesné Simon
Published: January 2025

Cable-driven parallel robots (CDPRs) are well appreciated for high dynamics applications, due to their lightweights moving parts. Nevertheless, due to the low stiffness of cables, vibrations can occur and can degrade performances if high precision is required, such as in additive manufacturing for instance. Previous works have studied techniques to counteract vibrations, like using motor command or embedded devices. Based on a previous first exploration of using piezoelectric transducers on cables for this type of robot, this paper presents a proper formulation of the collocated active vibration control to damp the end-effector oscillations of small-sized overconstrained CDPRs by the measure of the variation in cable tensions. This goes through a modeling of such a robot with embedded piezoelectric transducers under appropriate assumptions. From this control formulation, it is shown that the collocated nature of these transducers are fundamental. It is thus possible to highlight an energetic index of active cables selection, regardless of the used control law. The proposed technique is developed theoretically and analyzed through simulations on an eight-cable robot.
Construction of Confidence Regions for Uncertain Spatial Displacements With Dual Rodrigues Parameters
Authors: Yu Zihan , Ge Qiaode Jeffrey , Langer Mark P.
Published: January 2025

This article follows our recent work on the computation of kinematic confidence regions from a given set of uncertain spatial displacements with specified confidence levels. Dual quaternion algebra is used to compute the mean displacement as well as relative displacements from the mean. In constructing a 6D confidence ellipsoid, however, we use dual Rodrigues parameters resulting from dual quaternions. The advantages of using dual quaternions and dual Rodrigues parameters are discussed in comparison with those of three translation parameters and three Euler angles, which were used for the development of the so-called rotational and translational confidence limit (RTCL) method. The set of six dual Rodrigues parameters are used to define a parametric space in which a 6×6 covariance matrix and a 6D confidence ellipsoid are obtained. An inverse operation is then applied to first obtain dual quaternions and then to recover the rotation matrix and translation vector for each point on the 6D ellipsoid. Through examples, we demonstrate the efficacy of our approach by comparing it with the RTCL method known in literature. Our findings indicate that our method, based on the dual Rodrigues formulation, yields more compact and effective swept volumes than the RTCL method, particularly in cases involving screw displacements.
Numerical Study on the Effect of Various Working Fluids on the Performance of Loop Heat Pipes Based on Two-Dimensional Simulation
Authors: Shao Bo , Lin Bingyao , Li Nanxi , Liu Le , Jiang Zhenhua , Dong Deping , Wu Yinong
Published: January 2025

The computational fluid dynamics (CFD) method is often used to study heat and mass transfer mechanisms in loop heat pipes (LHPs). However, few numerical studies have been conducted on the entire loop heat pipe system. In this work, a two-dimensional simulation model of an LHP was developed. The wicking process was described using a capillary pressure model, implemented through user-defined functions (UDFs). The flow, phase change, and heat transfer processes vary with the change of the working fluid. Therefore, the effects of ammonia, propylene, and R245fa on the heat transfer performance of the LHP were analyzed in the simulation. According to the simulation results, the LHP charged with ammonia showed the best heat transfer performance, followed by the LHP charged with propylene, and the LHP charged with R245fa showed the worst heat transfer performance. The simulation results align with the predictions from figures of merit (FOMs). Moreover, the model provides detailed insights into the temperature field and vapor–liquid distribution during LHP operation. Experiments using an LHP with the three working fluids were also conducted to verify the model's accuracy. Regarding the influence of the working fluid and the heat load on LHP performance, the simulation model aligns with the experimental results.
Evaluation of Particulate Deposition Effects on Film Cooling Using Conjugate Heat Transfer Methods: An Experimental and Numerical Study
Authors: Yang Xing , Hao Zihan , Feng Zhenping
Published: January 2025

A significant challenge of offering adequate film cooling for gas turbine hot components in practical operation is deposition induced by impurities from the intake air and fuel, which influences the overall cooling performance by changing the surface geometric and thermal conditions. In this study, an experimental and numerical combined methodology was used to evaluate the deposition effects on film cooling from a row of holes on conductive flat plates. Cylindrical holes with simple and compound holes that are extensively used in today's modern engines were investigated to assess the sensitivity of their overall cooling effectiveness to deposition for coolant injection ratios of 0.5–2.0. Flow physics and thermal fields were analyzed to better understand the coupling effects of film cooling with deposition and their interaction with solid walls. Furthermore, the isolated effects of deposition on adiabatic film cooling and heat transfer were examined, allowing for a better understanding of which factor dominates the resulting combined effects. Inspection of overall cooling effectiveness on the wall backside revealed that the deposition effects were strongly linked to coolant jet behaviors, which were determined by both the coolant injection ratio and the hole orientation angle. Quantitative comparisons showed that deposition decreased overall cooling effectiveness by 22% on the flat plate cooled by the compound-angled hole with the lowest blowing ratio of 0.5, while it increased overall cooling effectiveness from the simple hole by 38% at a higher blowing ratio of 1.5. The results reported for the current work provide guidance on how to choose orientation angles for film cooling design where deposition problems are accounted for.
Parametric Study and Optimization of a New Type of Solar Air Collector Employing Flat Micro Heat Pipe Arrays
Authors: Wang Xinran , Diao Yanhua , Wang Zhen , Pan Yawen , Zhao Yaohua , Li Yuhan , Wang Tengyue , Zhu Tingting
Published: January 2025

