bluuebunny/crossref_metadata_2025 huggingface dataset:
How combined pairwise and higher-order interactions shape transient dynamics
Authors: Chatterjee Sourin , Nag Chowdhury Sayantan
Published: October 2024

Understanding how species interactions shape biodiversity is a core challenge in ecology. While much focus has been on long-term stability, there is rising interest in transient dynamics—the short-lived periods when ecosystems respond to disturbances and adjust toward stability. These transitions are crucial for predicting ecosystem reactions and guiding effective conservation. Our study introduces a model that uses convex combinations to blend pairwise and higher-order interactions (HOIs), offering a more realistic view of natural ecosystems. We find that pairwise interactions slow the journey to stability, while HOIs speed it up. Employing global stability analysis and numerical simulations, we establish that as the proportion of HOIs increases, mean transient times exhibit a significant reduction, thereby underscoring the essential role of HOIs in enhancing biodiversity stabilization. Our results reveal a robust correlation between the most negative real part of the eigenvalues of the Jacobian matrix associated with the linearized system at the coexistence equilibrium and the mean transient times. This indicates that a more negative leading eigenvalue correlates with accelerated convergence to stable coexistence abundances. This insight is vital for comprehending ecosystem resilience and recovery, emphasizing the key role of HOIs in promoting stabilization. Amid growing interest in transient dynamics and its implications for biodiversity and ecological stability, our study enhances the understanding of how species interactions affect both transient and long-term ecosystem behavior. By addressing a critical gap in ecological theory and offering a practical framework for ecosystem management, our work advances knowledge of transient dynamics, ultimately informing effective conservation strategies.
A quality improvement project to increase treatment rates of osteoporosis in general practice
Authors: Bolton Patrick , Seibel Markus , Moses Daniel , Moore Michael , Goodger Brendan
Published: October 2024

Objective This study tests a model to improve the management of patients with an osteoporotic fracture. Methods Patients with fractures potentially due to osteoporosis were identified from imaging reports using computerised near natural language processing. A coordinator notified the referring GP about the finding and provided follow-up to remind GPs of the need for management. This provided an opportunity to assess action taken by the GP. Results Near natural language processing efficiently detected fractures in patients at risk of osteoporosis. GPs reported that they are managing osteoporosis in over 40% of patients identified. Notification of GPs coincided with a small increase in osteoporosis management. Conclusion Information technology can identify patient populations with clinically important risks such as osteoporosis. Methods to engage GPs to optimally address this risk have yet to be developed.
Estimating the true number of people with acute rheumatic fever and rheumatic heart disease from two data sources using capture–recapture methodology
Authors: Thandrayen Joanne , Stacey Ingrid , Oliver Jane , Francia Carl , Katzenellenbogen Judith M. , Wyber Rosemary
Published: October 2024

Objective In Australia, accurate case ascertainment of acute rheumatic fever (ARF) and rheumatic heart disease (RHD) diagnoses for disease surveillance and control purposes requires the use of multiple data sources, including RHD registers and hospitalisation records. Despite drawing on multiple data sources, the true burden of ARF/RHD is likely to be underestimated. Methods This study used capture–recapture methods to quantify the missing number of ARF/RHD cases in data from hospitals and jurisdictional RHD registers. Linked datasets comprised reported cases of ARF/RHD in register records and administrative hospital data. Results Capture–recapture analyses indicated the total number of new ARF/RHD cases in three Australian jurisdictions (Queensland, South Australia and Western Australia), among people aged 3–54 years, was 3480 (95% CI = 3366–3600) during 2011–2016. This included 894 (25.7%) individuals who were not listed in either the hospital or register datasets. Non-Indigenous, urban and older people with ARF/RHD were least likely to be identified in either the hospital or register data sources. Conclusions The 894 likely ARF/RHD cases our analyses detected that are not included in the routine surveillance datasets are concerning and quantify the magnitude and characteristics of under-notification to RHD registers in Australia, especially for groups that are not typically at high risk of ARF.
How the vertical gradient of light in the understorey and water seasonality affect leaf traits of Vanilla phaeantha (Orchidaceae), a crassulacean acid metabolism (CAM) hemiephyte
Authors: Buss Aldineia , Silva Wesley Costa , Costa Vladimir Eliodoro , Moreira Ana Silvia Franco Pinheiro
Published: October 2024

Structural and physiological leaf traits and their plasticity were compared in the hemiepiphyte Vanilla phaeantha. This species grows along a phorophyte reaching different understorey positions and exhibiting diverse responses to environment changes. We analysed three height strata above the ground, establishing a light gradient, and considering seasonal water fluctuations. The upper leaves had higher area and mass and were less pigmented. The dry season induced a reduction of approximately 2 h of stomatal opening over the diel 24 h crassulacean acid metabolism (CAM) cycle in the leaves at all understorey positions. The leaves more exposed to sunlight were larger with higher titratable acidity during the rainy season, while the leaves near the ground maintained the same rates of stomatal conductance and nocturnal acidification between seasons, with lowest values of carbon isotopes in the rainy season. Our research showed that some structural leaf traits (such as specific leaf mass, biomass, and saturated water content) are sensitive to variation in understorey position. In contrast, other physiological traits (stomatal conductance, transpiration, and fluorescence parameters) are more sensitive to seasonal variations. The results are a novelty in assessing the variation of CAM along the same plant in a height gradient and under field conditions.
Anticausativization in Gyalrongic languages
Authors: Gates Jesse P.
Published: October 2024

