bluuebunny/crossref_metadata_2025 huggingface dataset:
The effects of resistivity on oscillatory reconnection and consequences for solar flare quasi-periodic pulsations
Authors: Schiavo Luiz A. C. A. , Stewart James , Browning Philippa K.
Published: October 2024

Quasi-periodic pulsations are often observed in flare emissions. While these may reveal much about the time-dependent reconnection involved in flare energy release, the underlying mechanisms are still poorly understood. In this paper, we use 2D magnetohydrodynamic simulations to investigate the magnetic reconnection in two merging flux ropes, focusing on the effects of the resistivity on the time variation of the reconnection. We consider both uniform resistivity and current-dependent anomalous resistivity profiles. Our findings reveal that resistivity plays a critical role in controlling the reconnection dynamics, including reconnection rate oscillations and the rate of decay of the reconnection rate. Resistivity also influences the oscillations in emitted gyrosynchrotron radiation. However, in contrast to this strong influence of resistivity on reconnection rates, we observed a different behavior for the emitted waves, whose frequencies are almost independent of resistivity variations.
Parametric assessment and multi-objective optimization of an ejector-enhanced compressed air energy storage system based on conventional and advanced exergy
Authors: Liu Tongqing , Wu Shuhong , Zhong Like , Yao Erren , Hu Yang , Xi Guang
Published: October 2024

Compressed air energy storage systems offer an effective solution to the intermittency and fluctuation challenges associated with renewable energy grid integration. A significant challenge in current compressed air energy storage systems is the substantial energy loss incurred during the discharge due to throttling processes, which is crucial for improving round-trip efficiency. Therefore, an ejector-enhanced compressed air energy storage system (EA-CAES system) is proposed in this study, characterized by the employment of ejector to reduce the pressure loss caused by the throttling process. The performance of the system is analyzed from both sensitivity analysis and multi-objective optimization. Conventional exergy analysis is used to estimate the locations and magnitudes of exergy destruction within the system, and advanced exergy analysis is applied to determine the interactions among components and to identify the potential for system performance improvement. The results showed that, compared to the advanced adiabatic compressed air energy storage system, the round-trip efficiency of the proposed system increased by 3.07%, and the total exergy destruction during the pressure reduction process was reduced by 401.9 kW. As for the sensitivity for components in the EA-CAES system, the avoidable exergy destruction of the ejector is the most sensitive to changes in all parameters, followed by the unavoidable exergy destruction of the heat exchangers in the charging and discharging processes influenced by the air storage pressure and throttling pressure, respectively. Finally, based on the best trade-off solution among multi-objective optimization, the ejector, turbine, and compressor should be paid special attention to the system improvement according to the advanced exergy analysis.
Accuracy bottlenecks in impedance spectroscopy due to transient effects
Authors: Lopez-Richard Victor , Pradhan Soumen , Castelano Leonardo K. , Wengenroth Silva Rafael Schio , Lipan Ovidiu , Höfling Sven , Hartmann Fabian
Published: October 2024

Impedance spectroscopy is vital for material characterization and assessing electrochemical device performance. It provides real-time analysis of dynamic processes such as electrode kinetics, electrons, holes or ion transport, and interfacial or defect driven phenomena. However, the technique is sensitive to experimental conditions, introducing potential variability in results. The intricate interplay of transient effects within the realm of spectral impedance analyses introduces a layer of complexity that may impede straightforward interpretations. This demands a nuanced approach for refining analytical methodologies and ensuring the fidelity of impedance characterization once the dynamic contributions of transient ingredients cannot be disentangled from the underlying steady-state characteristics. In our study, we experimentally identify that the transient effects in a memristor device are most pronounced near an optimal frequency related to intrinsic relaxation times, with these effects diminishing as the frequency varies beyond or below this range. While inherent systematic errors impose a practical limit (accuracy floor) on achievable measurement accuracy, this paper offers qualitative and quantitative insights into how specific procedures affect this limit and how to reduce it in orders of magnitude. Only by effectively addressing these errors, we can push beyond this constraint.
Enhancing quantum cascade laser active region design through inverse neural networks: A machine learning approach to metric-based structure generation
Authors: Hu Y. , Suri S. , Kirch J. , Knipfer B. , Jacobs S. , Yu Z. , Botez D. , Mawst L. J.
Published: October 2024