The performance improvement of flat-plate solar air collectors (FPSACs) is vital for solar energy utilization. Accordingly, flat micro heat pipe arrays (FMHPAs) have been utilized in FPSACs given their excellent thermal conductivity and suitable specific surface area. To investigate the impact of structural parameters of the flat-plate solar air collector with flat micro heat pipe arrays and optimize the performance, this study establishes a CFD 3D model of the collector with L-shaped flat micro heat pipe arrays. Fin height H, fin spacing L, glass thickness D, and air gap thickness Sair are selected as four important structural parameters for numerical work. Response surface methodology is adopted to recognize the significance of each factor and realize the prediction and optimization of the collector's thermal efficiency. Results show that the thermal efficiency can achieve a peak value of 52.50%. An enhanced heat transfer condition in condensation is obtained when the optimal fin height and fin spacing are 25 and 4 mm, respectively. Improved thermal insulation in evaporation is also achieved when the optimal glass thickness and air gap thickness are 3 and 35 mm, respectively. The significance order of the factors is H > L > D > Sair. The results can serve as an important reference for designing the flat-plate solar air collectors.
Genetic investigation of hydrogenases in
Thermoanaerobacterium thermosaccharolyticum
suggests that redox balance via hydrogen cycling enables high ethanol yield
Authors: de Souza Layse C. , Herring Christopher D. , Lynd Lee R.
Published: January 2025

Thermoanaerobacterium thermosaccharolyticum
is an anaerobic and thermophilic bacterium that has been genetically engineered for ethanol production at very high yields. However, the underlying reactions responsible for electron flow, redox equilibrium, and how they relate to ethanol production in this microbe are not fully elucidated. Therefore, we performed a series of genetic manipulations to investigate the contribution of hydrogenase genes to high ethanol yield, generating evidence for the importance of hydrogen-reacting enzymes in ethanol production. Our results indicate that a high ethanol yield, >85% of the theoretical maximum, only occurs when the
hfsD, hydAB
, and
nfnAB
genes are all present together, while the
hfsB
gene is absent. We propose that the products of these three gene clusters facilitate an NADPH-generating reaction via hydrogen cycling, with a stoichiometry comparable with a canonical ferredoxin:NADP
+
oxidoreductase (FNOR; EC 1.18.1.2) reaction. The hypothesized mechanism provides a balance of nicotinamide cofactors and facilitates ferredoxin recycling, leading to progress in optimizing the energy conversion of biomass-derived sugars to ethanol.

IMPORTANCE

Our study elucidates the crucial role of electron flow and redox balancing mechanisms in improving ethanol yields from renewable biomass. We delve into the mechanism of electron transfer, highlighting the potential of key genes to be leveraged for enhanced ethanol production in anaerobic microbial species. We suggest by genetic investigation the existence of a novel Ferredoxin:NADP+ Oxidoreductase (FNOR) reaction, comprising HfsD, HydAB, and NfnAB enzymes, as a promising avenue for achieving balanced stoichiometry and efficient ethanol synthesis. Our findings not only advance the understanding of microbial metabolism but also offer practical insights for developing strategies to improve bioenergy production and sustainability.
Leptospira
biofilms: implications for survival, transmission, and disease management
Authors: Dias Carla Silva , Pinna Melissa Hanzen
Published: January 2025

Leptospirosis is a zoonotic disease caused by
Leptospira
bacteria, affecting humans and a broad range of wild and domestic animals in diverse epidemiological settings (rural, urban, and wild). The disease’s pathogenesis and epidemiology are complex networks not fully elucidated. Epidemiology reflects the One Health integrated approach of environment–animal–human interaction, causing severe illness in humans and animals, with consequent public health burdens. Saprophytic and pathogenic leptospires have been shown to form biofilms
in vivo
,
in vitro,
and in environmental samples. Biofilms are characterized by a polymeric matrix that confers protection against hostile environments (both inside and outside of the host), favoring bacterial survival and dissemination. Despite its significance, the role of this bacterial growth mode in leptospiral survival, transmission, and decreased antibiotic susceptibility remains poorly understood and underexplored. Even so, the literature indicates that biofilms might be correlated with lower antimicrobial susceptibility and chronicity in leptospirosis. In this minireview, we discuss the aspects of biofilm formation by
Leptospira
and their significance for epidemiology and therapeutic management. Understanding the current scenario provides insight into the future prospects for biofilm diagnosis, prevention, and treatment of leptospirosis.
Interaction between bacterial adhesins leads to coaggregation by the oral bacteria
Veillonella parvula
and
Streptococcus gordonii
Authors: Leo Jack C.
Published: January 2025

