bluuebunny/crossref_metadata_2025 huggingface dataset:
Geschlechterunterschiede bei wissenschaftlichen Publikationen
Authors: Esser Julia , Sharma Shachi Jenny , Jansen Stefanie , Mayer Marcel , Jansen Louis , Klußmann Jens Peter , Lüers Jan Christoffer , Abing Helen
Published: January 2025

Ziel dieser Untersuchung war es, die Repräsentation von Frauen in der deutschsprachigen wissenschaftlichen Publikationslandschaft der HNO-Heilkunde zu untersuchen.

Die Autor*innenschaft wurde anhand von Artikeln überprüft, die zwischen 2013 und 2023 in den 2 größten HNO-Fachzeitschriften (Laryngo-Rhino-Otologie, HNO) veröffentlicht wurden, um die Häufigkeit und den prozentualen Anteil des Geschlechts bei der Erst- und Letztautor*innenschaft zu ermitteln.

Insgesamt wurden 2631 Artikel untersucht. Bei 699 (26,6%) der veröffentlichten Artikel waren Frauen Erstautorinnen und bei 384 (14,6%) der veröffentlichten Artikel waren Frauen Letztautorinnen. Es konnten deutliche Trends für den Anstieg des Frauenanteils beobachtet werden: Erstautorinnenpublikationen stiegen innerhalb des analysierten 10-Jahres-Zeitraums von 19,9% auf 34,5%, Letztautorinnenpublikationen stiegen von 9,4% auf 19,0%.

Der Anteil der Frauen, die Artikel als Erst- oder Letztautorin in der Hals-Nasen-Ohrenheilkunde veröffentlichen, ist zwar steigend, aber immer noch dürftig. Bemühungen zur Förderung der Geschlechtervielfalt können den Anteil von Frauen unter den Autor*innen von HNO-Literatur weiter erhöhen.
Surgical Technical Nuance of Exoscopic Cerebral Bypass Surgery Using the Mitaka 4K3D Exoscope
Authors: Aseged Mikael , Tanabe Jun , Opara Oluwamayowa , Kihara Kotaro , Sasaki Kento , Tanaka Riki , Hasebe Akiko , Haraguchi Kenichi , Yamada Yasuhiro , Fikru Ermiyas , Teshome Henok , Komatsu Fuminari , Nakahara Ichiro , Kato Yoko
Published: January 2025

Background and Objective Bypass surgery remains a crucial skill for neurosurgeons specializing in open or hybrid procedures. For years, these surgeries have been performed using an operating microscope. There have been limited publications on bypass surgeries using an exoscope. Here, we share our first-hand experience using the Mitaka HawkSight 4K3D HD exoscope in performing two bypass surgeries for moyamoya disease and intracranial atherosclerosis disease. The objective of the study is to show our experience and effectiveness of cerebral bypass with a Mitaka exoscope.

Methods We observed two patients operated with an Mitaka exoscope in our center in 2024.

Result The first case was a 35-year-old woman with moyamoya disease who presented with weakness for 1 month for which a combined bypass was done. The second case involved an 80-year-old male patient with cognitive impairment and right middle cerebral artery occlusion due to intracranial atherosclerosis disease, for which a direct bypass was done. In both instances, we utilized the exoscope with a 4K3D screen and 3D eyeglasses for enhanced visualization.

Conclusion Bypass surgery can be conducted using an exoscope, which provides 4K3D HD images displayed on a 55-inch screen, offering an optimal view for the entire operating room, including both scrubbed and unscrubbed personnel. Unlike an operating microscope, everyone sees the same image as the surgeon, enhancing coordination and understanding among the team. Mastering the exoscope requires a learning curve that depends on experience, repetition, and unwavering dedication.
The Prevalence of Septo-Optic Dysplasia in Neonates with Absent Cavum Septi Pellucidi Identified during Routine Prenatal Imaging
Authors: Phillipi Michael A. , Khaki Sheevaun , Kim Amanda J.H. , Regner Michael F. , Gievers Ladawna
Published: January 2025

Objective This study aimed to determine the prevalence of septo-optic dysplasia (SOD) in patients with prenatally identified absent cavum septi pellucidi (CSP), agenesis of the corpus callosum (ACC), or dysgenesis of the corpus callosum (DCC).