In this study, we introduce an automated design method for Quantum Cascade Laser (QCL) active region (AR) structure employing a generative neural network, termed an inverse network, which creates the structure designs based on specific k · p metric inputs related to device performance. The training dataset, derived from an earlier study, was selectively filtered to remove entries affected by energy-level hybridization or splitting, yielding ∼300 000 valid entries. A pre-trained forward network that processes QCL-AR structures and returns corresponding k · p metrics serves as the evaluator for the inverse network, supplanting traditional loss functions such as mean squared error or mean absolute error. This strategy overcomes the problem of non-uniqueness in the mapping from k · p metrics to QCL-AR structures. The inverse network incorporates a random layer, allowing it to produce a variety of QCL-AR structures from identical predicted metrics, thereby increasing the model’s practicality. Performance testing indicates high accuracy in the metrics of the generated QCL-AR structures, with the coefficient of determination, R2 scores, for key energy-level differences between the upper-laser (ul) level and the lower-laser level, E43, and between the next-higher-energy level above the ul level and the ul level, E54, of 0.9153 and 0.9701, respectively; and for the electron lifetimes τ43 and τ54 of 0.9568 and 0.9175. As an example, we show how the network generates a QCL-AR structure with the potential for low threshold-current density by suppressing shunt-type carrier leakage from the ul level through a higher energy AR state.
Genetic algorithm driven optimization of a guided mode resonator coupled to an infrared nanocrystal film
Authors: Abadie Claire , Ledos Nicolas , Mou Ye , Cavallo Mariarosa , Bossavit Erwan , Zhang Huichen , Colle Albin , Gemo Tommaso , Khalili Adrien , Prado Yoann , Gallas Bruno , Vincent Gregory , Mivelle Mathieu , Lhuillier Emmanuel
Published: October 2024

Nanocrystal (NC)-based devices suffer from a trade-off between absorption, pushing for thicker films, and charge conduction that is only efficient over a few NC sizes. Therefore, the design of detectors based on NCs strongly benefits from the introduction of optical resonators that engineer the light–matter coupling. Traditionally, the design of such a cavity relies on analytic scaling rules. However, the design becomes far more complex when multiple resonances are targeted, requiring alternative design strategies. In this study, we explore how infrared nanocrystals can be coupled to a guided mode resonator to achieve a broadband enhancement of absorption. A genetic algorithm is used to systematically investigate how geometric factors can be tuned to increase the absorption × bandwidth product. In comparison to the pristine film, a significant increase in absorption was demonstrated across the targeted spectral range (1–2.5 μm). The detector based on the design metasurface exhibited high detectivity (2 × 1010 Jones @ 200 K) and fast time response (18 ns).
Position query-guided cross-modal flow field prediction model of a transonic compressor cascade
Authors: Wang Liyue , Zhang Haochen , Lan Xinyue , Wang Cong , Qin Sheng , Sun Gang , Feng Jinzhang
Published: October 2024

The gradient of flow parameters in a transonic compressor cascade flow field varies significantly, especially in the region of shock waves, which causes a significant challenge to its high-precision flow field prediction. In this study, the position query-guided cross-modal flow field prediction model (PGCM) is proposed to effectively predict the flow field parameter distribution of a transonic compressor cascade. The PGCM utilizes the self-attention mechanism for the global and deep geometric feature extraction of configurations, which contributes to an in-depth understanding of the spatial relationships between coordinate points within the flow field, accurately capturing and analyzing the structural complexity of a compressor cascade flow. In addition, the PGCM integrates the cross-attention mechanism that establishes correlations between different input sequences, which enhances the performance of the model in querying and interpreting flow parameters at specific coordinates. The flow field prediction models are developed to predict the flow parameter distributions of different cascade geometries at Mach numbers of 0.78 and 0.93, respectively. The validation results indicate that the PGCM performs significantly better than the existing convolutional neural network and vision transformer, especially in the prediction of the pressure coefficient Cp distribution. The PGCM is adaptable to the variation of flow conditions and geometrical configurations efficiently and accurate in predicting the flow field of a compressor cascade. This paper demonstrates the promising potential of conducting the multi-modal information fusion to enhance the capability of flow field prediction.
Microsphere-enhanced fluorescence collection for nitrogen vacancy centers in diamond
Authors: Wu Shu-Hao , Lekavicius Ignas , Wang Hailin
Published: October 2024

We report experimental studies of microsphere-enhanced fluorescence collection of nitrogen vacancy (NV) centers using silica microspheres with diameters ranging between 15 and 50 μm and employing 20× and 40× objectives with numerical aperture of 0.42 and 0.64, respectively. Photoluminescence-excitation saturation counts as high as 95 kHz have been observed. These studies show that due to the effective collimation of fluorescence by the microsphere, objectives with relatively low numerical aperture (NA) can be used without sacrificing collection enhancement, in agreement with a theoretical model based on Mie scattering. The large enhancement of fluorescence collection with relatively low NA objectives, which feature extralong working distance and are relatively inexpensive, can potentially enable wider use of NV-based quantum sensing in real world applications.
Coupled heat and fluid transport in pulled extrusion of optical fiber preforms
Authors: Yuwono Eunice B. , Stokes Yvonne M. , Tronnolone Hayden , Wylie Jonathan J.
Published: October 2024

In the fabrication of optical fibers, the viscosity of the glass varies dramatically with temperature so that heat transfer plays an important role in the deformation of the fiber geometry. To date, models of fiber drawing processes have either assumed isothermal conditions or that advection is the dominant heat-transfer mechanism, with conduction therefore neglected. While advective heat transfer and neglect of conduction are valid in the fast process of drawing a preform to a fiber, heat conduction is also important in the slow process of extruding a fiber preform. In this paper, we derive and solve, in the context of pulled extrusion, a coupled heat and fluid flow model that incorporates heat conduction. The dramatic variation of viscosity with temperature means that this problem is extremely challenging to solve via standard numerical techniques and we therefore develop a novel finite-difference numerical solution method that proves to be highly robust. We use this method to show that conduction significantly affects the size of internal holes at the exit of the device and hence has important consequences for the process of manufacturing optical fibers.
Applicability of ensemble learning in total organic carbon and porosity evaluation of shales
Authors: Zhang Luchuan , Li Yibo , Zhang Lei , Xiao Dianshi , Zhang Haijie , Zhang Xuejuan , Liu Ruhao , Luo Tongtong , Xing Yabing , Chen Weiming , Jiang Lin , Chen Lei , Wang Bo
Published: October 2024

