bluuebunny/crossref_metadata_2025 huggingface dataset:
Evolution characteristics of shock wave in microsecond-scale underwater electrical wire explosion
Authors: Huang Yifan , Gu Tianyi , Chen Yao , Zeng Hanshi , Han Xiaotao
Published: December 2024

The underwater electrical wire explosion (UEWE) is a physical phenomenon initiated by the rapid injection of electrical energy, triggering an explosive event. UEWE offers advantages in energy conversion efficiency, repeatability, and controllability, making it valuable in various industrial applications. Building upon established zero-dimensional (0D) and one-dimensional (1D) models, this paper proposes an enhanced 0D-1D coupled cold-start model to describe the plasma channel expansion and subsequent shock wave (SW) propagation characteristics. The model comprises two submodules: a 0D magnetohydrodynamics model that describes plasma channel boundary expansion during the explosion, and a 1D hydrodynamics model using an artificial viscosity algorithm to depict SW propagation. The constructed numerical model facilitates investigation of plasma characteristics, SW propagation behavior, and energy conversion efficiency throughout the UEWE process. Additionally, the influences of wire dimensions and discharge frequency on these characteristics were analyzed. The results indicate that SW propagation characteristics are primarily governed by thermal pressure variations within the wire and that different wire dimensions markedly affect SW amplitude, attenuation, and impulse. The efficiency of electrical-to-SW energy conversion remains relatively low; however, thicker and shorter wires can enhance SW amplitude and improve conversion efficiency. Higher discharge frequencies produce greater impact forces and impulses near the explosion site, while also improving energy conversion rates. This study offers a theoretical basis and technical guidance for prospective engineering applications.
High-accuracy solution for fractional solitary wave dynamics in finite water depth with linear shear flow, wind, and dissipation effects
Authors: Zhou Yue , Xu Hang
Published: December 2024

In this paper, a fractional nonlinear Schrödinger equation has been initially derived for capturing the dynamics of gravity waves in finite water depth, accounting for factors such as wind, dissipation, and shear currents. A comprehensive framework is established to enhance the model's representation of gravity wave behavior. We employ a high-order iterative method, specifically the homotopy iterative technique, along with a non-uniform collocation approach integrated into the Haar wavelet method, resulting in a novel computational method characterized by high precision and efficiency. The robustness and reliability of the proposed approach are validated through convergence analysis and comparisons with analytical solutions. Furthermore, the results indicate that the nonlinear and dispersive effects caused by the fractional orders lead to changes in the propagation characteristics of gravity waves. The impacts of the damping coefficient related to wind action and dissipative effects on the temporal evolution of solitary waves are also discussed. The construction of the fractional model holds far-reaching significance for researching the nonlinear propagation of gravity waves in actual ocean water waves. Additionally, an outstanding computational technique for solving fractional nonlinear evolution equations in diverse applications has been developed.
Bandlike charge transport and electron–phonon coupling in organic molecular crystals
Authors: Chang Benjamin K , Bernardi Marco
Published: December 2024

Charge transport is important in organic molecular crystals (OMCs), where high carrier mobilities are desirable for a range of applications. However, modeling and predicting the mobility is challenging in OMCs due to their complex crystal and electronic structures and electron–phonon (e–ph) interactions. Here we show accurate first-principles calculations of electron and hole carrier mobility in several OMCs: benzene, anthracene, tetracene, pentacene, and biphenyl. Our calculations use the Boltzmann transport equation formalism with e–ph interactions computed from first principles. These calculations describe transport in the bandlike, weak e–ph coupling regime, and include all phonon modes and electronic bands on equal footing. In all systems studied, we predict the mobility and its temperature dependence in very good agreement with experiments between 100−400 K, where transport is phonon-limited. We show that e–ph scattering from low-frequency (LF) phonons with energy below 150 cm−1 primarily limits the mobility, even though these modes are not the ones with the strongest e–ph coupling. These LF modes are shown to consist mainly of intermolecular vibrations, with admixed long-range intramolecular character in OMCs with larger molecules. Furthermore, we find that the LF-mode scattering rates vary significantly with strain, suggesting that strain engineering can effectively modulate e–ph coupling and enhance the mobility. This work sheds light on bandlike transport mechanisms in OMCs and advances the rational design of high-mobility organic semiconductors.
A data-driven early warning method for thermal runaway during charging of lithium-ion battery packs in electric vehicles
Authors: Cheng Yuan-Ming , Gao De-Xin , Zhao Feng-Ming , Yang Qing
Published: December 2024

