bluuebunny/crossref_metadata_2025 huggingface dataset:
Surveillance for donor‐derived infections in Australia
Authors: Opdam Helen Ingrid , Boan Peter , Barry Lucinda , Chapman Jeremy R
Published: June 2024

Background

Systems for quality and safety assurance in organ donation and transplantation are vital, especially those that seek to minimize donor disease transmission. Australia has developed a national vigilance and surveillance system to identify, review, and analyze actual and potential donor‐derived infections and other disease transmissions.

Methods

The system involves notification of incidents to the Australian Organ and Tissue Authority for review by a Vigilance and Surveillance Expert Advisory Committee (VSEAC). The VSEAC grades incidents, O makes recommendations, and issues communications both publicly and to the clinical donation and transplant sector.

Results

Annual notifications have increased since the inception of the system in 2012 until 2022. The vast majority relate to procedural aspects including donor assessment, information/data issues, and the recovery, offer, allocation, preservation and transportation of organs. Possible donor‐derived disease accounted for 19% of all notifications, and those related to possible donor‐derived infection only 12%. The VSEAC, as a result of reviewing these incidents, has made recommendations resulting in revisions to donor screening, organ allocation, packaging and transportation. The review of incidents has led to changes in clinical guidance for increased viral risk donor assessment, testing, and ensuing organ utilization and recipient surveillance. Guidance has also been reviewed for other infectious risks including strongyloides, human T‐lymphotropic virus, and HEV.

Conclusion

The Australian vigilance and surveillance system has enabled national retrospective reporting and evaluation of serious adverse events or reactions to identify trends and inform processes and guidelines, therefore improving the safety of donation and transplantation.

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An Experimental Study of Incremental Buckling-Resistant Inchworm-Type Insertion of Microwire Neural Electrodes
Authors: Yi Dongyang , Landry Nathan , Blake Samuel , Baron John , Chen Lei
Published: June 2024

Chronically implanting microelectrodes for high-resolution action potential recording is critical for understanding the brain. The smallest and most flexible electrodes, most suitable for chronic recordings, are also the most difficult to insert due to buckling against the thin but hard-to-penetrate brain meninges. To address such implantation challenges without introducing further damage to the brain, this paper presents our design and prototype of an inchworm-type insertion device that conducts a grip-feed-release incremental motion for planar microelectrode insertion. To optimize the operating parameters of the developed inchworm insertion device, experimental studies were conducted on the polyvinyl chloride-based brain-mimicking phantom to investigate the effects of (1) incremental insertion depth, (2) inserter drive shaft rotary speed, and (3) the resulting inchworm insertion speed, on the phantom (1) penetration rupture force and (2) dimpling depth at rupture. Analysis showed that all three factors had a statistically significant impact on the rupture force and dimpling depth. A moderate level of the resulting insertion speed yielded the lowest rupture force and dimpling depth at rupture. Low insertion speed levels were associated with higher rupture force while high insertion speeds led to a large variance in dimpling depth and potential insertion failure. To achieve such a moderate insertion speed, it would be preferred for both the incremental insertion depth and the drive shaft rotary speed to be at a moderate level. Such findings lay the foundation for enabling previously impossible buckling-free insertion of miniaturized flexible planar microelectrodes deep into the brain.
Towing an Object With a Rover
Authors: Caruso Matteo , Sesto Gorella Nicholas , Gallina Paolo , Seriani Stefano
Published: June 2024

The present study investigates the problem of towing an object that is lying on a surface in a given workspace and the applicability to a planetary rover with four steering wheels. A quasi-static method has been introduced and used for path planning and for the synthesis of both object and rover trajectories. The rover uses a tether as the towing medium, which is modeled as an elastic unilateral constraint. Moreover, a kinematic model of the rover that includes steering asymmetrical joint limits is taken into account. The dynamics model of the overall system is then derived, and a sensitivity analysis is performed over a finite number of different trajectories, in order to evaluate the quasi-static assumption, the effects of the model, and the influence of the elastic constraint. Finally, experiments have been performed using the novel Archimede rover prototype and compared with dynamics simulations; the remarkable adherence shown with the model validates the overall approach.
Super-resolution spatial spectrum reconstruction under unknown near-field interferences
Authors: Chu Jichen , Cheng Lei , Xu Wen
Published: June 2024

In underwater acoustic signal processing, conventional spatial spectrum estimation and the associated direction-of-arrival estimation are often impaired by strong near-field interferences at the same frequency as the far-field target signal, leading to significant performance degradation and even detection failure. In contrast to prevalent near-field interference suppression algorithms that require prior knowledge of near-field interference positions, this paper proposes a super-resolution spatial spectrum reconstruction algorithm designed for more general scenarios where crucial information about the near-field interference, such as positions and magnitudes, is unknown. The proposed algorithm demonstrates its adaptability in mitigating unknown near-field interference and achieves this by leveraging rank constraint-based relaxation and alternating minimization, resulting in an effective spatial spectrum reconstruction strategy. The efficacy of the proposed spatial spectrum reconstruction method in handling strong near-field interference is confirmed through analysis of simulated and synthetic experimental data. It exhibits superiority over traditional competitors in terms of resolution, denoising capabilities, and estimation accuracy. Moreover, it achieves comparable results to algorithms that utilize prior information about near-field interference positions. The enhanced performance remains consistent even in challenging scenarios such as snapshot deficiency and low signal-to-noise ratios.
A simple BLASTn-based approach generates novel insights into the regulation and biological function of type I toxin-antitoxins
Authors: Shore Selene F. H. , Ptacek Michael , Steen Andrew D. , Fozo Elizabeth M.
Published: June 2024