This article presents a comprehensive survey of anticausativization within Gyalrongic languages, a group of
Sino-Tibetan languages spoken in Sichuan, China, contributing significantly to our understanding of this phenomenon’s theoretical
and diachronic underpinnings. The research affirms that anticausative alternation is predominantly associated with verbs that
exhibit a change of state semantics. This categorization includes decausative and autocausative verbs, further subdivided in
Gyalrongic languages into specific semantic groups such as Separation, Removal, Physical Transformation, etc. Certain verbs with
agent-oriented meanings also undergo anticausative alternation, calling for a revision of previous claims. Gyalrongic languages
demonstrate a unique trend in their use of anticausative marking, deviating from global patterns by avoiding the polyfunctional
employment of these markers. The article traces the origins of anticausative marking to a spontaneous / non-volitional action
prefix and identifies the emergence of a new non-volitional prefix that has overtones of anticausative marking, descending from an
orientational / TAME prefix.
Metric reconstruction in Kerr spacetime
Authors: Hollands Stefan , Toomani Vahid
Published: October 2024

Metric reconstruction is the general problem of parameterizing GR in terms of its two “true degrees of freedom” e.g., by a complex scalar “potential”—in practice mostly with the aim of simplifying the Einstein equation (EE) within perturbative approaches. In this paper, we re-analyze the metric reconstruction procedure by Green, Hollands, and Zimmerman (GHZ) [Class. Quant. Grav. 37, 075001 (2020)], which is a generalization of the Chrzanowski-Cohen-Kegeles (CCK) approach. Contrary to the CCK method, that by GHZ is applicable not only to the vacuum, but also to the sourced linearized Einstein equation (EE) on Kerr. Our main innovation is a version of the GHZ integration scheme that is suitable for the initial value problem of the sourced linear EE. By iteration, our scheme gives the metric to as high an order in perturbation theory as one might wish, in principle. At each order, the metric perturbation is a sum of a corrector, obtained by solving a triangular system of transport equations, a reconstructed piece, obtained from a Hertz potential as in the CCK approach, and an algebraically special perturbation, determined by the ADM quantities. As a byproduct, we determine the precise relations between the asymptotic tail of the Hertz potential in the GHZ and CCK schemes, and the quantities relevant for gravitational radiation, namely, the energy ﬂux, news- and memory tensors, and their associated BMS-supertranslations. We also discuss ways of transforming the metric perturbation to Lorenz gauge.
Effects of pulse rise time and pulse width on discharge mode transition of SDBD plasma under repetitive pulses
Authors: Sun Zihan , Zheng Xinlei , Zheng Haotian , Zhao Zheng , Li Jiangtao
Published: October 2024

Affected by environmental states and power supply parameters, the discharge mode of surface dielectric barrier discharge (SDBD) plasma may gradually transfer from O3 mode to NO
x
mode, resulting in various gas-phase species for different applications. Despite the intensive study of attempts to control this discharge mode transition by changing discharge conditions and power excitations in recent years, the effects of the pulse rise time and the pulse width on the discharge mode transition have not been discussed. In the present study, a SDBD was excited by repetitive pulses with different pulse rise times or pulse widths, and the time-varying concentrations of key long-lived species (O3 and NO2) were quantified. The results demonstrated that it was possible to modulate the discharge mode by adjusting pulse rise time/pulse width. The quenching of O3 was observed to occur at a faster rate and the mode transition was noted to occur at an earlier point in time as the pulse rise time decreased from 225 ns to 125 ns and the pulse width increased from 0.5 μs to 4 μs. The employment of a zero-dimensional model for the analysis of plasma chemical kinetics revealed that the reduction in pulse rise time and the prolongation of pulse width resulted in an increase in the mean vibrational energy of N2(v) and a more rapid electrode temperature rise caused by plasma heating. The former enhanced the generation of NO, while the latter accelerated the thermal decomposition of O3, thereby promoting the speed of mode transition.
A point cloud segmentation algorithm based on multi-feature training and weighted random forest
Authors: Zhao Fuqun , Huang He , Xiao Nana , Yu Jiale , Geng Guohua
Published: October 2024