In recent years, thermal runaway during charging of lithium-ion batteries has become a critical issue. This problem has emerged as a significant barrier to the development of power batteries for electric vehicles (EVs). This paper addresses this challenge from a data-driven perspective by proposing a temperature prediction model for thermal runaway during charging of EV lithium-ion batteries. The model leverages both long short-term memory and Transformer algorithms to account for the time-series characteristics of batteries charging. The charging data under varying capacities and ambient temperatures are extracted using the Newman–Tiedemann–Gaines–Kim model for lithium-ion batteries, which is then used to optimize the accuracy of the hybrid algorithm through training. Additionally, real-world EV charging data is collected to further validate the temperature prediction model. Experimental results demonstrate that the proposed model achieves superior prediction accuracy compared to both single models and convolutional neural network hybrid models. Based on this model, a residual-based early warning method incorporating a sliding window approach is proposed. The experimental findings indicate that when the residual of the predicted charging temperature for EVs lithium-ion batteries exceeds the warning threshold, preemptive termination of charging effectively prevents thermal runaway.
A binary coding method for half-period sinusoidal stripes in focused projection
Authors: Yan Fei , Xiang Qianhuai , Zhu Rui , Ma Xingyu , Liu Yinping
Published: December 2024

During sinusoidal streak projection measurements, the nonlinear responses inherent in projectors and cameras can significantly alter the characteristics of projection and imaging. Traditional techniques require precise out-of-focus levels to achieve accurate depth measurements, which inherently limit the depth range that can be effectively measured. Addressing this limitation, this paper introduces an innovative binarization coding method for half-period sinusoidal stripes in focused projection. Our approach begins with a binarization process that encodes the half-period sinusoidal stripes. We then capture these stripes as they are modulated by the height of the object under test. The subsequent synthesis of the half-period sinusoidal stripes is achieved through a method of superposition calculation. To enhance the experimental procedure, we employ a four-step phase-shifting technique, complemented by an assisted phase unfolding using the gray code method. For the validation of our method, a standard ball with a diameter of 50.8140 mm was measured. The results are compelling, demonstrating a root mean square error of merely 0.0285 mm. Comparative experimental results prove that the proposed method can effectively avoid the influence of nonlinearity, and also obtain high-precision reconstruction results for discontinuous scenes.
A novel Modelica-based reliability modeling approach for ship electric propulsion systems
Authors: Gai Jingbo , Fang Jianyang , Du Xuejiao , Sun Hai
Published: December 2024

As the primary power source for ships, the reliability of electric propulsion systems directly impacts the safety, stability, and economic efficiency of maritime operations. However, the composition of ship electric propulsion systems is complex and is continuously exposed to the dynamic and variable marine environment, which complicates their reliability modeling and analysis. This paper introduces a novel approach to reliability modeling for electric propulsion systems based on the Modelica language. The aim is to overcome the limitations of traditional reliability modeling methods by considering the heterogeneity, dynamicity, and interactivity of electric propulsion systems. The approach addresses system heterogeneity through multi-domain modeling, captures environmental dynamics through parametric modeling, and establishes device interactions using Modelica language connectors. Additionally, modeling efficiency is enhanced by reusing device model packages, which benefits system optimization. Using a specific ship’s electric propulsion system as a case study, the modeling process and simulation results are presented to demonstrate the effectiveness and flexibility of the proposed approach. This approach offers a new tool for reliability modeling of complex electromechanical systems and contributes to enhancing the accuracy and efficiency of system reliability assessments.
Roadmap for the development of machine learning-based interatomic potentials
Authors: Zhang Yong-Wei , Sorkin Viacheslav , Aitken Zachary H , Politano Antonio , Behler Jörg , P Thompson Aidan , Ko Tsz Wai , Ong Shyue Ping , Chalykh Olga , Korogod Dmitry , Podryabinkin Evgeny , Shapeev Alexander , Li Ju , Mishin Yuri , Pei Zongrui , Liu Xianglin , Kim Jaesun , Park Yutack , Hwang Seungwoo , Han Seungwu , Sheriff Killian , Cao Yifan , Freitas Rodrigo
Published: December 2024

An interatomic potential, traditionally regarded as a mathematical function, serves to depict atomic interactions within molecules or solids by expressing potential energy concerning atom positions. These potentials are pivotal in materials science and engineering, facilitating atomic-scale simulations, predictive material behavior, accelerated discovery, and property optimization. Notably, the landscape is evolving with machine learning transcending conventional mathematical models. Various machine learning-based interatomic potentials, such as artificial neural networks, kernel-based methods, deep learning, and physics-informed models, have emerged, each wielding unique strengths and limitations. These methods decode the intricate connection between atomic configurations and potential energies, offering advantages like precision, adaptability, insights, and seamless integration. The transformative potential of machine learning-based interatomic potentials looms large in materials science and engineering. They promise tailor-made materials discovery and optimized properties for specific applications. Yet, formidable challenges persist, encompassing data quality, computational demands, transferability, interpretability, and robustness. Tackling these hurdles is imperative for nurturing accurate, efficient, and dependable machine learning-based interatomic potentials primed for widespread adoption in materials science and engineering. This roadmap offers an appraisal of the current machine learning-based interatomic potential landscape, delineates the associated challenges, and envisages how progress in this domain can empower atomic-scale modeling of the composition-processing-microstructure-property relationship, underscoring its significance in materials science and engineering.
Quantifying the spatial distribution of the accumulated dose uncertainty using the novel delta index
Authors: van den Dobbelsteen Madelon , Hackett Sara L , Bosma Lando S , van Doormaal Renate J A , van Asselen Bram , Fast Martin F
Published: December 2024