Veillonella parvula
is an unusual diderm firmicute that plays a central role in the formation of dental biofilm formation through coaggregation with many other oral bacteria. However, the molecular interactions leading to oral biofilm formation are largely unknown. In a recent study (L. Dorison, N. Béchon, C. Martin-Gallausiaux, S. Chamorro-Rodriguez, et al., mBio 15:e02171-24, 2024,
https://doi.org/10.1128/mbio.02171-24
), coaggregation by
V. parvula
was shown to be mediated by trimeric autotransporter adhesins (TAAs), which are large, fibrous surface proteins widespread in Gram-negative bacteria. Importantly, this study identified the binding partner protein on a coaggregating bacterium,
Streptococcus gordonii
, which the authors called VisA. This finding is the first time a TAA mediating coaggregation with a different type of protein has been established and suggests that specifically interacting protein partners may have coevolved multiple times to allow complex biofilm formation, as exemplified by the development of dental plaque. Understanding these interactions might lead to innovations to reduce build-up of dental plaque and associated oral diseases.
Tracking clonal and plasmid transmission in colistin- and carbapenem-resistant
Klebsiella pneumoniae
Authors: Akintayo Ifeoluwa , Siroglavic Marko , Frolova Daria , Silva Mabel Budia , Grundmann Hajo , Iqbal Zamin , Budimir Ana , Reuter Sandra
Published: January 2025

The surveillance of mobile genetic elements facilitating the spread of antimicrobial resistance genes has been challenging. Here, we tracked both clonal and plasmid transmission in colistin- and carbapenem-resistant
Klebsiella pneumoniae
using short- and long-read sequencing technologies. We observed three clonal transmissions, all containing Incompatibility group (Inc) L plasmids and New Delhi metallo-beta-lactamase
bla
NDM-1
, although not co-located on the same plasmid. One IncL-
bla
NDM-1
plasmid had been transferred between sequence type (ST) 392 and ST15, and the promiscuous IncL-
bla
OXA-48
plasmid was likely shared between a singleton and a clonal transmission of ST392. Plasmids within clonal outbreaks and between clusters and STs had 0–2 single nucleotide polymorphism (SNP) differences, showing high stability upon transfer to same or different STs. The simplest explanation, without a comprehensive analysis with long-read sequencing, would be the spread of a single common IncL-
bla
NDM-1
plasmid. However, here, we report
bla
NDM-1
in five different plasmids, emphasizing the need to investigate plasmid-mediated transmission for effective containment of outbreaks.

IMPORTANCE

Antimicrobial resistance occupies a central stage in global public health emergencies. Recently, efforts to track the genetic elements that facilitate the spread of resistance genes in plasmids outbreaks, utilizing short-read sequencing technologies, have been described. However, incomplete plasmid reconstruction from short-read sequencing data hinders full knowledge about plasmid structure, which makes the exploration very challenging. In this study, we used both short- and long-read sequencing in clinical
Klebsiella pneumoniae
from University Hospital Centre Zagreb, Croatia, which was resistant to both last-resort antibiotics colistin and carbapenem. Our results show complex transmission networks and sharing of plasmids, emphasizing multiple transmissions of plasmids harboring carbapenem and/or colistin resistance genes between and within
K. pneumoniae
clones. Only full-length sequencing plus a novel way of determining plasmid clusters resulted in the complete picture, showing how future active monitoring of plasmids as a vital tool for infection prevention and control could be implemented.
Whole-genome phylogenetic analysis of
Mycobacterium avium
complex from clinical respiratory samples
Authors: Ka Lip Chew , Go Joelle , Binte Abu Bakar Nur Aisyah , Octavia Sophie , Pin Lin Raymond Tzer , Teo Jeanette W. P.
Published: January 2025