Bacterial chromosomal type I toxin-antitoxin systems consist of a small protein, typically under 60 amino acids, and a small RNA (sRNA) that represses toxin translation. These gene pairs have gained attention over the last decade for their contribution to antibiotic persistence and phage tolerance in bacteria. However, biological functions for many remain elusive as gene deletions often fail to produce an observable phenotype. For many pairs, it is still unknown when the toxin and/or antitoxin gene are natively expressed within the bacterium. We examined sequence conservation of three type I toxin-antitoxin systems,
tisB/istR-1, shoB/ohsC,
and
zor/orz
, in over 2,000
Escherichia coli
strains, including pathogenic and commensal isolates. Using our custom database, we found that these gene pairs are widespread across
E. coli
and have expression potential via BLASTn. We identified an alternative, dominant sequence variant of TisB and confirmed that it is toxic upon overproduction. Additionally, analyses revealed a highly conserved sequence in the
zorO
mRNA untranslated region that is required for full toxicity. We further noted that over 30% of
E. coli
genomes contain an
orz
antitoxin gene only and confirmed its expression in a representative strain: the first confirmed report of a type I antitoxin without its cognate toxin. Our results add to our understanding of these systems, and our methodology is applicable for other type I loci to identify critical regulatory and functional features.

IMPORTANCE

Chromosomal type I toxin-antitoxins are a class of genes that have gained increasing attention over the last decade for their roles in antibiotic persistence which may contribute to therapeutic failures. However, the control of many of these genes and when they function have remained elusive. We demonstrate that a simple genetic conservation-based approach utilizing free, publicly available data yields known and novel insights into the regulation and function of three chromosomal type I toxin-antitoxins in
Escherichia coli
. This study also provides a framework for how this approach could be applied to other genes of interest.
Triassic granitic magmatism in the Lancangjiang zone in southwestern China associated with Paleo-Tethys evolution and its control on tin mineralization
Authors: Zheng Mingjun , Sun Xiang , Santosh M. , Pei Tong , Xiao Ke , Si Xiaobo , Deng Jun
Published: June 2024

Tin deposits are predominantly associated with granitic rocks, yet the factors controlling tin enrichment in granites remain controversial. Here, we investigated the Daguanshan pluton within the central part of the Lincang batholith in the Lancangjiang zone, southwestern China, representing a northern extension of the Southeast Asian tin belt (spanning Thailand, Malaysia, and Indonesia) as part of the Paleo-Tethyan tectonic realm. The Daguanshan pluton, linked to the Hongmaoling tin deposit, is composed of variably evolved granite units, including hornblende-biotite granite, biotite granite, two-mica granite, and muscovite granite. Zircon U-Pb ages of the Daguanshan granite units range from 235.2 ± 0.7 Ma to 230.3 ± 1.2 Ma, consistent with the cassiterite U-Pb age of 238.2 ± 4.5 Ma for Hongmaoling mineralization. The four granite units have similar zircon εHf(t) values (−11.1 to −5.1) and bulk-rock εNd(t) values (−10.1 to −9.5) and show a magmatic fractionation trend. The less evolved hornblende-biotite granite and biotite granite, characterized as I-type granites, were probably derived from the remelting of early Paleozoic metamorphic igneous rocks in a postcollisional setting. Subsequently, the more evolved two-mica and muscovite granites emerged from these magmas, enriching tin contents from ~3.7 ppm to 25 ppm. Analysis of whole-rock Fe2O3/FeO ratios and zircon oxybarometry indicates that the oxygen fugacity of the less evolved granites was lower than the fayalite + magnetite + quartz (FMQ) buffer, and it decreased further with magma fractionation due to magnetite crystallization. Comparative assessments of the Daguanshan granites and the broader Lincang batholith, alongside Triassic tin granites in Southeast Asia, illuminate a cohesive tectonic origin linked to a collisional setting subsequent to the closure of the Paleo-Tethyan Ocean. These findings highlight the potential for significant tin mineralization within the highly evolved Triassic granites in the Lancangjiang zone.
Do various types of prelacteal feeding (PLF) have different associations with breastfeeding duration in Indonesia? A cross-sectional study using Indonesia Demographic and Health Survey datasets
Authors: Rahmartani Lhuri D , Quigley Maria A , Carson Claire
Published: June 2024

Introduction

Prelacteal feeding (PLF) is anything other than breastmilk given to newborns in the first few days of birth and/or before breastfeeding is established. PLF comes in many forms and is known as a challenge to optimal breastfeeding. Interestingly, both breastfeeding and PLF are common in Indonesia. This study investigated the association between PLF (any PLF, formula, honey, water and other milk) and breastfeeding duration.