Objective. Inter- and intra-fractional anatomical changes during a radiotherapy treatment can cause differences between the initially planned dose and the delivered dose. The total delivered dose can be accumulated over all fractions by using deformable image registration (DIR). However, there is uncertainty in this process which should be accounted for. The aim of this study is to propose a novel metric estimating the spatial distribution of the accumulated dose uncertainty and to evaluate its performance for multi-fraction online adaptive treatments. Approach. We postulate a new metric, the delta (δ) index, to estimate the uncertainties associated with the dose accumulation process. This metric is calculated for each voxel and takes into account the spatial uncertainty in DIR and local dose differences. For the spatial uncertainty of the DIR, the distance discordance metric was used. The accumulated dose and the δ index were determined for ten lung stereotactic body radiation therapy patients. The δ index was complemented by a more understandable metric, the δ index passing rate, which is the percentage of points satisfying the passing criteria in a region. Main results. The spatial distribution of the δ index and the δ index passing rates showed that voxels failing the criteria were predominantly in lower-dose regions. The mean percentage of voxels passing the criterion increased from 65% to 78%, for threshold doses of 20% and 90% of the prescription doses, respectively. Significance. The δ index was postulated to quantify the spatial distribution of the uncertainties associated with the dose accumulation process. The metric gives an intuitive understanding of the reliability of accumulated dose distributions and derived DVH metrics. The performance of the δ index was evaluated for multi-fraction online adaptive treatments, where a case of sub-optimal image registration was identified by the metric.
3-D motion tracking and vascular strain imaging using bistatic dual aperture ultrasound acquisitions
Authors: de Hoop Hein , Maas Esther , Muller Jan-Willem , Schwab Hans-Martin , Lopata Richard
Published: December 2024

Objective. This study demonstrates high volume rate bistatic 3-D vascular strain imaging, to overcome well-known challenges caused by the anisotropic resolution and contrast inherent to ultrasound imaging. Approach. Using two synchronized 32 × 32 element matrix arrays (3.5 MHz), coherent 3-D ultrasound images of ex vivo porcine aortas were acquired at 90 Hz during pulsation in a mock circulation loop. The image data of interleaved transmissions were coherently compounded on one densely sampled Cartesian grid to estimate frame-to-frame displacements using 3-D block matching. The radial displacement components were projected onto mesh nodes of the aortic wall, after which local circumferential and radial strain estimates were calculated with a 3-D least squares strain estimator. Main results. The additional reflection content and high-resolution phase information along the axis of the second transducer added more distinctive features for block matching, resulting in an increased coverage of high correlation values and more accurate lateral displacements. Compared to single array results, the mean motion tracking error for one inflation cycle was reduced by a factor 5–8 and circumferential elastographic signal-to-noise ratio increased by 5–10 dB. Radial strain remains difficult to estimate at the transmit frequency used at these imaging depths, but may benefit from more research into strain regularization and sub-pixel interpolation techniques. Significance. These results suggest that multi-aperture ultrasound acquisition sequences can advance the field of vascular strain imaging and elastography by addressing challenges related to estimating local-scale deformation on an acquisition level. Future research into 3-D aberration correction and probe localization techniques is important to extend the method’s applicability towards in vivo use and for a wider range of applications.
Microstructure of superconducting hetero-joints between single-grained Gd–Ba–Cu–O bulk superconductors
Authors: Gao Z , Congreve J V J , Tutt N , Shi Y , Liu J , Grovenor C R M , Cardwell D A , Durrell J H , Speller S C
Published: December 2024

A wide range of technologies rely on permanent magnets, including levitation devices, motors, generators and magnetic separators. Replacing permanent magnets with bulk superconductors will enable a step change in performance by providing an order of magnitude increase in the achievable magnetic field. However, the reliable fabrication of large single grained superconducting materials with a high, homogeneously distributed magnetic trapped field remains a barrier to the widespread application of these materials. Limits to the size and geometry of RE–Ba–Cu–O single grain bulk superconductors could be overcome by developing a reliable process to assemble larger components by fabricating superconducting joints between smaller samples. In this work we propose a mechanism of joint formation in GdBCO–Ag bulk superconductors using a YBCO–Ag intermediate that is based on detailed analysis of the joint interfaces. This improved understanding of the joint formation process provides the knowledge required to fully optimise the fabrication parameters, and to produce joints with improved superconducting and mechanical properties.
Evolution of the universe prior to inflation in loop quantum cosmology
Authors: Shahalam M.
Published: December 2024