The
Mycobacterium avium
complex (MAC) is a common causative agent causing nontuberculous mycobacterial (NTM) pulmonary disease worldwide. Whole-genome sequencing was performed on a total of 203 retrospective MAC isolates from respiratory specimens. Phylogenomic analysis identified eight subspecies and species.
M. avium
subspecies
hominissuis
(MAH) was the overwhelmingly dominant species (148/203, 72.9%). The other seven identified species were
M. intracellulare
subsp.
yongonense
(18/203, 8.9%),
M. intracellulare
subsp.
chimaera
(10/203, 4.9%),
M. colombiense
(11/203, 5.4%),
M. paraintracellulare
(6/203, 3%),
M. marseillense
(5/203, 2.5%),
M. intracellulare
(3/203, 1.5%), and
M. avium
subspecies
paratuberculosis
(2/203, 1%). Significant genetic clustering was observed among MAH isolates. Notably, a large cluster (<12 SNPs) of 76 MAH isolates bearing the same sequence type was observed. The presence of closely related isolates within hospital settings raises concerns about transmission routes with environmental sources potentially playing a significant role. Based on susceptibility breakpoints that are available for clarithromycin, amikacin, linezolid, and moxifloxacin, low rates of clarithromycin (0.5%, 1/203) and amikacin (1.5%, 3/203) phenotypic resistance were observed. While linezolid and moxifloxacin resistance were 25.6% (52/2030) and 46.3% (94/203), respectively. Drug resistance-associated loci were searched for mutations linked to phenotypic drug resistance. Of the entire cohort, only one isolate was found to have a A2059G 23S rRNA (
rrl
) gene mutation responsible for macrolide resistance.

IMPORTANCE

Mycobacterium avium
complex (MAC) infections are increasingly challenging to manage due to their complex species diversity and varied resistance patterns. This study underscores the genetic diversity within MAC, identifying at least eight species and subspecies among 203 clinical isolates, with
M. avium
subsp.
hominissuis
(MAH) being most prevalent at 72.9%. Notably, genetic clustering was observed within MAH and
M. intracellulare
subsp.
chimaera
, suggesting potential transmission routes within healthcare settings. Clarithromycin and amikacin resistance was found to be uncommon, aligning with the rarity of resistance-associated genetic mutations. These findings emphasize the need for enhanced infection control measures and routine susceptibility testing to tailor antibiotic therapies effectively.
Appearance of green tea compounds in plasma following acute green tea consumption is modulated by the gut microbiome in mice
Authors: Sterrett John D. , Quinn Kevin D. , Doenges Katrina A. , Nusbacher Nichole M. , Levens Cassandra L. , Armstrong Mike L. , Reisdorph Richard M. , Smith Harry , Saba Laura M. , Kuhn Kristine A. , Lozupone Catherine A. , Reisdorph Nichole A.
Published: January 2025

Studies have suggested that phytochemicals in green tea have systemic anti-inflammatory and neuroprotective effects. However, the mechanisms behind these effects are poorly understood, possibly due to the differential metabolism of phytochemicals resulting from variations in gut microbiome composition. To unravel this complex relationship, our team utilized a novel combined microbiome analysis and metabolomics approach applied to low complexity microbiome (LCM) and human colonized (HU) gnotobiotic mice treated with an acute dose of powdered matcha green tea. A total of 20 LCM mice received 10 distinct human fecal slurries for an
n
= 2 mice per human gut microbiome; 9 LCM mice remained un-colonized with human slurries throughout the experiment. We performed untargeted metabolomics on green tea and plasma to identify green tea compounds that were found in the plasma of LCM and HU mice that had consumed green tea. 16S ribosomal RNA gene sequencing was performed on feces of all mice at study end to assess microbiome composition. We found multiple green tea compounds in plasma associated with microbiome presence and diversity (including acetylagmatine, lactiflorin, and aspartic acid negatively associated with diversity). Additionally, we detected strong associations between bioactive green tea compounds in plasma and specific gut bacteria, including associations between spiramycin and
Gemmiger
and between wildforlide and
Anaerorhabdus
. Notably, some of the physiologically relevant green tea compounds are likely derived from plant-associated microbes, highlighting the importance of considering foods and food products as meta-organisms. Overall, we describe a novel workflow for discovering relationships between individual food compounds and the composition of the gut microbiome.

IMPORTANCE

Foods contain thousands of unique and biologically important compounds beyond the macro- and micro-nutrients listed on nutrition facts labels. In mammals, many of these compounds are metabolized or co-metabolized by the community of microbes in the colon. These microbes may impact the thousands of biologically important compounds we consume; therefore, understanding microbial metabolism of food compounds will be important for understanding how foods impact health. We used metabolomics to track green tea compounds in plasma of mice with and without complex microbiomes. From this, we can start to recognize certain groups of green tea-derived compounds that are impacted by mammalian microbiomes. This research presents a novel technique for understanding microbial metabolism of food-derived compounds in the gut, which can be applied to other foods.
Evolution of Pressure Waves in Liquid Containing a Porous Partition Saturated with a Bubble Fluid
Authors: Gimaltdinov I. K. , Rodionov A. S. , Valiakhmetova O. Yu.
Published: January 2025

The distinctive features of pressure wave dynamics in the presence of a porous partition (layer) saturated with a bubbly fluid are considered. It is shown that, depending on the parameters of the gas mixture and the porous medium (volume gas content, bubble dispersion, and porosity), reflection of a wave pulse from the porous partition saturated with a bubbly mixture is similar to reflection from the free boundary or from the rigid wall.
Do coping mechanisms moderate the effect of stressful life events on depression and anxiety in young people? A case–control study from Latin America
Authors: Hudson Georgie , Fung Catherine , Sureshkumar Diliniya Stanislaus , Gómez-Restrepo Carlos , Uribe-Restrepo José Miguel , Ariza-Salazar Karen , Diez-Canseco Francisco , Hidalgo-Padilla Liliana , Toyama Mauricio , Brusco Luis Ignacio , Olivar Natividad , Lucchetti Santiago , Priebe Stefan , Kirkbride James B
Published: January 2025

Background

Stressful life events (SLEs) are associated with increased risk of depression or anxiety. Coping mechanisms may moderate this relationship but little is known on this topic in young people or in Latin America.