Accurate evaluation of total organic carbon (TOC) content and porosity is of paramount significance for assessment and target interval selection for shale reservoirs. This study takes shales from the western Chongqing area as an exemplary case to delve into the applicability and reliability of ensemble learning in evaluating TOC content and porosity. The results indicate that although both Light Gradient Boosting Machine (LightGBM) and Random Forest (RF) algorithms are suitable for evaluating TOC content and porosity in shales, LightGBM algorithm is preferred due to its comprehensive advantages, including higher accuracy, stronger generalization capability, and faster operating speed. For TOC content evaluation, the four most important logging parameters identified by LightGBM and RF are consistent, but exhibit different orders: DEN (compensated density) > GR (gamma ray) > U (uranium) > CNL (compensated neutron) and DEN > U > GR > CNL, respectively. For porosity evaluation, LightGBM and RF identify the same type and order of the three most important logging parameters: AC (acoustic transit time) > DEN > U. This similarity may be attributed to the fact that both algorithms utilize Classification and Regression Tree (CART) as base learners. The dependence plots between SHAP (SHapley Additive exPlanations) values and logging parameters reveal that the role of each logging parameter in the evaluation model is segmented, rather than exhibiting a continuous linear contribution. In conclusion, given the exceptional performance of ensemble learning algorithms, they, especially LightGBM algorithm, are highly recommended for shale evaluation.
Infrared dual-band multi-focus full Stokes metalens for polarization detection
Authors: Guo Siyu , Liang Zhongzhu , Shi Xiaoyan , Yang Fuming , Li Jinhuan , Wu Zhe , Hou Enzhu , Sun Wenwen , Chen Xiangtao , Wei Xintong , Liu Junying
Published: October 2024

Infrared polarization detection has attracted wide applications in military and civilian fields by demonstrating more accurate target detection and identification capabilities due to more dimensional target information. A multifocal metalens for simultaneous detection of the polarization state of incident light at dual wavelengths is proposed based on the independent control of orthogonally polarized light. When light is incident at different wavelengths, the metalens array splits and focuses the light on three different polarization bases to form six focal points with various positions. When the incident light with varying states of polarization of dual wavelengths to be detected passes through the substrate and reaches the metalens array, the incident light detected in each wavelength forms six focal points at different positions of the focal plane of the metalens. The Stokes parameters are calculated based on the intensities of the six polarization components in the same focal plane to determine the polarization data of the azimuthal and elliptic angles of the incident light detected in each wavelength. In addition, the theoretical Stokes parameters of incident light with different polarization states at two wavelengths are compared with the reconstructed Stokes parameters, proving our method's validity. The device can directly examine the polarization state of the incident light in mid-wave infrared and long-wave infrared, significantly simplifying the polarization detection system.
Study of the effect of outlet radius on the cavitation performance of a hydrodynamic torque converter
Authors: Ran Zilin , Zhou Huanhui , Yang Weida , Lu Shuoshuo , Chen Xianwei , Chai Bosen
Published: October 2024

The inlet and outlet radii are important design parameters that directly determine the internal/external characteristics and cavitation characteristics of the torque converter (TC). The stator and turbine are the main areas of cavitation in TCs. Based on this, the outlet radius of the stator and turbine is taken as the research object of this paper. In this study, computational fluid dynamics (CFD) models of different turbine and stator outlet radii are established, and the influence of stator/turbine outlet radius design parameters on the performance of TCs is revealed by comparing the internal/external characteristics and cavitation characteristics. The results show that reducing the outlet radius of the stator/increasing the outlet radius of the turbine will cause the stator and the turbine blade to be shorter, increase the area of the vaneless region between the impellers, and reduce the risk of cavitation in TCs. However, it will also lead to a decrease in the external characteristics of the low-speed ratio (SR) condition and an increase in the external characteristics of the high-SR condition. With the decrease in the stator outlet radius/the increase in the turbine outlet radius, the mass flow rate of TCs will decrease, and the mass flow loss caused by cavitation will decrease from the original 42.51 to 6.95 and 21.95 kg/s, respectively. The suppression rates of the stator/turbine outlet radius on TC cavitation volume are 58.894% and 52.359%, respectively. The research results of this study can provide practical engineering guidance for the design of high-performance TCs and cavitation suppression.
Magnetization reversal and temperature characteristic in synthetic antiferromagnets
Authors: He Kaizhou , Xie Mingling , Yun Chaoxin , Liu Bin , Meng Shuangyan , Qiang Jin , Wang Xiangqian , Gao Xiaoping
Published: October 2024