We studied the dynamics of pre-inflation with generic potentials, namely

and

, in the context of loop quantum cosmology, where the initial singularity is resolved by a non-singular quantum bounce. Initially, the background evolution is dominated by either kinetic or potential energy at the quantum bounce. In the case of kinetic energy dominated evolution at the bounce, we found three generic phases, namely bouncing, transition, and slow-roll inflation. The first two regimes vanish in the case of potential energy dominated evolution; however, slow-roll inflation remains. Therefore, we found physically viable initial conditions of the inflaton field, which must have a minimum number of

-folds of 60 to be compatible with observations. Additionally, we analyzed the phase space diagram for the models under consideration; we found that all the trajectories of the inflaton field start from the bounce and move toward stable attractor points.
Short-term load forecasting method based on multiple meteorological factors and improved TCN-LSTM
Authors: Song Mingshu , Su Changsheng , Wang Yong , Du Long , Li Fengting
Published: December 2024

Effective scheduling plans, optimized energy deployment, and grid stability assurance hinge on precisely forecasting short-term power loads. Therefore, this paper introduces an innovative approach to short-term load forecasting that integrates meteorological factors with an enhanced TCN-LSTM methodology. Firstly, the impact of meteorological factors on loads is quantified using Pearson’s phase relationship, facilitating the identification of meteorological input variables for the short-term load forecasting model. Secondly, a novel time-series convolutional neural network (TCN) tailored to power load characteristics is developed. The introduction of a network structure adapted to the characteristics of power loads improves the TCN model, enabling the effective capture of the long-term dependence and short-term fluctuation in load data. Finally, the paper details the construction of the improved TCN-LSTM model for short-term load forecasting. The new vectors, formed based on the load data features extracted by the improved TCN, are used as inputs for LSTM for load forecasting. The proposed short-term load forecasting method is validated using load-meteorological data from a typical period in a specific area, and the results demonstrate a notable enhancement in forecasting.
Comparative study of earthquake – resistant building design according to SNI 03-1726-2019 in Jakarta and Aceh regions
Authors: Husen Muhamad Fitra , Mentari Sekar , Nursani Rosi
Published: December 2024

Indonesia’s unique geological setting necessitates region-specific approaches to earthquake-resistant building design. This study investigates the comparative structural behavior and design requirements of buildings in Jakarta and Aceh, two regions with contrasting seismic hazards, adhering to the Indonesian seismic code SNI 03-1726-2019. Utilizing ETABS software and the response spectrum method, the research reveals that structures in Aceh, due to the heightened seismic risk, demand larger dimensions (up to 40% increase in column size) compared to those in Jakarta. The analysis also uncovers similar patterns of horizontal and vertical irregularity in both regions. The base shear, a crucial indicator of seismic demand, is notably higher in Aceh (742,781.6 kN) than in Jakarta (588,980.6 kN). Additionally, roof displacement values exhibit variations between the two regions, with Jakarta recording 31.895 mm and 61.518 mm, and Aceh showing 30.542 mm and 56.936 mm. This study shows that regions with higher seismic acceleration necessitate greater building capacity to withstand the increased seismic forces. The research concludes that effective earthquake-resistant design must be tailored to the specific seismic context of each region, ensuring the safety and resilience of buildings across Indonesia.
Rotary-screen printing with improved registration and dimensional stability for flexible electronics
Authors: Välimäki Marja , Happonen Tuomas , Karhu Toni , Ontero Pekka , Luoma Enni , Ollila Jyrki , Korhonen Pentti , Takaluoma Antti , Rooms Harmen , Kraft Thomas M
Published: December 2024