Methods

This study used Indonesia Demographic and Health Surveys data from 2002, 2007 and 2017. Sample sizes were 5558 (2007), 6268 (2007) and 6227 (2017) mothers whose last child was aged 0–23 months. We used Cox regression survival analysis to assess the association between PLF and breastfeeding duration, estimating hazard ratios (HR) for stopping earlier.

Results

Overall PLF was prevalent (59%, 67% and 45% in 2002, 2007 and 2017, respectively), with formula being the most common (38%, 50% and 25%). No association between any PLF and breastfeeding duration in 2002 (HR 0.90 (95% CI 0.70 to 1.16)), but in 2007 and 2017, mothers who gave any PLF were more likely to stop breastfeeding earlier than those who did not (HR 1.33 (95% CI 1.11 to 1.61) and 1.47 (95% CI 1.28 to 1.69), respectively), especially in the first 6 months (HR 2.13 (95% CI 1.55 to 2.92) and 2.07 (95% CI 1.74 to 2.47), respectively). This association was more consistent for milk-based PLF. For example, HR in 2017 was 2.13 (95% CI 1.78 to 2.53) for prelacteal formula and 1.73 (95% CI 1.39 to 2.15) for other milk. The associations were inconsistent for the other PLF types. Prelacteal water showed no association while prelacteal honey showed some association with a longer breastfeeding duration in 2002 and 2007.

Conclusion

The impact of PLF on breastfeeding duration varied by type. While this study supports current recommendations to avoid PLF unless medically indicated, the potential consequences of different PLF types on breastfeeding outcomes should be clearly communicated to healthcare providers and mothers. Further research should explore the reasons for the high PLF prevalence in this setting.
Useful or not? The discussion of traditional Chinese medicine to treat COVID-19 on a Chinese social networking site
Authors: Wang Di , Lu Jiahui , Zhou Jiaming , Wong Vincent Kam Wai
Published: June 2024

The use of traditional medicine is a global phenomenon, and the WHO advocated its appropriate integration into modern healthcare systems. However, there is a hot debate about the legitimacy of traditional medicine among the general public. Here, we investigated the debate in the Chinese digital context by analysing 1954 responses related to 100 questions about traditional Chinese medicine (TCM) treatment against COVID-19 on the Zhihu platform. Attitude function theory was applied to understand the reasons underlying public attitudes.

Results showed that Zhihu users generally held a supportive attitude toward TCM. Their attitudes mainly came from their own experience and traditional media. The general users were more negative while medical professionals were more positive toward TCM. Ego defence (eg, derogating evidence sources) was used the most to support attitudes, followed by value expression (eg, believing in science). Supporters showed fewer expressions of faith (eg, the use of TCM is a kind of faith), politics (eg, supporting TCM is about politics) and science value (eg, TCM is a field of science), fewer ego defence, more patriotism and cultural confidence expressions (eg, TCM is a cultural pride) and more knowledge explanation (eg, TCM accelerates the metabolism of phlegm) than expected. Opposers showed fewer utilitarian and knowledge functions, fewer expressions of patriotism and more expressions of faith, politics and economics, but more ego defence functions than expected. Opposing posts were more likely to attract engagement than supporting and neutral posts. Posts that mentioned attitude functions generally attracted more engagement.

Our findings indicate that TCM debate in modern China is not only relevant to medical science and health, but also rooted deeply in cultural ideology, politics and economics. The findings can provide global insights into the development of proactive policies and action plans that will help the integration of traditional medicine into modern healthcare systems.
Widening geographic range of Rift Valley fever disease clusters associated with climate change in East Africa
Authors: Situma Silvia , Nyakarahuka Luke , Omondi Evans , Mureithi Marianne , Mweu Marshal Mutinda , Muturi Matthew , Mwatondo Athman , Dawa Jeanette , Konongoi Limbaso , Khamadi Samoel , Clancey Erin , Lofgren Eric , Osoro Eric , Ngere Isaac , Breiman Robert F , Bakamutumaho Barnabas , Muruta Allan , Gachohi John , Oyola Samuel O , Njenga M Kariuki , Singh Deepti
Published: June 2024

Background

Recent epidemiology of Rift Valley fever (RVF) disease in Africa suggests growing frequency and expanding geographic range of small disease clusters in regions that previously had not reported the disease. We investigated factors associated with the phenomenon by characterising recent RVF disease events in East Africa.

Methods

Data on 100 disease events (2008–2022) from Kenya, Uganda and Tanzania were obtained from public databases and institutions, and modelled against possible geoecological risk factors of occurrence including altitude, soil type, rainfall/precipitation, temperature, normalised difference vegetation index (NDVI), livestock production system, land-use change and long-term climatic variations. Decadal climatic variations between 1980 and 2022 were evaluated for association with the changing disease pattern.