Aim

To investigate whether coping strategies predict odds of depression and/or anxiety and moderate the relationship between SLEs and depression and/or anxiety in young people in Peru, Lima and Bogotá.

Method

Using case–control data from people aged 15–24, we used logistic regression to examine associations between coping mechanism, SLEs and caseness for depression or anxiety, adjusting for sociodemographic and socioeconomic factors. We included interaction terms to model whether this association varied depending on coping mechanisms (positive cognitive restructuring, problem focused, support seeking, distraction, avoidant).

Results

We included 1437 cases and 965 controls. Cases reported less use of positive cognitive restructuring (OR 0.66; 95% CI 0.57 to 0.75) and problem-focused coping (OR 0.82; 95% CI 0.73 to 0.93), and more use of avoidance than controls (OR 1.33; 95% CI 1.19 to 1.50) in adjusted models. They had greater odds of reporting lifetime (OR 1.07; 95% CI 1.04 to 1.10) and past-year (OR 1.05; 95% CI 1.01 to 1.10) SLEs than controls. We found weak but consistent evidence of effect modification; the association between lifetime SLEs and case–control status was stronger in those who used less support seeking (p=0.09), problem-focused coping (p=0.08) or positive cognitive restructuring (p=0.09).

Conclusions

Relationships between SLEs, coping mechanisms and depression/anxiety appear similar in these Latin American cities to other contexts. Active coping strategies may ameliorate the impact of SLEs on mental health of young people.
Childhood family income and medication use in youth
Authors: Moustgaard Heta , Moore Elina , Malmberg Satu , Tarkiainen Lasse , Martikainen Pekka
Published: January 2025

Background

Low family socioeconomic position is a well-established determinant of poor health in youth. Much less is known about the social patterning of youth medication use, and the current evidence is mixed. Furthermore, previous studies have not assessed important confounders of the associations. We analyse differences in youth medication use by childhood family income and medication type.

Methods

Administrative register data on full Finnish cohorts born in 1979–2003 (n=1 490 666) and survival analysis were used to assess the risk of using common prescription medications between ages 16 and 20 according to mean household income in ages 11–15, accounting for several observed familial characteristics including parental health. We also compared siblings with discordant childhood income exposures to assess whether any differences are explained by unobserved familial confounding.

Results

For each 10% increase in childhood family income, there was a 0.6%–1.7% increase in the probability of using the most common prescription medications: antibiotics, painkillers, and allergy and asthma medications. In contrast, a 10% increase in childhood income was related to a 2.5% decrease in the probability of psychotropic medication use. In sibling comparisons, childhood income was not associated with any type of medication use.

Conclusion

Apart from psychotropics, the results may indicate medication underuse among youth from low-income families. The sibling comparisons suggest that moderate differences in childhood income are unlikely to cause differences in youth medication use and thus, in contexts of relative income equality, income differences in medication use are likely to reflect other, unobserved, family factors shared by siblings.
Soldier performance management: insights from boots on ground research and recommendations for practitioners
Authors: Main Luana C , Maroni T D , Ojanen T , Drain J R , Nindl B
Published: January 2025

Theoretically, the serial measurement of biomarkers to monitor physiological responses to military training could be used to mitigate musculoskeletal injury risk and better understand the recovery status of personnel. To date, the cost and scalability of these initiatives have impeded their uptake by defence organisations. However, advances in technology are increasing the accessibility of a range of health and performance biomarkers. This paper presents a synthesises of findings from the literature and discussions with informed stakeholders to provide contextually relevant advice for future efforts to monitor military personnel, together with key considerations to ensure actionable outcomes from the data captured. The aim of this review is, therefore, twofold; first, to demonstrate how wearable devices and biomarkers have been used in defence research to assess the context-specific, occupational demands placed on personnel; and second, to discuss their potential to monitor military workloads, optimise training programming and understand soldier adaptation to multi-stressor environments.
Whole System Approach to designing, implementing and measuring health and performance benefits of improving diet behaviour in a military setting
Authors: Fallowfield Joanne L , Carins J
Published: January 2025