A key aspect of printed electronics manufacturing is layer-layer registration and potential deformation of the substrate during processing (e.g. printing) which involves thermal treatment under tension or steps without any tension (e.g. surface mount hybrid integration of electronics). The influence of thermal processing on the registration control and material interfaces for printed and hybrid processing was evaluated on a pilot printing line using roll-to-roll screen-printed silver microflakes and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) inks. The registration was not fully stabilized on polyethylene terephthalate (PET) whereas on thermally pre-treated PET (PET_t) it reached ±60 µm accuracy in the machine direction (MD) and ±100 µm in the cross-machine direction (CD) after settling. The print on PET deviated 0.18% in MD and −0.01% in CD, implying that the print dimensions were changing along the MD elongation, whereas the changes on PET_t occurred during the pre-treatment, thus, the print deviated only −0.01% in MD and 0.08% in CD. Silver-substrate interface obtained good adhesion, however partial delamination was detected after thermal post-treatment at zero tension, most likely due to substrate shrinkage. Differences in the thermal response may partially delaminate the silver. Delamination of PEDOT:PSS was not observed, which may be related to its polymeric nature. Silver resistance on PET was 8% higher than on PET_t in MD, due to the elongation of the PET that occurs during print curing. Respectively, the silver resistance on PET was 2% lower in CD, with the dimensions slightly below the nominal layout value. Thermal post-treatment at zero tension reduced the resistance on both substrates, being greater in the MD as well as the substrate shrinkage. The impacts of thermal treatment are particularly important if the hybrid electronics processing is utilizing manufacturing lines with different web tension, such as printing and surface mount technology assembly, since the dimensional changes of the substrate can cause significant reduction in accuracy and reliability.
Development of bioengineered 3D patient derived breast cancer organoid model focusing dynamic fibroblast–stem cell reciprocity
Authors: Roy Nakka Sharmila , Kumari Mamta , Alam Kamare , Bhattacharya Anamitra , Kaity Santanu , Kaur Kulwinder , Ravichandiran Velayutham , Roy Subhadeep
Published: December 2024

Three-dimensional (3D) models, such as tumor spheroids and organoids, are increasingly developed by integrating tissue engineering, regenerative medicine, and personalized therapy strategies. These advanced 3D in-vitro models are not merely endpoint-driven but also offer the flexibility to be customized or modulated according to specific disease parameters. Unlike traditional 2D monolayer cultures, which inadequately capture the complexities of solid tumors, 3D co-culture systems provide a more accurate representation of the tumor microenvironment. This includes critical interactions with mesenchymal stem/stromal cells (MSCs) and induced pluripotent stem cells (iPSCs), which significantly modulate cancer cell behavior and therapeutic responses. Most of the findings from the co-culture of Michigan Cancer Foundation-7 breast cancer cells and MSC showed the formation of monolayers. Although changes in the plasticity of MSCs and iPSCs caused by other cells and extracellular matrix (ECM) have been extensively researched, the effect of MSCs on cancer stem cell (CSC) aggressiveness is still controversial and contradictory among different research communities. Some researchers have argued that CSCs proliferate more, while others have proposed that cancer spread occurs through dormancy. This highlights the need for further investigation into how these interactions shape cancer aggressiveness. The objective of this review is to explore changes in cancer cell behavior within a 3D microenvironment enriched with MSCs, iPSCs, and ECM components. By describing various MSC and iPSC-derived 3D breast cancer models that replicate tumor biology, we aim to elucidate potential therapeutic targets for breast cancer. A particular focus of this review is the Transwell system, which facilitates understanding how MSCs and iPSCs affect critical processes such as migration, invasion, and angiogenesis. The gradient formed between the two chambers is based on diffusion, as seen in the human body. Once optimized, this Transwell model can serve as a high-throughput screening platform for evaluating various anticancer agents. In the future, primary cell-based and patient-derived 3D organoid models hold promise for advancing personalized medicine and accelerating drug development processes.
Investigations on the effect of vapor smoothing process in trichloromethane (chloroform) on the surface characteristics, mechanical properties and chemical structure of 3D printed Poly-Lactic-Acid (PLA)
Authors: Pitale Sameer , Keche Ashok J , Chopra Swamini
Published: December 2024

3D printing has become a prominent method for prototyping and manufacturing intricate geometric components. However, the inherent staircase effect often leaves 3D printed parts with suboptimal surface smoothness. To address this issue, post-processing techniques like vapor smoothing, involving the use of trichloromethane (chloroform) vapors, are employed. This paper presents experimental investigations on 3D printed PLA parts subjected to vapor smoothing, with a focus on varying the process time. Experimental determinations of elongation, tensile strength, and surface finish provide insights into the influence of process time on these critical features of 3D printed PLA components. The selection of an optimal process time emerges as a crucial factor in achieving a harmonious balance between surface characteristics and mechanical properties. The novelty of this research lies in establishing correlations between changes in PLA elongation, tensile strength, and surface finish post-vapor smoothing and the corresponding alterations in the chemical structure of PLA. The study reveals the synergistic physical and chemical interactions between chloroform vapors and PLA structure that result in enhanced surface finish. Simultaneously, the process time is identified as a key determinant governing the extent of changes in mechanical properties. Consequently, this work aims to elucidate the mechanisms responsible for the observed combination of properties and surface characteristics through Fourier-transform infrared (FTIR) analysis concerning vapor smoothing process time.
Varying aggregate sizes, plasticizers, and supplementary cementitious materials to efficiently use Portland clinker in concrete
Authors: Amitani Asahi , Miller Sabbie A
Published: December 2024