Results

Of 100 events, 91% were small RVF clusters with a median of one human (IQR, 1–3) and three livestock cases (IQR, 2–7). These clusters exhibited minimal human mortality (IQR, 0–1), and occurred primarily in highlands (67%), with 35% reported in areas that had never reported RVF disease. Multivariate regression analysis of geoecological variables showed a positive correlation between occurrence and increasing temperature and rainfall. A 1°C increase in temperature and a 1-unit increase in NDVI, one months prior were associated with increased RVF incidence rate ratios of 1.20 (95% CI 1.1, 1.2) and 1.93 (95% CI 1.01, 3.71), respectively. Long-term climatic trends showed a significant decadal increase in annual mean temperature (0.12–0.3°C/decade, p<0.05), associated with decreasing rainfall in arid and semi-arid lowlands but increasing rainfall trends in highlands (p<0.05). These hotter and wetter highlands showed increasing frequency of RVF clusters, accounting for 76% and 43% in Uganda and Kenya, respectively.

Conclusion

These findings demonstrate the changing epidemiology of RVF disease. The widening geographic range of disease is associated with climatic variations, with the likely impact of wider dispersal of virus to new areas of endemicity and future epidemics.
Understanding the extent of economic evidence usage for informing policy decisions in the context of India’s national health insurance scheme: Ayushman Bharat Pradhan Mantri Jan Aarogya Yojana (PM-JAY)
Authors: Sharma Deepshikha , Chauhan Akashdeep Singh , Guinness Lorna , Mehndiratta Abha , Dhiman Anamika , Singh Malkeet , Prinja Shankar
Published: June 2024

Introduction

Ayushman Bharat Pradhan Mantri Jan Aarogya Yojana (PM-JAY) is one of the world’s largest tax-funded insurance schemes. The present study was conducted to understand the decision-making process around the evolution (and revision) of health benefit packages (HBPs) and reimbursement rates within PM-JAY, with a specific focus on assessing the extent of use of economic evidence and role of various stakeholders in shaping these policy decisions.

Methods

A mixed-methods study was adopted involving in-depth interviews with seven key stakeholders involved in HBP design and reimbursement rates decisions, and a survey of 80 government staff and other relevant stakeholders engaged in the implementation of PM-JAY. The data gathered were thematically analysed, and a coding framework was developed to explore specific themes. Additionally, publicly available documents were reviewed to ensure a comprehensive understanding of the decision-making processes.

Results

Findings reveal a progressive transition towards evidence-based practices for policy decisions within PM-JAY. The initial version of HBP relied heavily on key criteria like disease burden, utilisation rates, and out-of-pocket expenditures, along with clinical opinion in shaping decisions around the inclusion of services in the HBP and setting reimbursement rates. Revised HBPs were informed based on evidence from a national-level costing study and broader stakeholder consultations. The use of health economic evidence increased with each additional revision with consideration of health technology assessment (HTA) evidence for some packages and reimbursement rates based on empirical cost evidence in the most recent update. The establishment of the Health Financing and Technology Assessment unit further signifies the use of evidence-based policymaking within PM-JAY. However, challenges persist, notably with regard to staff capacity and understanding of HTA principles, necessitating ongoing education and training initiatives.

Conclusion

While substantial progress has been made in transitioning towards evidence-based practices within PM-JAY, sustained efforts and political commitment are required for the ongoing systematisation of processes.
Study of self-bound compact stars in $$f(\mathscr {T})$$ gravity and observational constraints on the model parameters
Authors: Maurya S. K. , Chaudhary Himanshu , Ditta Allah , Mustafa G. , Ray Saibal
Published: June 2024

The present study is based on $$f(\mathscr {T})$$

f
(
T
)

gravity, where we impose possible observational constraints on the model parameters to obtain physically plausible features of compact stars, specifically neutron stars. To do so, as a first step, we consider the field equations in the $$f(\mathscr {T})$$

f
(
T
)

gravity framework. We then solve the field equations to generate a set of new exact solutions in $$f(\mathscr {T})$$

f
(
T
)

gravity where model parameters are found by using boundary conditions. A few tests are performed to asses the stability of the model and compare the obtained results with observations of compact stars, in particular with the compact binary merger event GW190814. We observe the maximum mass of the star beyond the $$3M_{\odot }$$

3

M
⊙

when the surface density is of the order $$10^{14}$$

10
14

gm/cm$$^3$$

3

for the higher torsion parameter, which implies that an anisotropic solution in teleparallel gravity is more suitable for modeling of massive compact objects in lower $$mass-gap$$

m
a
s
s
-
g
a
p

, and thus the model presented herein provides a satisfactory physical scenario with respect to the observational signature.
Euler–Heisenberg black hole surrounded by perfect fluid dark matter
Authors: Ma Shi-Jie , Wang Rui-Bo , Deng Jian-Bo , Hu Xian-Ru
Published: June 2024

A generation method of new metric in the case of static spherically symmetric space-time is derived. Using this approach, we construct a metric which describes Euler–Heisenberg black hole surrounded by perfect fluid dark matter and investigate its optical and thermodynamic properties. We found that radius of shadow will increase with the increase of dark matter effect, and more strong dark matter will diminish the light intensity of accretion disk generally. Moreover, in thermodynamics, when quantum electrodynamic parameter is positive, there will be a critical value of dark matter parameter, which determine the number of black hole’s critical points.
SMEFT chromomagnetic dipole operator contributions to $$t{{\bar{t}}}$$ production at approximate NNLO in QCD
Authors: Kidonakis Nikolaos , Tonero Alberto
Published: June 2024