Many employers—including the military—are experiencing systemic workforce capacity and capability challenges. This coincides with a time of declining workforce health, especially among military service entrants, where many performance-limiting health conditions are preventable if healthier behaviours are practised. Effectively tackling complex, interconnected health problems demands a multilevel, multicomponent Whole System Approach (WSA). However, despite recognition of the issues impacting international militaries, current policies and practices supporting healthy, performing workforces have failed. To arrest ill-health trends in personnel, military employers must develop transformational ways to support good health. This paper presents a military workplace WSA model, operationalised through COM-B to specifically target diet behaviour, supporting individual good health, promoting human performance and realising organisational benefits. The challenges of a military occupational setting to individual nutrition practices across the career are discussed. Finally, Impact Value Chain analysis is proposed to monitor system delivery and measure the effectiveness of an integrated, organisation-wide WSA.
Impacts of COVID-19 and contractual changes on the financial performance of lumber futures
Authors: Zhang Nan , Mei Bin
Published: January 2025

The United States lumber futures market has followed a volatile path since 2017. Two key events in this market are the COVID-19 pandemic and the release of newly revised lumber futures contracts in August 2022. This study aims to examine how these two events affect the financial performance of lumber futures. We employ the event study methodology and the generalized autoregressive conditional heteroskedasticity (GARCH) model to explore the market’s reaction. A market model that includes supply and demand factors, along with the GARCH effect, is used to calculate abnormal returns and their associated volatility. A standardized trading volume ratio is also constructed to assess volume effects. The results reveal different patterns of abnormal returns over the event windows: COVID-19 caused significant daily abnormal returns and cumulative negative effects, while new contracts generated positive abnormal returns that declined over time. Second, contractual changes induced immediate abnormal return volatility, whereas COVID-19 led to sustained volatility across longer windows. Lastly, COVID-19 caused below-normal trading volume effects, while the new contracts caused short-lived increases in trading activity above normal levels. These findings can help understand how different market events affect the financial performance of lumber futures, providing valuable insights for market participants.
A pseudo-random number generator on elliptic curves over Galois field using 2D enhanced logistic-quadratic map
Authors: Kadeer Abudureheman , Tuersun Yilihamu , Liu Hongjun , Shao Junjie
Published: January 2025

This study proposes a high-performance pseudo-random number generator (PRNG) that integrates a nondegenerate two-dimensional enhanced logistic-quadratic map (2D-ELQM) with operations on elliptic curves (ECs) over the finite field GF([Formula: see text]. First, we constructed the 2D-ELQM, which demonstrates a broader chaotic range and enhanced randomness and unpredictability. We conducted a dynamic analysis of the 2D-ELQM using various methods, including bifurcation and phase space diagrams, Lyapunov exponents (LE), Kolmogorov entropy (KE), sample entropy (SE), correlation dimension (CD) and TestU01. Subsequently, we combined the 2D-ELQM with EC operations over GF([Formula: see text] to design a robust PRNG. Finally, we performed a series of experiments and comprehensive analyses to evaluate the performance of the proposed PRNG, with results indicating its effectiveness and potential application in cryptographic systems.
OscSe: A Practical Security Assessment Model for General Open Source Components
Authors: Wang Ziyan , Huang Cheng , You Yang
Published: January 2025

Open source components (OSCs) have become a vital part for developing modern applications. The security of these components could affect the overall security of the software depends on them. Thus, the security of an OSC should be evaluated first before integrating to the software. However, the existing models lack generality, and cannot be easily automatic applied to OSCs developed in different programming language. To this end, we propose a security assessment model for OSCs, called the CRAM, which features generality and automation. The proposed model is constructed under the hypothesis that OSC with a larger and more active community is more likely to disclose more vulnerabilities. And it evaluates the security of OSC from its performance in size as well as activities of open source community and vulnerability disclosures. In the experiment section, we present validation and application experiments. In the validation experiment, we find that the basic hypothesis of the proposed model is valid, and there is a positive correlation between the community size as well as activities and vulnerability risk of OSCs. In the application experiment, we further evaluate our approach with large-scale open source components. Our hypothesis is further validated. The most of OSCs in the ecosystem are in line with the hypothesis. Finally, we successfully build the security baseline according to the hypothesis, and 5 vulnerable OSCs classified as vulnerable by our model are analyzed. The result proves the effectiveness of our model to identify a vulnerable open source ecosystem around the ecosystem.
Artificial Intelligence Management System of Floating Nuclear Reactors for Implementing Remote Distributed Energy Environments
Authors: Alamaniotis Miltiadis
Published: January 2025