Mitigating greenhouse gas (GHG) emissions from the production of concrete, a critical infrastructure material around the world, has been highlighted as necessary to meet climate change goals. Concrete is made of water, aggregates (e.g. crushed rocks), and Portland cement (PC), a hydraulic binder. PC is the primary source of GHG emissions from concrete, a function of the emissions derived from the production of its clinker, a kilned, quenched material composed of calcium silicates that, by mass, makes up the majority of PC. While considerable attention has been given to reducing the GHG emissions from PC manufacture, better utilization of other resources used in concrete can lower the demand for the level of clinker necessary in any given mixture. In this work, we examine how changing the size of aggregates, the use of a superplasticizer (SP), and the use of supplementary cementitious materials (SCMs) can lower GHG emissions from concrete. We derive a system of equations based fundamentally on standard mixture proportioning guidelines to determine the most efficient use of PC in a concrete mixture for specified strength and workability, and we quantify GHG emissions using life cycle assessment methods. Findings show that the use of reactive SCMs can contribute to reduced GHG emissions, as can the use of a higher maximum aggregate diameter and higher SP dosage. Our models also suggest that a concrete producer could follow standard mixture proportioning guidelines and yield a mixture that has over 2 times the PC content needed. The efficient use of PC within concrete mixtures by appropriately selecting other constituents can lower GHG emissions, contributing to climate change goals.
Gromov–Hausdorff distances from simply connected geodesic spaces to the circle
Authors: Rodríguez Martín Saúl
Published: December 2024

We prove that the Gromov–Hausdorff distance from the circle with its geodesic metric to any simply connected geodesic space is never smaller than

π
4

\frac {\pi }{4}

. We also prove that this bound is tight through the construction of a simply connected geodesic space

E

\mathrm {E}

which attains the lower bound

π
4

\frac {\pi }{4}

. We deduce the first statement from a general result that we also establish which gives conditions on how small the Gromov–Hausdorff distance between two geodesic metric spaces

(
X
,

d
X

)

(X, d_X)

and

(
Y
,

d
Y

)

(Y, d_Y )

has to be in order for

π
1

(
X
)

\pi _1(X)

and

π
1

(
Y
)

\pi _1(Y)

to be isomorphic.
Introduction
Authors: Ross Janice
Published: December 2024

The Introduction to Choreography of Environments sets up the context for this book’s exploration of the use of ordinary objects from a private residence as lenses into viewing dance innovation. It provides an overview of how this book posits the 1950s iconic mid-century modern home and expansive gardens of the California dancer Anna Halprin and landscape architect Lawrence Halprin, as a hidden archive. It includes a brief summary of how chapter is devoted to one of four pivotal objects from the Halprin house and grounds (staircase, chair, window and deck). Close readings of these objects are then used to trace how, despite the conservative postwar climate, this intimate domestic space became a radical template reshaping postmodern dance invention and its expansion into civic, social, and environmental engagement in the twentieth and twenty-first centuries. The fifth, and concluding chapter, explores how these four objects continue as forceful presences in the Halprins’ lives as prominent elements in their second home at The Sea Ranch on the Northern California Coastline.
Occupational exposure to respirable crystalline silica at an underground copper mine in Zambia
Authors: Nabiwa Lubinda , Linde Stephanus J L , Habanyama Adrian , Hayumbu Patrick , Sifanu Mwaba , Masekameni Masilu Daniel
Published: December 2024

Introduction

Overexposure to respirable crystalline silica (RCS) can lead to the development of silicosis and other respiratory diseases. The mine under study was reported to have the highest number of certified cases of pneumoconiosis in Zambia in 2015, and in 2008, a study revealed that 56% of the RCS samples exceeded 0.05 mg/m3. This study aims to assess occupational exposure to RCS at this underground copper mine.

Method

In this cross-sectional study, personal exposure monitoring was conducted using National Institute for Occupational Safety and Health’s methods 0600 and 7602 (KBr pellet), and 114 samples were collected. Gravimetric analysis of respirable dust (RD) samples and quantification of RCS were performed at an ISO 17025:2005 accredited analytical laboratory. BOHS-NVvA 2022 standard was used for determining activity areas’ overexposure.

Results

The median, 95th percentile (P95), and maximum (Max) RD concentrations were 0.279, 1.650, and 3.7 mg/m3, respectively. For the RCS exposure, the median, P95, and Max RCS exposure concentrations were 0.02, 0.179, and 0.548 mg/m3, respectively. Thirteen (11.7%) of the 111 samples had exposure exceeding the Republic of South Africa (RSA) TWA-OEL of 0.1 mg/m3, and 11 out of 18 activity areas were statistically overexposed to RCS when applying the BOHS-NVvA 2022 standard.

Discussion

The number of RCS samples exceeding 0.05 mg/m3 reduced from the 67% recorded in 2008 to 32.4% in this study. One factor that could have led to this reduction is the mine not working at full capacity during the sampling period. However, the lack of adherence to the occupational health and safety (OHS) guidelines by the miners still leads to personal exposure above the limits set by various countries.