Study Design This retrospective chart review investigated neonates prenatally diagnosed with an absent CSP, ACC, or DCC who were admitted to a single quaternary academic medical center in the Pacific Northwest between 2016 and 2023. This prenatal diagnosis prompted a routine and protocolized postnatal workup for SOD including laboratory evaluation, imaging, and specialty consultation. Sociodemographic and clinical data were collected for eligible neonates and their birthing persons. The prevalence of SOD in patients with midline callososeptal anomalies was calculated.

Results Of the 86 patients prenatally diagnosed with absent CSP, ACC, and/or DCC, 36.0% (n = 31) were diagnosed postnatally with SOD. Of those diagnosed with SOD, 71.0% (n = 22) had isolated optic nerve hypoplasia, 9.7% (n = 3) had pituitary hormone abnormalities, and 19.4% (n = 6) had both. Seven patients required maintenance hydrocortisone, one required thyroid hormone replacement, and one required thyroid and growth hormones. Of the 26 patients with SOD who underwent genetic testing, 9 (34.6%) had one or more genetic differences detected.

Conclusion SOD was diagnosed in 36.0% of cases of prenatally diagnosed midline callososeptal anomalies. For patients with prenatally diagnosed midline callososeptal anomalies, a standardized, postnatal SOD evaluation allows timely diagnosis and prompts early intervention and hormone replacement, thus avoiding the consequences of a delayed diagnosis.

Key Points
Deciphering Abbreviations in Malaysian Clinical Notes Using Machine Learning
Authors: Sulaiman Ismat Mohd , Bulgiba Awang , Kareem Sameem Abdul , Latip Abdul Aziz
Published: January 2025

Objective This is the first Malaysian machine learning model to detect and disambiguate abbreviations in clinical notes. The model has been designed to be incorporated into MyHarmony, a natural language processing system, that extracts clinical information for health care management. The model utilizes word embedding to ensure feasibility of use, not in real-time but for secondary analysis, within the constraints of low-resource settings.

Methods A Malaysian clinical embedding, based on Word2Vec model, was developed using 29,895 electronic discharge summaries. The embedding was compared against conventional rule-based and FastText embedding on two tasks: abbreviation detection and abbreviation disambiguation. Machine learning classifiers were applied to assess performance.

Results The Malaysian clinical word embedding contained 7 million word tokens, 24,352 unique vocabularies, and 100 dimensions. For abbreviation detection, the Decision Tree classifier augmented with the Malaysian clinical embedding showed the best performance (F-score of 0.9519). For abbreviation disambiguation, the classifier with the Malaysian clinical embedding had the best performance for most of the abbreviations (F-score of 0.9903).

Conclusion Despite having a smaller vocabulary and dimension, our local clinical word embedding performed better than the larger nonclinical FastText embedding. Word embedding with simple machine learning algorithms can decipher abbreviations well. It also requires lower computational resources and is suitable for implementation in low-resource settings such as Malaysia. The integration of this model into MyHarmony will improve recognition of clinical terms, thus improving the information generated for monitoring Malaysian health care services and policymaking.
Progress in mid-infrared optoelectronics for high-speed free-space data throughput
Authors: Grillot Frédéric , Poletti Thomas , Pes Salvatore
Published: January 2025

Free-space laser communications offer a promising alternative for broadband data transmission in places where fiber optics are impractical. This technology, particularly effective at the 1.55 μm wavelength in the near infrared, also has potential applications in the medium-wave infrared (MWIR, 3–5 μm) and long-wave infrared (LWIR, 8–14 μm) ranges. MWIR and LWIR are superior for transmission through fog, clouds, and dust, with LWIR offering stealth advantages thanks to natural thermal radiation. In addition, mid-infrared wavelengths benefit from reduced atmospheric scattering and signal distortion, making them much more reliable for free-space optical communications. Quantum cascade devices such as lasers, modulators, and detectors operating in the MWIR and LWIR ranges are seen as high-potential candidates for data transmission under poor weather conditions or in degraded environments. This Perspective reviews advances in mid-infrared optoelectronics and their applications in high-speed data transmission and integrated photonic technologies, offering insights for researchers and engineers working in this field.
Membrane-free redox flow battery: From the idea to the market
Authors: Navalpotro Paula , Palma Jesus , Muñoz-Perales Vanesa , Martínez-Bejarano Antonio , Martín-Arroyo María Victoria , Taylor David P. , Platek-Mielczarek Anetta , Rivano Pier Giuseppe , Paratore Federico , Re Emilio Dal , Marcilla Rebeca
Published: January 2025