Point cloud segmentation is the process of dividing point cloud data into a series of coherent subsets according to its attributes. It has been widely used in target recognition, digital protection of cultural relics, medical research and other fields. To improve the classification accuracy of point cloud and achieve accurate segmentation of objects or scenes, a point cloud segmentation algorithm based on multi–features training and weighted random forest (RF) is proposed. Firstly, the feature vector composed of 3D coordinate value, RGB value, echo intensity, point cloud density, normal direction and average curvature is used to train the SVM classifier, and the ‘one–to–one’ strategy is adopted to achieve the initial multivariate rough segmentation of point cloud. Then, the maximum information coefficient and sample correlation coefficient (SCC) are used to evaluate the correlation of the decision tree, and the decision tree is weighted accordingly to build a weak correlation weighted RF, so as to achieve further accurate segmentation of the point cloud. The experiment verifies the effectiveness of the proposed algorithm by segmenting the outdoor scene point cloud data model. The results show that the segmentation algorithm based on multi–features training and weighted RF can achieve accurate point cloud segmentation, and is an effective point cloud segmentation method.
Remaining useful life prediction method for jointless track circuits based on multivariate feature fusion and nonlinear Wiener process
Authors: Li Qian , Lin Junting , Niu Pengyuan
Published: October 2024

Predicting the remaining useful life (RUL) of track circuits is essential to ensure the safe and reliable operation of high-speed railways. In response to the challenges faced by current machine-learning-based RUL prediction methods, which struggle to represent the uncertainty in the probability distribution of RUL predictions, this paper suggests a hybrid-driven method for estimating remaining life. Firstly, the track circuit Health Index is constructed by feature dimensionality reduction and fusion of the original multivariate monitoring data through kernel principal component analysis and Autoencoder; Secondly, the degraded state of the rail circuit is modelled using a nonlinear Wiener degradation model. Finally, the principle of first hitting time is used to derive the probability density function of the anticipated RUL. The efficacy and superiority of the approach presented in this paper are validated by experimental research on the track circuit monitoring dataset. The method enhances forecast accuracy and reduces prediction uncertainty, offering robust technical support for track circuit maintenance decision-making.
Cylinder object 6-DOF pose estimation via single perspective circle on cylindrical surface
Authors: Yu Aidi , Wang Yujia , Guo Bing , Li Haoyuan
Published: October 2024

Pose estimation is an important research topic in computer vision. In this paper, a novel method for six-degree-of-freedom (6–DOF) pose estimation of cylindrical objects via a single perspective circle on cylindrical surface is proposed. Unlike traditional methods that rely on planar circular features, a circular feature target which is affixed to the side of cylindrical objects is utilized. The geometric properties of the spatial curve formed by its contour are leveraged for pose estimation. Specifically, the imaging model of the spatial curve is established to derive the general equation of its projection curve. The initial pose is determined based on the perspective principle, and the final optimized pose is obtained with the least squares method. To avoid local optima, a verification and correction method is proposed to enhance estimation accuracy. Synthetic and physical experiments demonstrate that the proposed method can achieve real-time, high-precision pose estimation for cylindrical objects, exhibiting robustness against occlusion and noise interference.
Underwater point cloud transmission framework: hybrid encoder implementation based on CNN and transformer
Authors: Deng Zexi , Zhang Yang , Yang Hongbo , Wang He
Published: October 2024

In underwater multi-robot systems, 3D point cloud data generated by sonar and depth sensors facilitates the execution of more complex collaborative tasks among robots, which partly rely on efficient data transmission. In this work, we propose a hybrid encoder framework based on convolutional neural network and Transformer for underwater point cloud transmission, aimed at dealing with large-scale point cloud data. Our encoder allows setting lower compression rate on regions or objects of interest for semantic point clouds, preserving crucial information in the point cloud. For underwater acoustic communication, we employ orthogonal frequency division multiplexing combined with deep joint source-channel coding for transmission to enhance the system’s error-resilience. Compared to state-of-the-art methods in the simulation experiments, our end-to-end framework achieves considerable compression performance while eliminating certain cliff and leveling effects, also demonstrating robustness even with changing channels.
Contrasting effect of high-Z coating on proton acceleration from thin transparent low-Z foil target
Authors: Tayyab M , Bagchi S , Upadhyay A , Sijoy C D , Mishra V , Moorti A , Chakera J A
Published: October 2024

In the present work, we investigate the impact of a thin metallic coating on proton acceleration from transparent dielectric foils. A substantial difference in the experimental results is observed based on the placement of the thin metal coating—either on the front surface (the side facing the laser) or on the rear surface of the foil. In the former case, we observed an enhancement in both the energy and flux of the accelerated protons/ions. However, in the latter case, the thin metal coating was found to have a highly detrimental effect on the acceleration process. Measurements conducted on transmitted laser pulse signals confirm the crucial role of the intensity-dependent target material transparency and the laser pre-pulse playing vital roles in determining the proton/ion acceleration dynamics. Numerical simulations involving radiation hydrodynamics followed by two-dimensional particle-in-cell simulations confirm the experimental observations.
Determination of atomic hydrogen density and fluorescence decay time by 1D resolved, picosecond TALIF in the RAID linear device
Authors: Kadi L , Baquero-Ruiz M , Andrebe Y , Guittienne Ph , Jacquier R , Karimov R , Stollberg C , Furno I
Published: October 2024