Conclusion

Exposure to RCS in more than half of the activity areas was not under control. Routine RCS monitoring in Zambian mines should be mandatory, as this is not an isolated case, though it is more of a challenge at this mine because of the high percentage of RCS in RD samples (18.5%). Miners should be continuously trained on the importance of adhering to the OHS guidelines. Furthermore, Zambia should consider adopting the RSA occupational exposure limit for RCS and the BOHS-NVvA 2022 standard for exposure level compliance testing.
Green flowers need yellow to get noticed in a green world
Authors: del Valle José C , León-Osper Melissa , Domínguez-González Carlos , Buide Mª Luisa , Arista Montserrat , Ortiz Pedro L , Whittall Justen B , Narbona Eduardo
Published: December 2024

Background and Aims

Flower colour is a key feature in plant–pollinator interactions that makes the flowers visible amid the surrounding green vegetation. Green flowers are expected to be scarcely conspicuous to pollinators; however, many of them are visited by pollinators even in the absence of other traits that might attract pollinators (e.g. floral scents). In this study, we investigate how entomophilous species with green flowers are perceived by pollinators.

Methods

We obtained reflectance spectra data of 30 European species that display green or green–yellow flowers to the human eye. These data were used to perform spectral analyses, to calculate both chromatic (colour contrast against the background) and achromatic (colour contrast that relies on the signals from the green-sensitive photoreceptors) cues and to model colour perception by hymenopterans (bees) and dipterans (flies).

Key Results

The visibility of green flowers to bees and flies (i.e. their chromatic contrast values) was lower compared with other floral colours commonly pollinated by these insects, whereas green–yellow flowers were as conspicuous as the other flower colours. Green flowers with low chromatic contrast values exhibited higher achromatic contrast, which is used to detect distant flowers at narrow visual angles, than green–yellow flowers. Additionally, the marker points (i.e. sharp transition in floral reflectance that aids pollinators in locating them) of green and green–yellow flowers aligned to some degree with the colour discrimination abilities of bees and flies.

Conclusions

We found that many entomophilous green and green–yellow flowers are conspicuous to bees and flies through their chromatic or achromatic contrasts. Although acquiring pigments such as carotenoids, which impart a yellowish hue to flowers and enhance their visibility to pollinators, could increase their conspicuousness, the metabolic costs of pigment production, along with the use of alternative strategies to attract pollinators, might have constrained carotenoid emergence in certain lineages of green-flowered species.
Bibliometric Analysis of the Highest Cited Cosmetic Upper Facial Plastic Surgery Articles Over 50 Years
Authors: Rangu Nitin , Pistone Evan , Tan Jeremy , Do Thai
Published: December 2024

In this bibliometric analysis, the authors analyze the top 100 (T100) most cited articles on cosmetic upper facial plastic surgery. Throughout this study, the objective of the authors is to delineate the trends in cosmetic upper facial surgeries to identify prevailing techniques, emerging trends, and potential areas of future investigation. The articles were indexed from the Web of Science database and were extracted in a double-blinded manner by 2 independent graders. The search phrase used covered a wide range of cosmetic upper facial plastic surgeries, of which a short sample is included: (“cosmetic*” AND “bleph*”) OR (“cosmetic*” AND “upper eyelid blepharoplasty”) OR (“cosmetic*” AND “lower eyelid blepharoplasty”). In their statistical analysis of the number of citations received in each article in the T100, the authors reveal an average of 55.1 citations (a standard deviation of 38.7). Surgical methods were the most commonly cited unique study area, with 30% of the T100, followed by botulinum toxin and complication management with 29% and 15% of the T100, respectively. The unique study area with the highest average citations received was botulinum toxin, with an average of 64.7 citations. Invasive procedures made up 55% of the T100 articles. The authors found that the late 1990s and 2000s were a burgeoning period of growth in this field and highlight the evolution of many contemporary popular cosmetic procedures over time. Particularly, a growth in minimally invasive procedures was noted, with noted impacts in aesthetics training and research focus.