We study higher-order QCD corrections for the production of a top–antitop quark pair ($$t{{\bar{t}}}$$

t

t

¯

production) at the Large Hadron Collider in the Standard Model Effective Field Theory. We consider effects of new physics parametrized by the top-quark chromomagnetic dipole operator. We calculate new physics contributions to the total cross section at approximate NNLO, with second-order soft-gluon corrections added to the complete NLO result, including uncertainties from scale dependence and from parton distributions. We also calculate new physics contributions at approximate NNLO for differential distributions in top-quark transverse momentum.
Influence of quantum correction on the Schwarzschild black hole polarized image
Authors: Guo Sen , Huang Yu-Xiang , Liu Kuan , Liang En-Wei , Lin Kai
Published: June 2024

Using a model of an accretion disk around a Schwarzschild black hole, the analytic estimates for image polarization were derived by Narayan et al. (Astrophys J 102:912, 2021). Recently, the EHT team also obtained polarization images of the Sgr A$$^{*}$$

∗

and measured both linear and circular polarization (Astrophys J Lett 964:L25, 2024). We find that quantum correction effects can also influence polarization information. Considering the quantum corrected Schwarzschild black hole (Kazakov–Solodukhin black hole), we derive the polarization intensity of the target black hole and investigate polarization images under different parameters. It is found that a larger quantum deformation leads to an expansion of the polarization region, while the polarization intensity value decrease. Under different observation angles, magnetic fields, fluid direction angles, and fluid velocity conditions, we also derive polarization images of corrected black holes. These key indicators not only affect the intensity of polarization but also the direction of polarization. We establish the relationship between polarization intensity and quantum correction deformation parameters, revealing a gradual decline in polarization intensity with reduced radius and an anti-polarization behavior induced by the progressive increase in deformation parameters at a constant radius. Our analysis may provide observational evidence for quantum effect of general relativity.
Motion of particles around a magnetically charged Euler–Heisenberg black hole with scalar hair and the Event Horizon Telescope
Authors: Theodosopoulos Dionysios P. , Karakasis Thanasis , Koutsoumbas George , Papantonopoulos Eleftherios
Published: June 2024

We study the motion of uncharged particles and photons in the background of a magnetically charged Euler–Heisenberg (EH) black hole (BH) with scalar hair. The spacetime can be asymptotically (A)dS or flat. After investigating particle motions around the BH and the behavior of the effective potential of the particle radial motion, we determine the contribution of the BH parameters to the geodesics. Photons follow null geodesics of an effective geometry induced by the corrections of the EH non-linear electrodynamics. Thus, after determining the effective geometry, we calculate the shadow of the BH. We also analyze in detail the case of extremal BH spacetimes and we find that the radius of both the event horizon and shadow exhibits discontinuities when varying with respect to either the magnetic charge or the scalar charge. These extremal scenarios exist for sufficiently small values of the EH parameter, and imply the formation of a second photon ring around the BH shadow. Upon comparing the theoretically calculated BH shadow to the images of the shadows of M87* and Sgr A* observed by the Event Horizon Telescope collaboration, we impose constraints on the BH parameters, namely the scalar hair ($$\nu $$
ν
), the magnetic charge ($$Q_{m}$$

Q
m

) and the EH parameter ($$\alpha $$
α
). For sufficiently large values of the EH parameter, our model is in agreement with the EHT observations for approximately every value for the BH magnetic charge.
Effects of route guidance strategies on traffic emissions in urban traffic networks
Authors: Zhang Wanning , Chen Yaohui , Zhang Kai , Chen Bokui
Published: June 2024

Urban traffic emissions have significant environmental and health implications. Diverging from traditional research that primarily aims to improve traffic flow and efficiency, this study specifically focuses on the environmental impact on traffic emissions, conducting a comprehensive analysis within the Manhattan urban network through four route guidance strategies. The performance of these strategies is examined across various vehicle densities, and their impact on four traffic pollutant emissions (Carbon-dioxide, Nitrogen Oxides, Volatile Organic Compounds and Particulate Matter) is assessed. Moreover, our innovative approach analyzes emissions from the perspectives of both travel distance and trip frequency, placing special emphasis on trip frequency to provide practical insights with high real-world applicability. The results highlight the potential and limitation of the Congestion Coefficient Strategy. Under equal travel demands, the Congestion Coefficient Strategy showed promise in reducing carbon emissions. However, at lower vehicle densities, it led to a significant increase in emissions. This revelation pointed to the need for modifications to the strategy when applied in scenarios with lower traffic density. Recognizing this limitation, we introduced a modified strategy that achieved remarkable reductions in emissions across diverse vehicle densities, effectively overcoming the challenges posed by the original Congestion Coefficient Strategy. These findings offer valuable insights for policymakers and transportation planners in selecting optimal route guidance strategies to reduce pollutant emissions. Future studies will explore the efficacy of these strategies in road networks characterized by different topological configurations.
Soliton waves with optical solutions to the three-component coupled nonlinear Schrödinger equation
Authors: Ali Karmina K. , Yusuf Abdullahi
Published: June 2024