Understanding the magnetization reversal and temperature characteristics of synthetic antiferromagnets (SAFs) is helpful for optimizing the magnetic properties. In this study, a series of synthetic antiferromagnets with perpendicular magnetic anisotropy are deposited. The four stable magnetic states of the SAF are determined by the mutual alignment of magnetic moments in the layers and are controlled by both the magnetic interlayer exchange interaction and Zeeman energy. First order reversal curves were employed to investigate magnetization reversal behaviors and distinguish between reversible and irreversible components. An innovative approach to enhancing the antiferromagnetic coupling field and thermal stability involves introducing a Ru insertion and increasing the thickness of the adjacent magnetic layer.
Mechanical vibration-induced suppression of transverse acoustic phonons in silicon due to Akhiezer damping
Authors: Jin Jae Sik
Published: October 2024

Thermoelectric modules that utilize waste heat from machinery are inevitably exposed to mechanical vibrations. Here, we investigated the effects of mechanically induced phonon anharmonicity on Akhiezer damping with three different vibrational modes: Lamé, square extensional, and width extensional modes. We showed complete suppression of the transverse acoustic phonons at 300 K or above for the Lamé mode resonator, which is the reason why the mode has a high quality factor. Our results provide a new fundamental understanding of mechanically induced phonon scattering and rationally enable the design of thermoelectric modules to achieve high performance via mechanical vibrations when they are exposed to mechanical motion. Moreover, this should pave the way for studies of oscillatory motion in short-time-scale vibrational resonators.
A multi-scale temporal convolutional capsule network with parameter-free attention module-dynamic routing for intelligent diagnosis of rolling bearing
Authors: Jin Yulin , Hao Liang , He Xinghua , Liu Zhiwen
Published: October 2024

We proposed a multi-scale temporal convolutional capsule network model coupled with a parameter-free attention module and dynamic routing mechanism to analyze complex vibration signals for diagnosing the health of bearings. The proposed method utilizes a capsule network as the fundamental architecture. Instead of a convolutional neural network, a temporal convolutional network is employed. Additionally, a multi-scale feature fusion module is integrated into the capsule network structure to dynamically extract various layers of features from fault samples, enhancing the discriminatory capability of abnormal data. Subsequently, the parameter-free attention module and dynamic routing mechanism are employed to construct digital capsules. This allows the smallest unit capsule in a single layer to carry more information, enhance the similarity between the instance primary capsule and the fault capsule, reduce the interference of irrelevant features to the model, and improve the accuracy of fault type recognition. Finally, a multi-scale temporal convolutional capsule network model that integrates feature extraction and pattern recognition is established to perform end-to-end diagnosis of the bearing. Experimental findings suggest that the proposed method outperforms other deep learning methods in terms of accuracy and robustness. It can provide a theoretical basis and implementation path for the detection and diagnosis of train wheelset bearing time series abnormal data.
Research on impedance measurement based on Gallium Nitride Transistor
Authors: Liu Chi , Zhang Zhe , Liu Yuan
Published: October 2024

Impedance measurement has broad applications in fields such as electrochemistry, biology, medicine, and food safety. Typically, frequency response analyzers are used for small signal disturbance measurements, but they come with drawbacks such as high cost, large size, and limited excitation capabilities. To address the need for wide-band, large-signal, and portable impedance measurement in electrochemical applications, a novel scheme based on a Gallium Nitride device excitation circuit and amplitude-phase discrimination module is proposed. A multiphase cascade frequency-doubling buck circuit is used to inject disturbance signals into the impedance under test, and impedance parameters are obtained using discrete fourier transformafter signal sampling. By varying the frequency of the disturbance signal, impedance information across different frequencies can be captured. In this approach, the amplitude-phase discrimination module replaces the frequency response analyzer, reducing the overall size of the measurement system, while the power device-based excitation circuit enables large signal disturbances.
A mode shape sensitivity-based wavelet feature extraction method for interface debonding detection in concrete-filled steel tubes
Authors: Khanahmadi Mohtasham , Mirzaei Borhan , Amiri Gholamreza Ghodrati , Gholhaki Majid , Rezaifar Omid
Published: October 2024

The use of concrete-filled steel tube (CFST) composite columns is increasingly prevalent in the construction industry, particularly in high-rise structures. A common issue in CFST columns is interface debonding between the concrete core and the steel tube. If this debonding progresses both superficially and deeply, it can lead to instability and buckling of the column, posing a serious threat to the overall structural integrity. This study presents an innovative and effective method for extracting damage-sensitive features using horizontal, vertical, and diagonal detail coefficients derived from the wavelet analysis of corrected modal signals. The study introduces the total normalized irregularity detection index (NIDIT) as a damage detection metric. The results indicate that NIDIT is highly effective in identifying and detecting debonding regions. NIDIT quantifies the accumulation of irregularities and disturbances in the affected areas, allowing for the detection of concrete surface debonding from the steel tube. The findings show that NIDIT can accurately and efficiently detect damage in middle and end-edge regions, addressing a significant challenge in structural health monitoring with high precision.
Strengthening by {110} and {112} edge dislocations in BCC high entropy alloys
Authors: Liu Xin , Barreira Rui , Rahbar Niazi M , Curtin W A
Published: October 2024