The increasing global energy demand and the transition toward a more sustainable energy system necessitate the integration of renewable sources, emphasizing the need for effective energy storage systems. Redox flow batteries (RFBs) are particularly suitable due to their efficiency and unique ability to decouple energy and power density. However, their widespread adoption is hindered by the high costs of ion-selective membranes and vanadium-based electrolytes currently used in commercial vanadium RFBs. This study analyzes an alternative membrane-free (membraneless) flow battery technology that relies on immiscible electrolytes, which spontaneously separate into two distinct liquid phases, eliminating the need for an ion-selective membrane or any other kind of physical separator. This approach promises to address key hurdles in advancing RFB technology by reducing overall costs while enhancing sustainability and overall performance. Here, we examine the fundamentals, evolution, and development needed for market implementation of this innovative technology.
Entropy-based methods for formulating bottom-up ultra-coarse-grained models
Authors: Sahrmann Patrick G. , Voth Gregory A.
Published: January 2025

Bottom-up coarse-grained (CG) modeling is an effective means of bypassing the limited spatiotemporal scales of conventional atomistic molecular dynamics while retaining essential information from the atomistic model. A central challenge in CG modeling is the trade-off between accuracy and efficiency, as the inclusion of often pivotal many-body interaction terms in the CG force-field renders simulation markedly slower than simple pairwise models. The Ultra Coarse-Graining (UCG) method incorporates many-body terms through discrete internal state variables that modulate the CG force-field according to, e.g., changes in local environment when substantial chemical heterogeneities exist. However, assigning optimal internal states systematically from atomistic simulation data, as well as the practical application of bottom-up UCG theory to biomolecular systems, remain open problems. We develop two synergistic methods to aid in the development of UCG models that can capture inhomogeneities in atomistic systems such as those induced by phase coexistence. The first method establishes the systematic construction of UCG force-fields from a relative entropy minimization principle, while the second method utilizes machine-learning to obtain optimal local order parameters for enhanced model efficiency and transferability. We apply these methods to a methanol liquid–vapor interface and the ripple phase of a 1,2-dipalmitoyl-sn-glycero-3-phosphocholine lipid bilayer and demonstrate that UCG modeling alone recapitulates aspects of phase coexistence that are otherwise not observed in CG modeling.
Multi-functional broadband diffractive neural network with a single spatial light modulator
Authors: Li Bolin , Zhu Yinfei , Fei Jinlei , Zheng Runshi , Gu Min , Lin Jian
Published: January 2025

Diffractive neural networks (DNNs) are emerging as a novel optical computing architecture that combines wave optics with deep-learning methods for high-speed parallel information processing. Herein, we report a reflection type, multi-functional, broadband DNN design. It consists of two phase-modulation layers based on a single spatial light modulator and a mirror facing it. The power efficiency of this design is more than 16 times higher than that of the cascaded structure utilizing beam splitters. It can function either as a two-layer DNN or a one-layer DNN with the other serving as an information input layer. Single- and dual-wavelength filtering and focusing, as well as spatial wavelength demultiplexing of supercontinuum, are experimentally demonstrated using the two-layer DNN, whereas the one-layer DNN is experimentally demonstrated by the classification of hand-written digits, which are input by the first layer via holographic imaging. The designed DNN could operate independently or be readily integrated with other optical systems and may find applications in spectroscopy, microscopy, and information technology.
Centriole structural integrity defects are a crucial feature of hydrolethalus syndrome
Authors: Curinha Ana , Huang Zhaoyu , Anglen Taylor , Strong Margaret A. , Gliech Colin R. , Jewett Cayla E. , Friskes Anoek , Phan Thao P. , Nicholas Zachary , Holland Andrew J.
Published: January 2025

Hydrolethalus syndrome (HLS) is a lethal, autosomal recessive ciliopathy caused by the mutation of the conserved centriole protein HYLS1. How HYLS1 controls centriole function is poorly understood. Here, we show that mice harboring the HYLS1 disease mutation die shortly after birth and exhibit developmental defects that recapitulate several manifestations of HLS. These phenotypes arise from a loss of centriole integrity that causes tissue-specific defects in cilia assembly and function. We show that HYLS1 is recruited to the centriole by CEP120 and stabilizes the localization of centriole inner scaffold proteins that ensure the integrity of the centriolar microtubule wall. The HLS disease mutation reduced the centriole localization of HYLS1 and caused degeneration of the centriole distal end. We propose that tissue-specific defects in centriole integrity caused by the HYLS1 mutation prevent ciliogenesis and contribute to HLS phenotypes.
Prickle2 regulates apical junction remodeling and tissue fluidity during vertebrate neurulation
Authors: Matsuda Miho , Sokol Sergei Y.
Published: January 2025