This study uses the modified Sardar sub-equation method to find novel soliton solutions to the nonlinear three-component coupled nonlinear Schrödinger equation (NLSE), which is used for pulse propagation in nonlinear optical fibers. Multi-component NLSE equations are widely used because they can represent a wide range of complex observable systems and more dynamic patterns of localized wave solutions. The optical solutions proposed in this study are novel and can be described using hyperbolic, trigonometric, and exponential functions. These solutions are categorized as bright, dark, singular, combo bright-singular, and periodic solutions. Some solutions’ dynamic behaviors are demonstrated by selecting appropriate physical parameter values. The results and computational analysis indicate that the techniques provided are simple, effective, and adaptable. They can be applied to a variety of nonlinear evolution equations, whether stable or unstable, and can be used in fields such as mathematics, mathematical physics, and applied sciences.
Investigation of dark energy scenarios in f(Q) gravitation theory
Authors: Jalali Samira , Aygün Sezgin
Published: June 2024

In order to solve the mystery of the accelerating and expanding universe model first, various dark energy candidates, such as Quintessence, Tachyon, k-essence, Phantom and DBI-essence, were investigated in detail in the [Formula: see text] modified symmetric teleparallel gravitation theory for homogeneous and isotropic FRLW universe model. The [Formula: see text] model is used to obtain solutions in [Formula: see text] theory. Also, the physical behaviors of some cosmological parameters such as pressure and density were studied. Dark energy candidates were analyzed for different values of n with various graphs.
Hopf Bifurcation and Turing Instability of a Delayed Diffusive Zooplankton–Phytoplankton Model with Hunting Cooperation
Authors: Meng Xin-You , Xiao Li
Published: June 2024

In this paper, a diffusive zooplankton–phytoplankton model with time delay and hunting cooperation is established. First, the existence of all positive equilibria and their local stability are proved when the system does not include time delay and diffusion. Then, the existence of Hopf bifurcation at the positive equilibrium is proved by taking time delay as the bifurcation parameter, and the direction of Hopf bifurcation and the stability of bifurcating periodic solutions are investigated by using the center manifold theorem and the normal form theory in partial differential equations. Next, according to the theory of Turing bifurcation, the conditions for the occurrence of Turing bifurcation are obtained by taking the intraspecific competition rate of the prey as the bifurcation parameter. Furthermore, the corresponding amplitude equations are discussed by using the standard multi-scale analysis method. Finally, some numerical simulations are given to verify the theoretical results.
Constructing and Realising an Employment Platform for Slash Youth in the Age of Digital Intelligence
Authors: Xiang Xue
Published: June 2024

The current employment environment is becoming increasingly complex, with many job seekers competing with each other in more concentrated and narrower fields, worsening the job market as well as inhibiting the career potential of job seekers. There is a need to provide better employment guidance and employment quality assessment for slash youth. This study attempts to design a job recommendation model for slash youths by combining an improved collaborative filtering algorithm and a dynamic bilateral matching algorithm (BMA). The test results show that the precision rate of the BMA is always the largest with the increase of the number of clusters, with the highest value reaching 90.04%; the average ranking inverse curve of bilateral matching has the fastest growth rate, with the maximum value of 62.04%, which is 34.26% and 10.06% higher than the other two maximum values, and the optimal number of clusters is set to 24. The highest precision rate of the algorithm is 82.17% when the number of recommendations is 10. The algorithm also performed better in terms of recommendation diversity, with a maximum value of around 0.28. The recommendation success rate and satisfaction value reached 87.72% and 47.86%, respectively. The recommendation precision of the model designed in this study is high. It is conducive to solving problems such as difficulty in recruiting and finding jobs, and promotes the healthy development of the recruitment market.
Domain wall and holographic dark energy in f(Q) theory of gravity
Authors: Hatkar S. P. , Tadas D. P. , Katore S. D.
Published: June 2024

In this paper, we have studied the flat Friedmann–Robertson–Walker (FRW) space time with domain wall and holographic dark energy in the context of [Formula: see text] theory of gravity. The exact solutions of the field equations are obtained using two different forms of varying deceleration parameters: (i) [Formula: see text] and (ii) [Formula: see text]. It is observed that the universe is accelerating and expanding. Furthermore, we have also discussed some physical parameters of the investigated model.
Ruled surfaces obtained by infinitesimal bendings of curves in Minkowski 3-space
Authors: Han Hyelim , Shin An Sook , Jang Youngsong
Published: June 2024

In this paper, we define a ruled surface obtained by an infinitesimal bending of a curve in Minkowski [Formula: see text]-space. We also characterize such ruled surfaces according to causal characters of the curve. Furthermore, we find appropriate conditions of ruled surfaces obtained by infinitesimal bendings of curves to be (lightlike) developable, in particular, cylindrical or conical in Minkowski [Formula: see text]-space, with examples presented.
Markov Chains to Explore the Nanosystems for the Biophysical Studies of Cancers
Authors: Al-Utaibi Khaled A. , Nutini Alessandro , Sait Sadiq M. , Iqbal S.
Published: June 2024