Mechanical tests and microscopy studies on body-centered cubic (BCC) high entropy alloys reveal transitions from screw to edge dislocation slip and from {110} to {112} slip plane activity. Here, a strengthening theory for BCC edge dislocation slip on {112} planes is thus developed that parallels a recent theory for {110} slip. Using the atomistic dislocation pressure fields for four BCC elements (Nb, Ta, Mo, W) as proxies to span the range of likely alloy cores, theory predicts that the zero temperature yield strength for {112} slip is slightly lower (0%–20%) than that for {110} slip but that the associated energy barrier is slightly (0%–20%) higher. This leads to cancelling effects, and hence very similar strengths, at finite temperatures and strain rates. Full atomistic results on selected dilute binary alloys show some shifts in these trends, but with similar magnitudes and cancelling effects. The close strengths of {110} and {112} slip modes indicate that subtle aspects beyond the scope of the theory will determine which slip system controls the observed strengthening. This closeness in strength cements the use of the {110} edge theory for guiding alloy design independent of actual slip system.
High-sensitivity and spatial resolution benchtop cone beam XFCT imaging system with pixelated photon counting detectors using enhanced multipixel events correction method
Authors: Pu Shaozhou , Song Jiadan , Lu Hongbing , Zhang Wenli , Li Liang
Published: October 2024

Objective. High atomic number element nanoparticles have shown potential in tumor diagnosis and therapy. X-ray fluorescence computed tomography (XFCT) technology enables quantitative imaging of high atomic number elements by specifically detecting characteristic x-ray signals. The potential for further biomedical applications of XFCT depends on balancing sensitivity, spatial resolution, and imaging speed in existing XFCT imaging systems. Approach. In this study, we utilized a high-energy resolution pixelated photon-counting detector for XFCT imaging. We tackled degradation caused by multi-pixel events in the photon-counting detector through energy and interaction position corrections. Sensitivity and spatial resolution imaging experiments were conducted using PMMA phantoms to validate the effectiveness of the multi-pixel events correction algorithm. Main results. After correction, the system’s sensitivity and spatial resolution have both improved. Furthermore, XFCT/CBCT dual-modality imaging of gadolinium nanoparticles within mice subcutaneous tumor was successfully achieved. Significance. These results demonstrate the preclinical research application potential of the XFCT/CBCT dual-modality imaging system in high atomic number nanoparticle-based tumor diagnosis and therapy.
Development of a flat cutoff probe covered with a dielectric layer for non-invasive plasma diagnostics
Authors: Chae Gwang-Seok , Yeom Hee-Jung , Yoon Min Young , Kim Jung-Hyung , Lee Hyo-Chang
Published: October 2024

Herein, we investigated the effect of a dielectric film on the transmission spectrum of a bar-type flat cutoff probe (BCP). By conducting electromagnetic wave simulations, we found that placing a dielectric film with a thickness of 1 mm or less on the sensor did not affect the measurement of the BCP under thin sheath condition. However, a film thickness of 1 mm or more results in a low-frequency shift in the cutoff frequency. The shift in the cutoff frequency was related not only to the film thickness, but also to the dielectric constant of the film and sheath width, which could be understood through a circuit model of the BCP. The calculated results were experimentally validated using alumina plates of various thicknesses. Consequently, our findings demonstrate that measuring the electron density on a BCP is feasible even when a dielectric film is deposited, thereby improving the accuracy of the measurement.
The geometry, purity, and grain orientation database of the Cu stabilizer layer and the effect on the electrical and thermal properties of commercial REBCO tapes
Authors: Li Chengyang , Suo Hongli , Zhang Zili , Zhou Benzhe , Ma Lin , Liu Jianhua , Wang Lei , Wang Qiuliang
Published: October 2024

Building upon our previous database of the thermal, electrical, and mechanical properties of commercial REBCO tape, we have constructed a subsequent database focusing on the Cu layer of such tapes from eight distinct manufacturers. This database encompasses information pertaining to the geometry, purity, and grain orientation of the Cu layer. The primary objective of this database is to not only elucidate the material science of the Cu layer across various commercial tapes but also to establish correlations between the thermal, electrical, and mechanical properties and the aforementioned geometry, purity, and grain orientation parameters. After analysis, three significant findings have been validated. Firstly, the non-uniformity of geometry plays a critical role in the electrical resistivity in the radial direction, primarily through altering the actual contact surface area. Secondly, it has been observed that the total grain boundary length per micrometer thickness exhibits a nearly linear correlation with the thermal conductivity in the circumferential direction. Thirdly, the purity of the Cu layer in all the commercial REBCO tapes is lower than anticipated. It is our aspiration that this database will facilitate enhanced comprehension of the Cu layer in REBCO tapes among a broader spectrum of researchers.
CFD analysis of the impact of corner adjustments in tall square buildings for wind load mitigation
Authors: Singh Ashish , Kontoni Denise-Penelope N , Mandal Sasankasekhar
Published: October 2024