We report on the first 1D resolved two-photon absorption laser-induced fluorescence (TALIF) measurements of atomic hydrogen (H) performed in the Resonant Antenna Ion Device using a picosecond laser system. The results are obtained across a cylindrical plasma column with peak electron density

10

18

m

−
3

and temperature

1

eV

on axis, which decrease monotonically to

2
⋅

10

17

m

−
3

and 0.75 eV over a scale of a few cm away from the axis. TALIF results in these conditions are compatible with a uniform H density profile across the observed region, with a mean dissociation degree close to 3%. The small variation of H density across regions covering a wide range of plasma parameters suggests that transport processes and wall interactions play an important role in determining the H density profile. The fluorescence decay time is close to

10

ns

at all observed locations, a result compatible with complete substate mixing of the n = 3 states of H.
An RFID smart structure using inkjet-printed additive manufacturing technology for metal crack characterization
Authors: Xie Xiangyu , Wang Haidou , Dong Lihong , Song Yaya , Di Yuelan , Guo Weiling , Zhang Jun
Published: October 2024

Developing an indicator for metal materials to characterize cracks is urgent. However, traditional sensor-based technology has drawbacks such as high costs for installation and maintenance when using wired connections. In this paper, we studied the Radio Frequency Identification sensors created through three-dimensional printing technology to characterize surface cracks in metals. This approach simplifies the manufacturing process, silver nanoparticles are printed layer by layer on substrate to form the sensor pattern. The functionality of the sensor is verified through simulations and experiments involving samples with various crack sizes. Our findings demonstrate that when cracks pass over the sensor, there is a distinct response in terms of a shift in resonant frequency, moreover, the sensor offers a reading range greater than 0.7 m at resonance frequency without requiring power supply or wired connection for data transmission purposes. This research showcases the design of a smart structure that is compact, easy-to-fabricate, and potential for applications related to structural health monitoring and crack sensing.
Effects of lateral critical current nonuniformity on stresses in dry-wound high-field REBCO coils
Authors: Yan Yufan , Park Jeonghwan , Kim Geonyoung , Kim Jaemin , Gömöry Fedor , Hahn Seungyong
Published: October 2024

The distribution of critical current density (jc
) in rare-earth barium copper oxide (REBCO) coated conductors (CC) affects the magnetization behaviors and subsequently screening-current-induced stresses, particularly for solenoid magnets in high fields. This paper studies numerically the correlation between lateral jc
profile across conductor width and stress distribution in pancake coils. The modeling framework considers bending, winding, thermal contraction, and magnetic forces including coupled electromagnetic-mechanical behaviors, i.e. the deviation of the perpendicular field away from axial direction due to tilting deformation. The lateral nonuniformity is introduced using trapezoidal functions, emulating typical jc
profiles originated in pristine tapes and those caused by slitting. First, parametric studies are carried out on the small test coils previously reported in the ‘Little Big Coils’ (LBC) paper. It is shown that while slitting edge defects have a moderate impact on peak strains, imperfections in the pristine tape with a larger shoulder width can accelerate the penetration process, shifting peak force to the structurally resilient middle section. Similar behaviors are found in the LBC3 case study, suggesting that lateral jc
nonuniformity may have contributed to the observed degradation states in pancakes with different slit-edge orientations. Furthermore, the manipulation of lateral jc
profile is proposed as a strategy to manage stresses in high field solenoids. This is demonstrated in the design study of a hypothetical REBCO insert. By adjusting the lateral jc
distribution and the overall scaling factor, magnet designs with a reasonable current margin and moderate peak strain can be found. The multi-width concept is then applied to allow for a higher operating current and a larger margin for the end pancakes. Albeit being a generic case, this study highlights the sensitivity of peak stresses in high-field magnets to jc
distribution. This feature may be taken into account to fine-tune magnet designs and adjust coil assemblies for better overall performance. It also emphasizes the need for careful characterization and effective control of lateral jc
distributions in REBCO CC.
A robust, fiber-coupled scanning probe magnetometer using electron spins at the tip of a diamond nanobeam
Authors: Li Yufan , Welker Gesa , Norte Richard , van der Sar Toeno
Published: October 2024

Fiber-coupled sensors are well suited for sensing and microscopy in hard-to-reach environments such as biological or cryogenic systems. We demonstrate fiber-based magnetic imaging based on nitrogen-vacancy (NV) sensor spins at the tip of a fiber-coupled diamond nanobeam. We incorporated angled ion implantation into the nanobeam fabrication process to realize a small ensemble of NV spins at the nanobeam tip. By gluing the nanobeam to a tapered fiber, we created a robust and transportable probe with optimized optical coupling efficiency. We demonstrate the imaging capability of the fiber-coupled nanobeam by measuring the magnetic field generated by a current-carrying wire. With its robust coupling and efficient readout at the fiber-coupled interface, our probe could allow new studies of (quantum) materials and biological samples.
Unstable regions of anisotropic relativistic spheres in higher dimensions
Authors: Yousaf M , Almutairi Bander , Bhatti M Z , Yousaf Z , Khan A S
Published: October 2024