The immune response is essential for the human body to function well and to survive against the sudden and chronic diseases such as viral & bacterial infections and cancers. In the immunosurveillance process, Natural Killer (NK) cells are one of the main elements in controlling the development of such infections and, for this reason, they have become the subject of “in-depth” studies especially for the application of new forms of immunotherapy. NK cells can rapidly destroy both autologous and tumor cells in vitro and for this reason the interest in their function is increasingly growing. Their presence in the tumor micro-environment (TME) also assumes prognostic value since the repertoire of NK cell receptors has been linked to anti-tumor function. In this work, a Markov chain modeling approach is proposed to analyze the network of interactions that NK cells carry out with other immune elements in the defense against cancer such as CD4+ cells and CD8+ cells and dendritic cells (DCs) that activate and enhance immune responses. The probabilistic approach used is promising since it helps to understand the balance and the communication in the micro-environment, in a realistic manner. The advantage of discrete time Markov chain approach is that, it can be further extended to complex networks using the state-of-the-art algorithms and can also be translated for the novel AI tools for the cytokines and protein databases.
On Challenges of Monocular Pose Estimation for Endoluminal Navigation
Authors: Mackutė Emilė , Abdalla Ahad , Dickson Stuart , Dhaliwal Kevin , Khadem Mohsen
Published: June 2024

Accurate endoscope navigation is vital for precise sampling and drug delivery during endoluminal procedures. Current systems rely on sensorized endoscopes for real-time bronchoscope tracking, but they are costly and require specialised settings. Camera pose estimation offers an alternative for endoscope motion tracking and navigation. In this study, we assess state-of-the-art monocular pose estimation methods for endoluminal navigation. We analyze multiple datasets and diverse feature tracking frameworks, including SIFT, ORB, BRISK, FREAK, AKAZE, SuperPoint, LoFTR, and EndoSfMLearner. Our findings reveal that, while modern deep learning-based feature detectors like SuperPoint and LoFTR yield denser features compared to traditional methods, their overall quality and reliability remain suboptimal. This insight is crucial for understanding the limitations of current monocular odometry in endoluminal environments. We also emphasize the challenges in generalizing learned frameworks developed for other odometry applications to endoscopic applications, stressing the need for more publicly available datasets. To fill this gap, we introduce a clinical bronchoscopy dataset with ground truth camera pose data. This dataset serves as a realistic benchmark for improving feature-based odometry in surgical navigation and encourages tailored framework development for learned pose estimation in endoluminal interventions.
Generating Hidden Markov Models from Process Models Through Nonnegative Tensor Factorization
Authors: Skau Erik , Hollis Andrew , Eidenbenz Stephan , Rasmussen Kim , Alexandrov Boian
Published: June 2024

Monitoring of industrial processes is a critical capability in industry and in government to ensure reliability of production cycles, quick emergency response, and national security. Process monitoring allows users to gauge the progress of an organization in an industrial process or predict the degradation or aging of machine parts in processes taking place at a remote location. Similar to many data science applications, we usually only have access to limited raw data, such as satellite imagery, short video clips, event logs, and signatures captured by a small set of sensors. To combat data scarcity, we leverage the knowledge of Subject Matter Experts (SMEs) who are familiar with the actions of interest. SMEs provide expert knowledge of the essential activities required for task completion and the resources necessary to carry out each of these activities. Various process mining techniques have been developed for this type of analysis; typically such approaches combine theoretical process models built based on domain expert insights with ad-hoc integration of available pieces of raw data. Here, we introduce a novel mathematically sound method that integrates theoretical process models (as proposed by SMEs) with interrelated minimal Hidden Markov Models (HMM), built via nonnegative tensor factorization. Our method consolidates: (a) theoretical process models, (b) HMMs, (c) coupled nonnegative matrix-tensor factorizations, and (d) custom model selection. To demonstrate our methodology and its abilities, we apply it on simple synthetic and real-world process models.
Limits and Difficulties in the Design of Under-Approximation Abstract Domains
Authors: Ascari Flavio , Bruni Roberto , Gori Roberta
Published: June 2024

The main goal of most static analyses is to prove the
absence of bugs
: if the analysis reports no alarms, then the program will not exhibit any unwanted behaviours. For this reason, they are designed to over-approximate program behaviours and, consequently, they can report some
false
alarms. O’Hearn’s recent work on incorrectness has renewed the interest in the use of under-approximations for
bug finding
, because they only report
true
alarms. In principle, Abstract Interpretation techniques can handle under-approximations as well as over-approximations, but, in practice, few attempts were developed for the former, notwithstanding the much wider literature on the latter. In this article, we investigate the possibility of exploiting under-approximation abstract domains for bug-finding analyses. First we restrict to consider concrete powerset domains and highlight some intuitive asymmetries between over- and under-approximations. Then, we prove that the effectiveness of abstract domains defined by under-approximation Galois connection is limited because the analysis is likely to return trivial results whenever common transfer functions are encoded in the program. To this aim, we introduce the original concepts of
non-emptying functions
and
highly surjective function family
, and we prove the nonexistence of abstract domains able to under-approximate such functions in a non-trivial way. We show many examples of finite and infinite numerical domains, as well as other generic domains. In all such cases, we prove the impossibility of performing non-trivial analyses via under-approximation Galois connections.
A Framework for Enhancing Social Media Misinformation Detection with Topical-Tactics
Authors: Bagozzi Benjamin E. , Goel Rajni , Lugo-de-Fabritz Brunilda , Knickmeier-Cummings Kelly , Balasubramanian Karthik
Published: June 2024