Tall buildings face significant challenges due to wind loads. Therefore, it is crucial to accurately assess wind loads in the design of these structures. One effective strategy for tackling this issue is through aerodynamic modifications. This research paper explores the effectiveness of aerodynamic modifications in mitigating wind loads on tall square-shaped buildings through computational fluid dynamics (CFD) simulations using ANSYS Fluent software. Four corner modification strategies—chamfering, rounding, recessing, and double recessing—are applied to a square model with corner reductions of 5%, 10%, 15%, and 20%. Analysis of force and pressure coefficients for along-wind load, accompanied by the lift coefficient for across-wind load, reveals crucial insights. Chamfering proves optimal at a 5% corner reduction, while rounded and recessed corners excel at a 10% reduction. At a 15% reduction, rounded and chamfered corners demonstrate the highest effectiveness. Notably, rounded corners exhibit exceptional efficacy at a 20% reduction. These findings highlight the potential of corner adjustments as efficient strategies for substantial wind load mitigation on square-plan tall buildings. This research provides essential guidance for architects and engineers in optimizing the design of such structures, contributing to improved resilience against wind-induced forces.
Evaluating Natural Course Performance in Parametric G-formula: Review of Current Practice and Illustration Based on the United Autoworkers-General Motors Cohort
Authors: Lu Wenxin , Picciotto Sally , Costello Sadie , Colbeth Hilary , Eisen Ellen
Published: October 2024

The parametric g-formula is a causal inference method that appropriately adjusts for time-varying confounding affected by prior exposure. Like all parametric methods, it assumes correct model specification, usually assessed by comparing the observed outcome with the simulated outcome under no intervention (natural course). However, it is unclear how to evaluate natural course performance and whether other variables should also be considered. We reviewed current practices for evaluating model misspecification in applications of parametric g-formula. To illustrate the pitfalls of current practices, we then applied the parametric g-formula to examine cardiovascular disease mortality in relation to occupational exposure in the United Autoworkers-General Motors cohort (UAW-GM), comparing 20 parametric model sets and qualitatively assessing natural course performance for all time-varying variables over follow-up. We found that current practices of evaluating model misspecification are often insufficient, increasing risk of bias and statistical cherry picking. Based on our motivational analyses of the UAW-GM cohort, good natural course performance of the outcome does not guarantee good simulations of other covariates; poor predictions of exposures and covariates may still exist. We recommend reporting natural course performance for all time-varying variables at all time-points. Objective criteria for evaluating model misspecification in parametric g-formula need to be developed.
Canids in a changing climate: predicting range shifts and evolutionary rescue under distinct future scenarios
Authors: Porto Lucas M V , Bennett David , Maestri Renan , Etienne Rampal S
Published: October 2024

Human land use and climate change have profoundly impacted species distributions, with approximately a quarter of all known mammal species currently facing extinction threats. In this study, we modelled both present and future potential distributions of all 36 extant Canidae species to assess their responses to moderate and pessimistic future climatic scenarios. Additionally, we investigated the likelihood of canids experiencing evolutionary rescue, which could facilitate adaptation to climate change for certain species. We gathered species occurrence data for all extant canids and corresponding environmental variables for these locations. Our modelling results reveal that 32 species (89% of Canidae species) are projected to undergo range contractions owing to climate change, whereas four species (11% of canids) are expected to expand their ranges. Evolutionary analyses suggest that some canids might lack the capacity to adapt to the rapid pace of climate change, particularly Atelocynus microtis and Vulpes velox. Furthermore, our findings underscore the critical importance of incorporating variables related to proximity to water bodies to predict the future distributions of South American canids accurately.
‘Where is the Justice?’ Unauthorized Migrants’ Perceptions of the Legitimacy of the Dutch Immigration System
Authors: Kox M H (Mieke)
Published: October 2024

The legitimacy of immigration systems in a globalized world is questioned since individuals without legal status are excluded from states’ liberal political projects and presumed to hold beliefs different from those of the state. Drawing on ethnographic research with 105 unauthorized migrants in the Netherlands, this contribution demonstrates that these migrants may consider immigration systems to be legitimate if states lawfully enact them and provide access to their human rights. Yet, they believe that the Dutch authorities currently neglect these obligations, resulting in perceived legitimacy deficits. While some scholars advocate for new vocabulary to better understand these systems, I argue that the focus should be on changing these systems to ensure legitimacy and uphold the liberal principles of democracy.
Can dermatologists help save the planet?
Authors: Abdul Gafoor Shafiah Muna , Taheem Anjeli , Woodcock Emma , Nelson Toby
Published: October 2024

According to the British Society for Dermatological Surgery, simple aprons and nonsterile gloves should be considered in MMS and minor skin surgeries to improve sustainability practices. Therefore, between August 2020 and September 2022, we utilized two plastic aprons, one nonsterile glove pair (tumour-extirpation) and one sterile glove pair (reconstruction) in place of complete sterile PPE. No surgical gowns were used. Of the 410 MMS procedures conducted, only 1.7% (n = 7) had a minor postoperative surgical-site infection. Our data suggest that there are no significant differences in postoperative wound infections when using nonsterile PPE vs. sterile PPE in MMS. We encourage such safe, sustainable practices to help save the planet we live on!
Individual cognitive traits can be predicted from task-based dynamic functional connectivity with a deep convolutional-recurrent model
Authors: Almeida de Souza Erick , Vieira Bruno Hebling , Salmon Carlos Ernesto Garrido
Published: October 2024