In this work, we consider the collapse of a

D

-dimensional sphere in the framework of a higher-dimensional spherically symmetric space-time in which the gravitational action chosen is claimed to be somehow linked to the

D

-dimensional modified term. This work investigates the criteria for the dynamical instability of anisotropic relativistic sphere systems with

D

-dimensional modified gravity. The certain conditions are applied that lead to the collapse equation and their effects on adiabatic index Γ in both Newtonian (N) and Post-Newtonian (PN) regimes by using a perturbation scheme. The study explores that the Γ plays a crucial role in determining the degree of dynamical instability. This index characterizes the fluid’s stiffness and has a significant impact on defining the ranges of instability. This systematic investigation demonstrates the influence of various material properties such as anisotropic pressure, kinematic quantities, mass function,

D

-dimensional modified gravity parameters, and the radial profile of energy density on the instability of considered structures during their evolution. This work also displays the dynamical behavior of spherically symmetric fluid configuration via graphical approaches.
Density functional theory study of cobalt sulfide as a counter electrode material for dye-sensitized solar cells
Authors: Dadi Dereje Gelanu , Shura Megersa Wodajo , Gochole Fekadu
Published: October 2024

Dye-sensitized solar cells (DSSCs) are viewed as potential substitutes for traditional silicon-based solar cells due to their affordability, impressive performance in low-light conditions, eco-friendly energy production, and adaptability in solar product integration. The use of noble metals such as platinum as counter electrodes in DSSCs was initially limited by their high cost; however, cobalt sulfide has been recognized as a viable alternative due to its abundance, non-toxic properties, and cost-effectiveness. In this work, the crystal structure, electronic, optical characteristics and electrocatalytic activity of the tetragonal phases of cobalt sulfide are investigated through density functional theory with a quantum espresso package. The results obtained for the lattice parameter are a = b = 3.53 Å and c = 4.80 Å. The generalized gradient approximation and hybrid exchange correlation function yield bandgaps of 1.63 and 1.69 eV, respectively, which are consistent with the reported experimental values. An analysis of the density of states and the projected density was carried out to validate the accuracy of the calculated band gaps. Additionally, significant information was obtained from the optical properties through the calculation of the dielectric function. The findings reveal real and imaginary static dielectric constants of 11.85 and 0.13, respectively. Furthermore, the measured absorption and conductivity spectra exhibit promising attributes in the UV–visible range and good electrical conductivity. Moreover, the electrocatalytic activity was studied to analyze the adsorption energy of CoS and the electrolyte. Generally, the calculated electronic and optical properties of CoS crystals indicate their potential application as counter electrodes in dye-sensitized solar cells.
Comparison of fracture behavior of set concretes based on natural and crushed aggregates
Authors: Golewski Grzegorz Ludwik
Published: October 2024

The studies were carried out to diagnose the effects of coarse aggregate type on the mechanical behavior of plain concretes under incremental loading. During the studies mechanical parameters including compressive strength (f
cm) and splitting tensile strength (f
ctm), as well as fracture parameters involving critical stress intensity factor (

K

Ic

S

) and critical crack tip opening displacement (CTOD
c) were evaluated. The aim of the study was to accurately assess the impact of the type of mineral aggregates on the fracture toughness of ordinary concretes. In order to obtain the most reliable comparison of the obtained test results, mineral aggregates, both natural and crushed, from the same geographic area (most commonly used in plain concretes) were used in the experiments. Hence, crushed aggregates covered: basalt (BA), granite (GT) and limestone (LM) and natural pebble gravel aggregate (GL) were used in the concrete mixtures. For better understanding of the crack initiation and propagation in concretes with different coarse aggregates, a macroscopic failure surfaces examination of the tested beams is also presented. Both of the analyzed fracture mechanics parameters, i.e.

K

Ic

S

and CTOD
c increased significantly in the case of concretes which were manufactured based on crushed aggregates. They amounted in comparison to concrete based on gravel aggregate at levels ranging from 20% for concrete with limestone aggregate, to over 30% for concrete with a granite aggregate, and to as much as over 70% for concrete with basalt aggregate. The fracture process in each series of concrete was: quasi-plastic in the case of gravel concrete, semi-brittle in the case of limestone concrete, and clearly brittle in the case of the concretes based on granite and basalt aggregate. The results obtained help to explain how the coarse aggregate type affects the strength parameters and fracture toughness at bending.
Optimizing energy consumption in post-combustion CO2 capture at an NGCC power plant: a simulation-based approach
Authors: Khan Ali Feroz , Hansen Bryan , Guinta Dave
Published: October 2024