This paper explores future energy systems primarily powered by innovative floating reactors. These reactors exhibit high potential, particularly for supplying power to remote areas beyond the reach of traditional power grids. In this study, a novel artificial intelligence (AI) system is introduced to optimize the management of floating reactors in remote, distributed environments, where the reactors must move between different sites and energize their local grids. This research marks the first application of AI in providing management decisions for those reactor types in such distributed assembled environments. Specifically, an intelligent management system has been developed to coordinate the reactor’s operations across various sites. The proposed system leverages fuzzy logic tools, which enable it to account for multiple uncertain factors when making management decisions. The system’s performance is tested through simulated scenarios and benchmarked against a round-robin fixed time method. The results demonstrate the system’s efficiency in delivering both economic and operational benefits.
Absolutely s-pure and dual Kasch rings
Authors: Kourki Farid
Published: January 2025

First we show that a ring [Formula: see text] is right absolutely s-pure if and only if every finitely generated proper left ideal of [Formula: see text] has nonzero right annihilator. Then we define a ring [Formula: see text] to be a right US-ring if it is s-pure, as right [Formula: see text]-module, in every ring extension. Right absolutely s-pure rings are right US-rings and the converse is shown to be true when [Formula: see text] is commutative or right nonsingular. A counterexample is provided to prove that the reverse implication do not hold in general. We also prove that being right absolutely s-pure and being right dual Kasch are independent properties. Moreover, it is shown that these two properties are equivalent in the case when the ring is right and left quasi-duo. Finally, we give answers to two questions raised by Dobbs and Shapiro.
Quantile-Based Spillover Network Analysis of Financial Institutions in Chinese Mainland and Hong Kong
Authors: Yao Yinhong , Chen Zhensong , Chen Wei , Liu Xueyong
Published: January 2025

Strong connection among financial institutions provides more possible channels for information spillovers under different market conditions. Therefore, this paper attempts to comprehensively capture the spillover effects among financial institutions in Chinese mainland and Hong Kong by constructing the spillover networks based on the Quantile Vector AutoRegression (QVAR) model. By taking the stock prices as the representatives of financial institutions, we find that the spillover effects under extremely positive and negative conditions are larger than those under normal conditions. The magnitudes of spillovers are dynamic and show a dramatically upward trend when the market encounters extreme shocks, such as the Sino-US trade friction and the COVID-19 pandemic. The directional spillovers of the financial sector and its subsectors from Chinese mainland to Hong Kong are greater than those from Hong Kong to Chinese mainland, and banking contributes more to the spillovers. In addition, most institutions in Chinese mainland are spillover transmitters, and whether the institutions are net receivers or not varies over shock sizes. These results are essential for risk management in financial institutions in the opening financial markets.
The Best Evaluation Sequence Method and Application Based On Quantum Cognitive Theory
Authors: Yu Wangwang , Liu Xinwang , Zi Yingping
Published: January 2025

In the credit risk evaluation process, considering that the decision maker’s irrational behavior may cause the interference effect between evaluation information, and further decrease the reliability of evaluation results. To solve this problem, the best evaluation sequence method and its application in credit risk evaluation based on quantum cognitive theory is proposed in this paper. First, the quantum cognition theory and the evaluation information given by the decision maker are used to get the interference degree between evaluation information. Second, the interference degree between evaluation information is aggregated to obtain the comprehensive interference degree of each alternative. Third, according to the idea that the greater the comprehensive interference degree of the alternative, the more backward the evaluation sequence of the alternative is, we determine the best evaluation sequence of alternatives. Finally, our proposed method is applied to obtain the best evaluation sequence of commercial bank credit risk.
Developing a Computer Program for Material Selection to be Produced by Additive Manufacturing
Authors: Akay Muhammed , Yurdakul Mustafa , İç Yusuf Tansel
Published: January 2025

In this study, a program called additive manufacturing guide (AM Guide) based on Excel VBA was constructed with a database that contains 401 different materials from 46 main material groups used in AM processes. This program could suggest material selection advice for 14 different material selection criteria for the part to be designed. In addition, the program could suggest seven frequently preferred design parameters or boundary conditions in terms of manufacturability for 21 basic materials in four main material groups. As a result of the study, the developed program (AM Guide) was tested with four case studies from the extant literature and presented the advantage of the material selection for the AM environments. For AM technology to be used effectively and become widespread, it is necessary to have foresight and perspective in terms of material choices. In this context, there is a need for a guide to users on issues such as material selection of the parts to be produced with AM technologies. Three benchmark examples were conducted in this paper. For the first example, the developed AM guide offered 91 different alternative materials against the six alternatives for the same problem from the extant literature. Also, the developed AM guide proposed 134 and 122 different materials for cases 2 and 3, respectively, against 5 and 6 alternatives offered from the extant literature for the same cases.
Can bipartite graph be effective tool for clustering: A self-organizing map-based automated plant disease detection
Authors: Ghosh Aditi , Roy Parthajit
Published: January 2025