There has been increased interest in understanding the neural substrates of intelligence and several human traits from neuroimaging data. Deep learning can be used to predict different cognitive measures, such as general and fluid intelligence, from different functional magnetic resonance imaging experiments providing information about the main brain areas involved in these predictions. Using neuroimaging and behavioral data from 874 subjects provided by the Human Connectome Project, we predicted various cognitive scores using dynamic functional connectivity derived from language and working memory functional magnetic resonance imaging task states, using a 360-region multimodal atlas. The deep model joins multiscale convolutional and long short-term memory layers and was trained under a 10-fold stratified cross-validation. We removed the confounding effects of gender, age, total brain volume, motion and the multiband reconstruction algorithm using multiple linear regression. We can explain 17.1% and 16% of general intelligence variance for working memory and language tasks, respectively. We showed that task-based dynamic functional connectivity has more predictive power than resting-state dynamic functional connectivity when compared to the literature and that removing confounders significantly reduces the prediction performance. No specific cortical network showed significant relevance in the prediction of general and fluid intelligence, suggesting a spatial homogeneous distribution of the intelligence construct in the brain.
Influenza Vaccine Effectiveness Against Illness and Asymptomatic Infection in 2022–2023: A Prospective Cohort Study
Authors: White Elizabeth B , Grant Lauren , Mak Josephine , Olsho Lauren , Edwards Laura J , Naleway Allison , Burgess Jefferey L , Ellingson Katherine D , Tyner Harmony , Gaglani Manjusha , Lutrick Karen , Caban-Martinez Alberto , Newes-Adeyi Gabriella , Duque Jazmin , Yoon Sarang K , Phillips Andrew L , Thompson Mark , Britton Amadea , Flannery Brendan , Fowlkes Ashley
Published: October 2024

Background

Previous estimates of vaccine effectiveness (VE) against asymptomatic influenza virus infection based on seroconversion have varied widely and may be biased. We estimated 2022–2023 influenza VE against illness and asymptomatic infection in a prospective cohort.

Methods

In the HEROES-RECOVER cohort, adults at increased occupational risk of influenza exposure across 7 US sites provided weekly symptom reports and nasal swabs for reverse transcription–polymerase chain reaction (RT-PCR) influenza testing. Laboratory-confirmed influenza virus infections were classified as symptomatic (≥1 symptom) or asymptomatic during the week of testing. Participants reported demographic information and vaccination through surveys; most sites verified vaccination through medical record and immunization registry review. Person-time was calculated as days from the site-specific influenza season start (September–October 2022) through date of infection, study withdrawal, or season end (May 2023). We compared influenza incidence among vaccinated versus unvaccinated participants overall, by symptom status, and by influenza A subtype, using Cox proportional hazards regression adjusted for site and occupation. We estimated VE as (1 − adjusted hazard ratio) × 100%.

Results

In total, 269 of 3785 (7.1%) participants had laboratory-confirmed influenza, including 263 (98%) influenza A virus infections and 201 (75%) symptomatic illnesses. Incidence of laboratory-confirmed influenza illness among vaccinated versus unvaccinated participants was 23.7 and 33.2 episodes per 100 000 person-days, respectively (VE: 38%; 95% CI: 15%–55%). Incidence of asymptomatic influenza virus infection was 8.0 versus 11.6 per 100 000 (VE: 13%; 95% CI: −47%, 49%).

Conclusions

Vaccination reduced incidence of symptomatic but not asymptomatic influenza virus infection, suggesting that influenza vaccination attenuates progression from infection to illness.
Ghrelin for neuroprotection in post-cardiac arrest coma: a 1-year follow-up of cognitive and psychosocial outcomes
Authors: van Gils Pauline , Nutma Sjoukje , Meeske Karen , van Heugten Caroline , van den Bergh Walter , Foudraine Norbert , le Feber Joost , Filius Margreet , van Putten Michel , Beishuizen Bert , Hofmeijer Jeannette ,   for the GRECO investigators, Nutma S , Beishuizen A , van den Bergh W M , Foudraine N A , le Feber J , Filius P M G , Cornet A D , Vermeijden J W , van der Palen J , van Putten M J A M , Hofmeijer J , van der Worp H B , Slooter A J C , van Smeeden M , Wilms E , Rinket Martin , Krol Tim , Visser Rosalie , van Veen Esther , Gijsbers Lucien , Fleuren-Janssen Manon , Kreijtz Michel , Tamminga Hester , Filius Margreet , Rinket Martin , Krol Tim , Addink Wim , Damink Rob , Snoek-Pecht Marlies , Kreijtz Michel , Tamminga Hester , Dittrich Suzanne , Bosma Margriet , Appeldoorn Jerôme , Elenbaas Jolanda , IJmker Vera , de Bever Laura , Roesink Ozzy
Published: October 2024

Aims

Effective treatments to improve brain recovery after cardiac arrest are needed. Ghrelin showed efficacy in experimental models and was associated with lower neuron-specific enolase levels in the clinical Ghrelin in Coma (GRECO) trial. Here, we present cognitive and psychosocial outcomes at 1-year follow-up.