This study aims to optimize energy consumption in post-combustion carbon capture processes at a Natural Gas Combined Cycle (NGCC) power plant. It further addresses challenges associated with steam extraction from NGCC power plants and explores non-condensable steam turbines to boost process efficiency. Various scenarios are explored to minimize energy requirements by leveraging heat integration and alternative solvent compositions. The research uses simulations with commercially available software and literature-derived data to address the challenges of high energy consumption in such processes. Emphasis is placed on optimizing solvent composition and implementing advanced heat optimization strategies to reduce energy consumption. Four scenarios with different solvent compositions are investigated, utilizing Monoethanolamine and aqueous piperazine. The results show that process parameter optimization and heat optimization strategies can result in significant energy savings. To attain a carbon-neutral energy landscape, this research helps develop more sustainable and effective carbon capture methods.
3D bioprinted chondrogenic gelatin methacrylate-poly(ethylene glycol) diacrylate composite scaffolds for intervertebral disc restoration
Authors: Astudillo Potes Maria D , Tilton Maryam , Mitra Indranath , Liu Xifeng , Dashtdar Babak , Camilleri Emily T , Elder Benjamin D , Lu Lichun
Published: October 2024

Degenerative spine pathologies, including intervertebral disc (IVD) degeneration, present a significant healthcare challenge due to their association with chronic pain and disability. This study explores an innovative approach to IVD regeneration utilizing 3D bioprinting technology, specifically visible light-based digital light processing, to fabricate tissue scaffolds that closely mimic the native architecture of the IVD. Utilizing a hybrid bioink composed of gelatin methacrylate (GelMA) and poly (ethylene glycol) diacrylate (PEGDA) at a 10% concentration, we achieved enhanced printing fidelity and mechanical properties suitable for load-bearing applications such as the IVD. Preconditioning rat bone marrow-derived mesenchymal stem cell spheroids with chondrogenic media before incorporating them into the GelMA-PEGDA scaffold further promoted the regenerative capabilities of this system. Our findings demonstrate that this bioprinted scaffold not only supports cell viability and integration but also contributes to the restoration of disc height in a rat caudal disc model without inducing adverse inflammatory responses. The study underscores the potential of combining advanced bioprinting techniques and cell preconditioning strategies to develop effective treatments for IVD degeneration and other musculoskeletal disorders, highlighting the need for further research into the dynamic interplay between cellular migration and the hydrogel matrix.
Materials, processes, devices and applications of magnetoresistive random access memory
Authors: Yang Meiyin , Cui Yan , Chen Jingsheng , Luo Jun
Published: October 2024

Magnetoresistive random access memory (MRAM) is a promising non-volatile memory technology that can be utilized as an energy and space-efficient storage and computing solution, particularly in cache functions within circuits. Although MRAM has achieved mass production, its manufacturing process still remains challenging, resulting in only a few semiconductor companies dominating its production. In this review, we delve into the materials, processes, and devices used in MRAM, focusing on both the widely adopted spin transfer torque MRAM and the next-generation spin-orbit torque MRAM. We provide an overview of their operational mechanisms and manufacturing technologies. Furthermore, we outline the major hurdles faced in MRAM manufacturing and propose potential solutions in detail. Then, the applications of MRAM in artificial intelligent hardware are introduced. Finally, we present an outlook on the future development and applications of MRAM.
Fabrication, compact & device modeling of 4H–21DNTT organic thin film transistor
Authors: Dadhich Shubham , Upadhyaya Vivek , Mathur Garima , Dwivedi A D D
Published: October 2024

In this study, we explored a novel organic semiconductor (OSC), 6,6 bis-(trans4-butylcyclohexyl) dinaphtho[2,1-b:2,1-f]thieno[3,2-b]thiophene (4H–21DNTT). The work also includes a TCAD device model for optimizing and improving the device performance. Both the experimental and simulated results have demonstrated sufficient mobility to realize complex circuits. To validate its potential, a compact model was developed and employed in the SPICE simulator for complex-circuit simulations. Both models accurately capture the below-threshold, linear, and saturation operating conditions through a unified approach, removing the necessity for explicitly defining the threshold and saturation voltages.
Bearing fault diagnosis based on novel hierarchical multiscale dispersion entropy in corresponding color block images
Authors: Wang Zihan , Peng Jigang , Sun Yongjian
Published: October 2024