Recent years have seen advancements in machine learning methods for the detection of misinformation on social media. Yet, these methods still often ignore or improperly incorporate key information on the topical-tactics used by misinformation agents. To what extent does this affect the (non)detection of misinformation? We investigate how supervised machine learning approaches can be enhanced to better detect misinformation on social media. Our aim in this regard is to enhance the abilities of academics and practitioners to understand, anticipate, and preempt the sources and impacts of misinformation on the web. To do so, this article leverages a large sample of verified Russian state-based misinformation tweets and non-misinformation tweets from Twitter. It first assesses standard supervised approaches for detecting Twitter-based misinformation both quantitatively (with respect to classification) and qualitatively (with respect to topical-tactics of Russian misinformation). It then presents a novel framework for integrating topical-tactics of misinformation into standard “bag of words”-oriented classification approaches in a manner that avoids data leakage and related measurement challenges. We find that doing so substantially improves the out-of-sample detection of Russian state-based misinformation tweets.
Achieving Tunable Erasure Coding with Cluster-Aware Redundancy Transitioning
Authors: Zhang Feng , Nan Fulin , Xu Binbin , Shen Zhirong , Zhai Jiebin , Kalplun Dmitrii , Shu Jiwu
Published: June 2024

Erasure coding has been demonstrated as a storage-efficient means against failures, yet its tunability remains a challenging issue in data centers, which is prone to induce substantial cross-cluster traffic. In this article, we presentClusterRT, a cluster-aware redundancy transitioning approach that can dynamically tailor the redundancy degree of erasure coding in data centers.ClusterRTformulates the data relocation as the maximum flow problem to reduce cross-cluster data transfers. It then designs a parity-coordinated update algorithm, which gathers the parity chunks within the same cluster and leverages encoding dependency to further decrease the cross-cluster update traffic.ClusterRTfinally rotates the parity chunks to balance the cross-cluster transitioning traffic across the data center. Large-scale simulation and Alibaba Cloud ECS experiments show thatClusterRTreduces 94.0% to 96.2% of transitioning traffic and reduces 70.4% to 88.4% of transitioning time.
Plant-Driven Assembly of Disease-Suppressive Soil Microbiomes
Authors: Spooren Jelle , van Bentum Sietske , Thomashow Linda S. , Pieterse Corné M. J. , Weller David M. , Berendsen Roeland L.
Published: June 2024

Plants have coevolved together with the microbes that surround them and this assemblage of host and microbes functions as a discrete ecological unit called a holobiont. This review outlines plant-driven assembly of disease-suppressive microbiomes. Plants are colonized by microbes from seed, soil, and air but selectively shape the microbiome with root exudates, creating microenvironment hot spots where microbes thrive. Using plant immunity for gatekeeping and surveillance, host-plant genetic properties govern microbiome assembly and can confer adaptive advantages to the holobiont. These advantages manifest in disease-suppressive soils, where buildup of specific microbes inhibits the causal agent of disease, that typically develop after an initial disease outbreak. Based on disease-suppressive soils such as take-all decline, we developed a conceptual model of how plants in response to pathogen attack cry for help and recruit plant-protective microbes that confer increased resistance. Thereby, plants create a soilborne legacy that protects subsequent generations and forms disease-suppressive soils.
Theories for Understanding the Effect of Impact Assessment and Project Evaluation on the Practice of Science
Authors: McRoberts Neil , Brinker Samuel , Coleman Kaity
Published: June 2024

We examine the phenomenon of impact assessment in the practice of scientific research, paying attention to the context in which project evaluation is used in federally funded research on plant health in the United States. Our analysis, which is derived from systems theory, carries out a particular view of the research process. For the purposes of this review, our use of the term systems theory references the body of interdisciplinary work that deals with the organization and function of complex structures in nature and human society. Key concepts in this body of theory are that both the components and the interactions among components are important in understanding behavior and that, frequently, systems are seen to be hierarchical in structure. The aim of our analysis is to bring to the attention of the plant health community several concepts from the social sciences that might help in understanding how researchers have responded to the increased expectations from funders to provide project evaluations and impact assessments. We generate a synthesis of these theories, which have not previously been used in a unified way, to explain choices in response to newly imposed goals. Although our analysis is motivated by a specific disciplinary focus on plant health, the issues we discuss are general. Thus, we hope the review is useful to a wide range of scientists, science program managers, and policymakers.