An innovative approach for automated plant disease identification has been proposed in this study. The main contribution of this study is the introduction of a bipartite graph-based clustering technique that has been used for image segmentation, a feature extraction methodology using Self-Organizing Map (SOM), and a ray tracing method. Numerous research works have already been done in this area with their respective merits and demerits. But this bipartite graph-based clustering for image segmentation and feature extraction using SOM and ray tracing techniques has not been used in any of these studies as far as we are aware. The core idea behind this clustering technique is to represent similar spatial data points using a bipartite graph and then singular value decomposition has been used on that graph for clustering. It is common to use SOM for clustering. However, in this study, SOM has been used for feature extraction. First, a spatial dependency matrix based on the pixel value of the gray image has been constructed using SOM. Then some statistical features have been computed from this matrix. Using the ray tracing method, the length of the most extended cluster, i.e. the length of the most extended disease-affected patch, and the distribution of the clusters in the image have been computed. The accuracy of our model has been greatly enhanced using these features only. It has been experimented on disease-affected grape leaf images taken from the Plant Village Dataset. This model outperforms state-of-the-art models, which is shown in the experimental findingsresults section. Not only that, the proposed features produce better accuracy rather than using some existing features. This comparison has also been shown in the experimental findings. The result has been validated using K-fold cross-validation. Last, but not the least, these features produce good accuracy using different classifiers also.
On the best n-term approximation for general Wiener-type spaces
Authors: Huang Ying , Chen Liang
Published: January 2025

In this paper, we investigate the best n-term approximation problem for general Wiener-type spaces in the [Formula: see text] sense. Previous work estimated the approximation error under the Bernstein discretization condition, which is often nontrivial to verify, and the constants involved typically lacked explicit quantitative estimates. In this paper, we replace this condition with a simpler condition of Hölder continuity and establish an explicit approximation error bound. As a corollary, we fully resolve an open question regarding the sampling recovery of some Wiener-type space.
A Novel Heuristic for the Generalized Traveling Salesman Problems With Imprecise Cost Matrices
Authors: Dutta Prasanta , Khan Indadul , Basuli Krishnendu , Maiti Manas Kumar
Published: January 2025

A meta-heuristic approach with multiple perturbation rules is proposed to solve the generalized traveling salesman problems in different environments. The proposed approach consists of two phases. The first phase is devoted for the sequencing of the groups and in the second phase one node is selected from each group to minimize the tour cost. In the first stage a group sequence is generated randomly. After that a [Formula: see text]-bit shuffling approach is used to regenerate the new group sequences. In the second phase, for every group sequence several selection rules are used for selecting the nodes/cities from different groups of a particular group sequence. At a regular interval, [Formula: see text]-opt operation is used to update the paths and the corresponding group sequences are updated according to the group elements. The proposed algorithm is capable of solving the problem in crisp as well as different imprecise environments, like fuzzy environment, rough environment, etc. Proper decision making approaches are outlined for decision-making in fuzzy and rough environments. Simulation approaches in fuzzy and rough environments are also presented to deal with the problem for different types of fuzzy and rough estimations. In the crisp environment, the algorithm has been tested using different sizes benchmark test instances from GTSPLIB having sizes upto 226 nodes with 26 groups. There are no benchmark data sets available for the GTSPs in imprecise environments. Test problems in imprecise environments are generated from different benchmark crisp test problems of the GTSPLIB and are used to test the algorithm in the corresponding imprecise environments. It is observed from the numerical illustration and graphical representation that the proposed approach obtains 100% accurate results in all the runs of the algorithm for different seeds of the random number generator for all the considered benchmark test problems under consideration. Another observation is visualized from the table that the algorithm has found multiple optimal paths for some test instances. It can be concluded from the observations that the proposed algorithm is capable of solving the GTSPs in crisp as well as in imprecise environments for a significantly large size problems.
Ethylene Glycol-Based Oxide Tri-Hybrid Nanofluid Flow over a Curved Riga Permeable Medium for the Impact of Thermal Radiation
Authors: Panda Subhajit , Baithalu Rupa , Mishra S. R. , Aly Emad H.
Published: January 2025

In various industries, for advanced cooling, electronic device thermal management, and solar thermal systems ethylene glycol (EG)-based nanofluids are presented as efficient heat transfer agents. The proposed oxide tri-hybrid nanofluids comprising multiple oxide nanoparticles, i.e., Al2O3, TiO2 and SiO2 have significantly enhanced thermal properties and stability compared to mono and binary nanofluids. The current investigation aims at the transportation of heat characteristics of an EG-based tri-hybrid nanofluid over a curved Riga surface filled with a porous substance. The study focuses on thermal radiation effects. Moreover, the Riga plate is a magnetic device with alternating electrodes and magnets that provide a significant electromagnetic forcing mechanism for flow behavior. The designed mathematical model with their dimensional form needs transformation to their corresponding dimensionless form with the utility of similarity rules. Further, a numerical technique based on shooting is employed for the solution of the model for the attainment of physical factors. The physical properties of these factors are presented briefly through graphs followed by a comparative analysis.