The process of folding the flat neuroectoderm into an elongated neural tube depends on tissue fluidity, a property that allows epithelial deformation while preserving tissue integrity. Neural tube folding also requires the planar cell polarity (PCP) pathway. Here, we report that Prickle2 (Pk2), a core PCP component, increases tissue fluidity by promoting the remodeling of apical junctions (AJs) in Xenopus embryos. This Pk2 activity is mediated by the unique evolutionarily conserved Ser/Thr-rich region (STR) in the carboxyterminal half of the protein. Mechanistically, the effects of Pk2 require Rac1 and are accompanied by increased dynamics of C-cadherin and tricellular junctions, the hotspots of AJ remodeling. Notably, Pk2 depletion leads to the accumulation of mediolaterally oriented cells in the neuroectoderm, whereas the overexpression of Pk2 or Pk1 containing the Pk2-derived STR promotes cell elongation along the anteroposterior axis. We propose that Pk2-dependent regulation of tissue fluidity contributes to anteroposterior tissue elongation in response to extrinsic cues.
No added sugar: CCDC134 stabilizes ER chaperone Gp96 for TLR biogenesis
Authors: Blumenthal Antje , Domínguez Cadena Leslie C.
Published: January 2025

Bernaleau et al. (https://doi.org/10.1084/jem.20240825) show that CCDC134 located in the ER is required for TLR biogenesis by controlling the N-glycosylation, folding, and stabilization of the ER chaperone Gp96.
Quantum dots array: an approach to multipixel devices
Authors: Martyniuk Oleh , Chaudhary Vivek , Rhanbouri Mohamed Amine , Laguta Oleksii , Tahsin Muhammad , Gaskill D Kurt , Fatimy Abdelouahad El , Neugebauer Petr
Published: January 2025

Graphene has been proven to be an excellent material for high-frequency electromagnetic radiation detection. Here, we are reporting the graphene quantum dots (GQDs) devices designed as multi-parallel arrays of the dots (200 nm in diameter) between the source and drain electrodes. These state-of-the-art devices provide a novel concept of tuning the total device area and impedance while maintaining superior performance. The GQDs devices have been fabricated on silicon oxide substrate and analyzed for their transport properties. The multi-parallel array of GQDs on SiO2/Si substrates has depicted the possibility of tuning the activation energy depending on the back gate bias and the number of parallelly arranged GQDs while keeping the temperature dependence of resistance higher than 75 MΩ K−1 and 5 GΩ K−1 (for 2-dots and 8-dots devices). The results presented here pave the way for further optimization and realization of chip-scale arrays of GQDs-based multipixel devices, enhancing the applications in imaging and magneto-optical spectroscopy.
Road preview method for active suspension based on reinforcement learning
Authors: Wang Guohong , Kou Farong , Liu Pengtao , Lv Wenhua , Xing Longlong
Published: January 2025

The pre-identification of impulse road surfaces, such as speed bumps, potholes, and manhole covers, can significantly enhance the performance of active suspension systems. However, existing current identification methods often fail to balance between low cost, high reliability, and precise speed. This study proposes an impulse road surface identification method based on a reinforcement learning (RL) network. First, a real dataset of impulse road surfaces was collected, with suspension dynamic responses serving as inputs and random road levels along with impulse road surface features as outputs. This data was used to develop a random forest extreme gradient boosting (RF-XGBoost) network to recognize road surface information from vehicle dynamics. Next, a semantic segmentation network was employed to segment road surfaces during intelligent vehicle travel, using road surface information identified by the random forest network as the reward function for RL. The RL policy was pre-trained using the actual collected data. To validate the effectiveness of the proposed control strategy, a simulation environment was constructed in Prescan, where speed bumps, potholes, and manhole covers of varying heights and sizes were randomly arranged. The RL-based road surface identification algorithm was implemented in Simulink, and a co-simulation was conducted with the CarSim vehicle model. The enhanced RF-XGBoost network effectively distinguishes between random and impulse road surfaces, achieving average recognition accuracies of 95.7% for random surfaces and 98.2% for impulse surfaces. During initial training iterations, the RL network exhibited lower accuracy; however, as training progressed, the accuracy for unfamiliar road surface features reached an average of 96.5%, and overall recognition accuracy improved by an average of 9%. The simulation results demonstrate that the proposed RL identification method effectively acquires information about the road ahead, shows robustness and generalization, and provides crucial disturbance data for subsequent active suspension control.
The regional ventilation distribution monitored by electrical impedance tomography during anesthesia induction with head-rotated mask ventilation
Authors: Xu Qing , Fang Yijiao , Pan Congxia , Gao Lingling , Zhu Yun , Zhang Jun , Zhao Zhanqi , Yang Li
Published: January 2025