The rolling bearing is a critical component of mechanical equipment, and its failure can lead to serious consequences. In order to effectively extract fault features of rolling bearings and improve fault diagnosis performance, a fault diagnosis framework based on hierarchical multiscale dispersion entropy (HMDE) and improved histogram of oriented gradient (HOG) is proposed by combining entropy method with image recognition method. Firstly, the original vibration signal is subjected to moving average filtering to eliminate sudden noise and outliers. Then, HMDE is used for the extraction of fault features. HMDE can evaluate the complexity of the signal at different levels and scales, thereby extracting more comprehensive information. Based on HMDE, entropy color block (ECB) images are generated and the improved HOG of the images are extracted. Finally, K-nearest neighbor (KNN) is used to classify the improved HOG features, completing the recognition of different working states of rolling bearings. The validity and robustness of the proposed fault diagnosis framework are proved by the verification experiments on the public bearing datasets of Case Western Reserve University and Southeast University.
Bonding performance and construction parameters of low-rebound shotcrete
Authors: Liu Xiangyang , Wei Liangwen , Lu Dewang , Sun Liang , Huang Yaoming , Liu Shiyang
Published: October 2024

Shotcrete has the advantages of short setting time, high early strength, simple process and flexible operation methods. It is mainly used as temporary support in domestic highway tunnels. This study investigates the development of low-rebound shotcrete for tunnel construction by adding silica fume and fly ash into the mixture. Sandstone and limestone were employed to simulate the surrounding rock. The workability and mechanical properties of the shotcrete were evaluated based on slump tests, rebound rates, compressive strength measurements, and bonding strength tests between the surrounding rock and the shotcrete. Furthermore, the research investigated construction techniques, with an emphasis on spraying distance, shrinkage angle, and wind pressure, and optimized these parameters for practical engineering uses. The outcomes demonstrate that the addition of silica fume enhances the mechanical properties of the shotcrete and reduces rebound. It was discovered that optimal spraying distance was between 1.2 m and 1.5 m, with the optimal wind pressure at 0.5 m, and the ideal shrinkage angle at 6°. Research on low rebound shotcrete is of great significance for improving construction quality, construction efficiency and engineering structural performance, and also meets the requirements of sustainable development.
Evaluation of a pathology resident wellness initiative: Initial establishment and subsequent expansion through a time of high stress, the COVID-19 pandemic
Authors: Davis Katelynn , Bailey Gabrielle , Butcher Monica R , Dombrowski Katya , Fomchenko Katherine M , Schendzielos Rachel , Boyd Kristy , Nath Nancy , Hanyok Laura A , Hruban Ralph H , Wake Laura M , White Marissa J , Ware Alisha D
Published: October 2024

Objectives

Recent studies have shown that the pathology workforce is at risk of decreased workplace well-being, which may lead to decreased job satisfaction, increased attrition, burnout, depression, anxiety, and suicidality, but there has been relatively little research on well-being initiatives designed for pathologists, pathology trainees, and laboratory professionals. Some studies have suggested that well-being initiatives may decrease burnout and increase workplace satisfaction and engagement.

Methods

Here we describe the creation of a Pathology Wellness Committee in a large residency program. Interventions included emotional, social, and physical well-being interventions as well as system-based improvements. Additional initiatives were introduced in response to the increased stress, isolation, and social distancing guidelines during the height of the COVID-19 pandemic. The program’s impact was measured by an annual House Staff Council Resident Wellness Survey over 4 years.

Results

The annual surveys showed improvements in workplace and residency program satisfaction and emotional well-being following system-based improvements and well-being initiatives. Physical and social well-being showed slight but not statistically significant decreases over the 4-year period. Results from the annual Accreditation Council for Graduate Medical Education Survey were also evaluated.

Conclusions

We found that dedicated well-being initiatives in conjunction with system-based interventions may help improve overall well-being in pathology residents.
Physicochemical and microbiological stability of 40 mg/mL amiodarone hydrochloride oral suspension
Authors: Cavelier Marine , Gondé Henri , Costa Damien , Lamoureux Fabien , Pereira Tony , Varin Rémi , Hervouët Charles
Published: October 2024

Purpose

Amiodarone hydrochloride is an antiarrhythmic drug used to treat supraventricular tachycardia. However, there are currently no commercial pediatric forms available to treat young patients. Various oral formulations were previously reported in the literature, but the concentration was lower than the doses prescribed in clinical practice (a loading dose of 500 mg/m2/day for 7-10 days followed by a maintenance dose of 250 mg/m2/day). The objective of this study was to develop an oral liquid formulation of amiodarone hydrochloride at an optimal concentration for use in children and to evaluate its physicochemical and microbiological stability.

Methods

No commercial suspension vehicle was used, allowing the choice of excipients. Compounding was performed using hydroxypropylmethylcellulose as thickener, potassium sorbate preservative, citric acid/sodium citrate buffer, sodium saccharin as sweetener, and a strawberry flavoring agent. A concentration of 40 mg/mL was selected based on a 5-year compilation of prescribed doses. Analyses performed were the following: visual and microscopic inspection, testing for antimicrobial preservation, osmolality and pH measurements, quantification of amiodarone hydrochloride by a stability-indicating liquid chromatography method, and a microbiological count.

Results

At least 95% of the initial amiodarone hydrochloride remained stable during the 60-day study period under refrigeration. All other tested parameters remained stable at 5 °C. A targeted log reduction of the microorganism inoculum by day 14 and no microbial growth by day 28 were demonstrated in the test for antimicrobial preservation.