Level of Evidence: 4 (Therapeutic)
Gluteal Augmentation: A Historical Perspective on Aesthetic Practice
Authors: Chacur Roberto
Published: December 2024

Buttock augmentation has emerged as a significant focus in cosmetic surgery, driven by advancements in techniques and increasing patient interest in body contouring. The evolution of this field, from early pioneering methods to modern, diverse approaches, highlights the need to understand the specific characteristics of each technique and their implications for aesthetic outcomes. The author aims to provide a detailed review of 4 major buttock augmentation techniques: gluteal implants, Brazilian butt lift (BBL), intramuscular polymethylmethacrylate (PMMA), and deep subcutaneous hyaluronic acid fillers. The goal is to assess the benefits and limitations of each method, helping practitioners and patients make informed decisions tailored to their preferences and needs. A comprehensive literature review was conducted, incorporating clinical studies, case reports, and expert opinions on these 4 techniques. Evaluation criteria included effectiveness, safety, recovery time, and patient satisfaction. Data were synthesized to provide a comparative analysis of each method. Gluteal implants offer predictable volume but involve surgical risks and lengthy recovery. The BBL, using autologous fat, delivers natural results and body contouring benefits but carries risks such as fat embolism and fat reabsorption. Intramuscular PMMA fillers provide permanent results with minimally invasive application but are challenging to remove. Hyaluronic acid fillers are reversible and minimally invasive but require periodic maintenance and may present risks like material migration. In this review, the author highlights the advantages and drawbacks of each technique, emphasizing individualized assessments and practitioner expertise. By outlining these methods, the author supports informed decision making in buttock augmentation.

Level of Evidence: 5 (Therapeutic)
GUEST: an R package for handling estimation of graphical structure and multiclassification for error-prone gene expression data
Authors: Chen Li-Pang , Tsao Hui-Shan
Published: December 2024

In bioinformatics studies, understanding the network structure of gene expression variables is one of the main interests. In the framework of data science, graphical models have been widely used to characterize the dependence structure among multivariate random variables. However, the gene expression data possibly suffer from ultrahigh-dimensionality and measurement error, which make the detection of network structure challenging and difficult. The other important application of gene expression variables is to provide information to classify subjects into various tumors or diseases. In supervised learning, while linear discriminant analysis is a commonly used approach, the conventional implementation is limited in precisely measured variables and computation of their inverse covariance matrix, which is known as the precision matrix. To tackle those challenges and provide a reliable estimation procedure for public use, we develop the R package GUEST, which is known as Graphical models for Ultrahigh-dimensional and Error-prone data by the booSTing algorithm. This R package aims to deal with measurement error effects in high-dimensional variables under various distributions and then applies the boosting algorithm to identify the network structure and estimate the precision matrix. When the precision matrix is estimated, it can be used to construct the linear discriminant function and improve the accuracy of the classification.

Availability and implementation

The R package is available on https://cran.r-project.org/web/packages/GUEST/index.html.
‘Behind the scenes’ of a clinic appointment: insights from the patient experience of eczema
Authors: Patel Ria
Published: December 2024

This article reflects on my experience as both a clinical medical student and a dermatology patient, providing insights into the lived experience of a patient with eczema beyond the clinic setting. It offers a patient’s perspective on how clinicians can empower patients through clear communication and by acknowledging the daily impact of their condition.
A data-driven framework for biomarker discovery applied to optimizing modern clinical and preclinical trials on Alzheimer’s disease
Authors: Llorente-Saguer Isaac , Oxtoby Neil P
Published: December 2024

PET is used to measure tau protein accumulation in Alzheimer’s disease. Multiple biomarkers have been proposed to track disease progression, most notably the standardized uptake value ratio of PET tracer uptake in a target region of interest relative to a reference region, but literature suggests these region choices are nontrivial. This study presents and evaluates a novel framework, BioDisCVR, designed to facilitate the discovery of useful biomarkers, demonstrated on [18F]AV-1451 tau PET data in multiple cohorts. BioDisCVR enhances signal-to-noise by conducting a data-driven search through the space of possible combinations of regional tau PET signals into a ratio of two composite regions, driven by a user-defined fitness function. This study compares ratio-based biomarkers discovered by the framework with state-of-the-art standardized uptake value ratio biomarkers. Data used is tau PET regional measurements from 198 individuals from the Alzheimer’s Disease Neuroimaging Initiative database, used for discovery, and 42 from the Mayo Clinic Alzheimer’s Disease Research Center and Mayo Clinic Study of Aging (MCSA), used for external validation. Biomarkers are evaluated by calculating clinical trial sample size estimates for 80% power and 20% effect size. Secondary metrics are a measure of longitudinal consistency (standard deviation of linear mixed-effects model residuals), and separation between cognitive groups (t-statistic of the change over time due to being cognitively impaired). When applied to preclinical (secondary prevention with CU individuals) and clinical (treatment aimed at cognitively impaired individuals) trials on Alzheimer’s disease, our data-driven framework BioDisCVR discovered ratio-based tau PET biomarkers vastly superior to previous work, both reducing measurement error and sample size estimates for hypothetical clinical trials. Our analysis suggests remarkable potential for patient benefit (reduced exposure to health risks associated with experimental drugs) and substantial cost savings, through accelerated trials and reduced sample sizes. Our study supports the leveraging of data-driven methods like BioDisCVR for clinical benefit, with the potential to positively impact drug development in Alzheimer’s disease and beyond.