Methods and results

GRECO was a Phase 2 multicentre, double-blind, randomized, placebo-controlled trial in comatose patients after cardiac arrest. The intervention was intravenous acyl-ghrelin 600 μg twice daily or placebo for 1 week, starting within 12 h after the arrest. Patients were assessed after 1 year using cognitive tests and questionnaires measuring participation, health-related quality of life, mood, and caregiver strain. Composite z-scores of the cognitive tests were computed by comparing the scores with those of a norm population and averaging the tests for memory, attention, and executive functioning separately. Groups were compared based on composite z-scores and cut-off scores for psychosocial outcomes. Of the 160 participants originally included, 66 of the 85 participants who survived to 1 year after OHCA completed the psychosocial and cognitive follow-up. The intervention group scored numerically higher across the cognitive domains compared with the control group, but the differences were not statistically significant (memory median = −0.850 vs. −1.385, U = 424.5, P = 0.587; attention median = −0.733 vs. −0.717, U = 420.5, P = 0.548; and executive functioning median = −0.311 vs. −0.482, U = 408.5, P = 0.323). There were significantly fewer signs of depression in the intervention group (U = 322.5, P = 0.014).

Conclusion

This predefined secondary analysis found that ghrelin treatment was associated with non-significantly but consistently better cognitive outcomes and significantly fewer signs of depression. This is in line with the primary outcomes.

Clinical trial registration

Clinicaltrialsregister.eu: EUCTR2018-000005-23-NL
Earnings Responses to Even Higher Taxes
Authors: Miao Dingquan , Selin Håkan , Söderström Martin
Published: October 2024

We exploit a recent Swedish tax reform, implying higher marginal tax rates for the top 5% of the earnings distribution, to learn about earnings responses to higher taxes. Using a simple and graphical cross-sectional method, we estimate an earnings elasticity of 0.16, evaluated four years after the reform. Our analysis indicates that the response is driven by adjustments in wage rates, and not by changes to hours, job switches or income shifting. We interpret the magnitude and preciseness of the response using a realistically calibrated simulation model in which people face uncertain marginal tax rates due to earnings dynamics.
Safety and Immunogenicity of an Adjuvanted Clostridioides difficile Vaccine Candidate in Healthy Adults: A Randomized Placebo-Controlled Phase 1 Study
Authors: Leroux-Roels Isabel , Alhatemi Azhar , Caubet Magalie , De Boever Fien , de Wergifosse Bertrand , El Idrissi Mohamed , Ferreira Guilherme S , Jacobs Bart , Lambert Axel , Morel Sandra , Servais Charlotte , Yarzabal Juan Pablo
Published: October 2024

Background

This study investigated the safety, reactogenicity, and immunogenicity in healthy subjects of a Clostridioides difficile vaccine candidate with/without adjuvant, targeting toxins A and B.

Methods

In this first-in-human, phase 1, observer-blind study, subjects aged 18–45 years were randomized to receive F2 antigen (n = 10) or placebo (n = 10), and subjects aged 50–70 years to receive F2 antigen plus AS01 adjuvant (n = 45), F2 antigen (n = 45), or placebo (n = 30) in 2 doses 1 month apart. A subcohort (n = 40) received a third dose 15 months later. Solicited adverse events (AEs) were recorded for 7 days and unsolicited AEs for 30 days after each dose. Immunogenicity was assessed at baseline and after each dose.

Results

Solicited AEs were transient and most frequent in subjects receiving F2 antigen plus AS01. No serious AEs were considered related to study vaccine. Immunogenicity was substantially higher in subjects receiving F2 antigen plus AS01 than subjects receiving F2 antigen alone. A third dose increased the immune response in subjects with baseline neutralization titers below the assay lower limit of quantitation.

Conclusions

The GSK C. difficile vaccine candidate was immunogenic, especially when given with AS01, and was well tolerated with an acceptable safety profile.

Clinical Trial Registration

NCT04026009.
Guidelines for the transfer of people living with HIV attending primary healthcare facilities in South Africa: a scoping review
Authors: Odayar Jasantha , Phillips Tamsin K , Hennessey Claudine , Myer Landon
Published: October 2024

People living with HIV may move between health facilities: this is called ‘transfer’, and includes up- and down-referral based on clinical condition and lateral transfer (e.g. between primary healthcare [PHC] facilities for reasons such as geographic mobility or stigma). Transfers involving PHC facilities occur frequently and are associated with viraemia and disengagement. We reviewed the South African National Department of Health (NDOH) and Southern African HIV Clinicians Society websites and contacted NDOH officials to identify national guidelines applicable to HIV care in South Africa for recommendations on transfers involving PHC facilities. In total, 21/24 (88%) documents mentioned transfer, using the terms ‘referral’, ‘linkage’, ‘transfer’, ‘transition’ and ‘handover’. Guidelines defined ‘linkage to care’ as connecting individuals to care after HIV testing, but other terms were not well defined. Documents emphasised transfers between different levels of the health system, and transfers between PHC facilities received limited attention. The transfer process was delineated for linkage to care, up- and down-referrals, but not for transfers between PHC facilities. Clinical management of patients transferring between PHC facilities and tracing of patients who requested transfers and missed their visits were not specified. Overall, transfers between PHC facilities were not well addressed and require attention to improve HIV treatment outcomes.