Conclusion

The stability of 40 mg/mL amiodarone hydrochloride oral suspension was maintained under refrigeration for 60 days before opening bottles and for 1 month after opening bottles.
Lifestyle factors in the biomedical literature: an ontology and comprehensive resources for named entity recognition
Authors: Nourani Esmaeil , Koutrouli Mikaela , Xie Yijia , Vagiaki Danai , Pyysalo Sampo , Nastou Katerina , Brunak Søren , Jensen Lars Juhl
Published: October 2024

Motivation

Despite lifestyle factors (LSFs) being increasingly acknowledged in shaping individual health trajectories, particularly in chronic diseases, they have still not been systematically described in the biomedical literature. This is in part because no named entity recognition (NER) system exists, which can comprehensively detect all types of LSFs in text. The task is challenging due to their inherent diversity, lack of a comprehensive LSF classification for dictionary-based NER, and lack of a corpus for deep learning-based NER.

Results

We present a novel lifestyle factor ontology (LSFO), which we used to develop a dictionary-based system for recognition and normalization of LSFs. Additionally, we introduce a manually annotated corpus for LSFs (LSF200) suitable for training and evaluation of NER systems, and use it to train a transformer-based system. Evaluating the performance of both NER systems on the corpus revealed an F-score of 64% for the dictionary-based system and 76% for the transformer-based system. Large-scale application of these systems on PubMed abstracts and PMC Open Access articles identified over 300 million mentions of LSF in the biomedical literature.

Availability and implementation

LSFO, the annotated LSF200 corpus, and the detected LSFs in PubMed and PMC-OA articles using both NER systems, are available under open licenses via the following GitHub repository: https://github.com/EsmaeilNourani/LSFO-expansion. This repository contains links to two associated GitHub repositories and a Zenodo project related to the study. LSFO is also available at BioPortal: https://bioportal.bioontology.org/ontologies/LSFO.
DAVID Ortholog: an integrative tool to enhance functional analysis through orthologs
Authors: Sherman Brad T , Panzade Ganesh , Imamichi Tomozumi , Chang Weizhong
Published: October 2024

Motivation

The Database for Annotation, Visualization, and Integrated Discovery (DAVID) is a web-based bioinformatics system for the functional interpretation of large lists of genes/proteins generated from high-throughput assays. It has been cited in 72 287 papers since its debut in 2003 as of 23 July 2024. The analysis is usually limited to the species of study. However, the knowledge of genes may be incomplete or unavailable for some species. Model organisms have been studied more extensively and analyzing gene lists in the context of these species can offer valuable insights, helping users better understand the genes and biological themes in their species of interest.

Results

We developed DAVID Ortholog for the conversion of gene lists between species. We utilized the ortholog data downloaded from Orthologous MAtrix (OMA) and Ensembl Compara as the base for the conversion. The OMA ortholog IDs and Ensembl gene IDs were converted to DAVID gene IDs and the pairing information of these IDs from these two sources was integrated into the DAVID Knowledgebase. DAVID Ortholog can convert the user’s source gene list to an ortholog list of a desired species and the downstream DAVID analysis, in the context of that species, can be continued seamlessly, allowing users to further understand the biological meaning of their gene list based on the functional annotation found for the orthologs.

Availability and implementation

https://davidbioinformatics.nih.gov/ortholog.jsp.
AncestryGrapher toolkit: Python command-line pipelines to visualize global- and local- ancestry inferences from the RFMIX version 2 software
Authors: Lisi Alessandro , Campbell Michael C
Published: October 2024

Admixture is a fundamental process that has shaped levels and patterns of genetic variation in human populations. RFMIX version 2 (RFMIX2) utilizes a robust modeling approach to identify the genetic ancestries in admixed populations. However, this software does not have a built-in method to visually summarize the results of analyses. Here, we introduce the AncestryGrapher toolkit, which converts the numerical output of RFMIX2 into graphical representations of global and local ancestry (i.e. the per-individual ancestry components and the genetic ancestry along chromosomes, respectively).

Results

To demonstrate the utility of our methods, we applied the AncestryGrapher toolkit to visualize the global and local ancestry of individuals in the North African Mozabite Berber population from the Human Genome Diversity Panel. Our results showed that the Mozabite Berbers derived their ancestry from the Middle East, Europe, and sub-Saharan Africa (global ancestry). We also found that the population origin of ancestry varied considerably along chromosomes (local ancestry). For example, we observed variance in local ancestry in the genomic region on Chromosome 2 containing the regulatory sequence in the MCM6 gene associated with lactase persistence, a human trait tied to the cultural development of adult milk consumption. Overall, the AncestryGrapher toolkit facilitates the exploration, interpretation, and reporting of ancestry patterns in human populations.

Availability and implementation

The AncestryGrapher toolkit is free and open source on https://github.com/alisi1989/RFmix2-Pipeline-to-plot.