Objective. Abnormal regional lung ventilation can lead to undesirable outcomes during the induction of anesthesia. Head rotated ventilation has proven to change the airflow of upper airway tract and be effective in increasing the tidal volume. This study aimed to investigate the influence of head rotated mask ventilation on regional ventilation distribution during the induction phase of anesthesia. Approach. Ninety patients undergoing anesthesia induction were randomly assigned to receive either neutral head (neutral-head group) or rotated right side head (rotated-head group) mask ventilation. Pressure-controlled mode was used in all mechanical ventilation. The regional lung ventilation was monitored by electrical impedance tomography. The primary outcome was the ratio of left/right lung ventilation distribution. The secondary outcomes were global inhomogeneity index (GI), center of ventilation (CoV, 100% = entirely dorsal), and the regional lung distribution differences between spontaneous and mask ventilation. Main results. Forty-two patients with neutral-head and 38 with rotated-head mask ventilation were analyzed finally. Compared with spontaneous ventilation, mask positive-pressure ventilation caused significant changes in the ratio of left/right lung ventilation distribution [0.85 (0.27) versus 0.94 (0.30); P = 0.022]. However, there were no differences in the ratio of left/right lung ventilation distribution between neutral and rotated head groups (P = 0.128). When compared with spontaneous ventilation, mask ventilation caused regional distributions of ventilation shifts towards ventral lung areas (CoV: 45.7 ± 5.0% versus 39.2 ± 4.8%; P < 0.001), and significant lung ventilation inhomogeneity (GI: 0.40 ± 0.07 versus 0.49 ± 0.14; P < 0.001). Compared with neutral-head mask ventilation, rotated-head mask ventilation was associated with higher expiratory tidal volume (TVe) (575.1 ± 148.6 ml versus 654.2 ± 204.0 ml; P = 0.049). Significance. Mask positive ventilation caused regional lung ventilation changes. When compared with neutral-head mask ventilation, rotated-head mask ventilation did not improve the regional ventilation towards to left lung. However, rotated-head mask ventilation was associated with higher TVe, and has the potential for better oxygenation.

Trial Registration. This study was registered on Chinese Clinical Trial Registry on 6 August, 2024 (ChiCTR2400087858).
A novel dual-inertia driven piezoelectric actuator for flexible mounting applications
Authors: Shao Yan , Xu Minglong , Liu Kaiyuan , Meng Min
Published: January 2025

Stepping piezoelectric actuators are widely recognized for their high power density, fine resolution, and extensive travel range. However, their dependence on rigid supports limits their applicability in flexible mounting scenarios, such as cable traction systems, where insufficient reaction forces can result in in-place oscillation and subsequent functional failure. To address this challenge, this study has proposed a novel dual-inertia driven piezoelectric actuator specifically designed for flexible mounting applications. The actuator comprises two primary components with large inertia, an innovative rhombus-shaped clamping mechanism enabling precise clamping force adjustment, and a compact Hall sensor for accurate displacement monitoring. A multi-body dynamic model has been developed to analyze the interaction between inertial forces and frictional transitions, which are critical for achieving precise stepwise elongation or contraction in flexible setups. Experimental evaluations have demonstrated the actuator’s superior performance, achieving a maximum load capacity of 5.57 N, a clamping friction of 11.2 N, a free-load speed of 10.53 mm s−1, and a stepping resolution of 0.55 μm. These findings have established the proposed actuator as a significant advancement in piezoelectric technology, offering a robust and adaptable solution for high-precision actuation in flexible mounting applications.
Presetting-time complete synchronization of two Lorenz systems with applications into nonlinear PMSMs and Hindmarsh-Rose neuron models
Authors: Ma Ru-Ru , Huang Zhixiang , Ma Zhicai
Published: January 2025

This paper begins by examining the presetting-time synchronization (PtS) of two nonlinear Lorenz systems and subsequently applies these findings to synchronize the permanent magnet synchronous motors (PMSMs) and Hindmarsh-Rose neuron models. Unlike conventional finite-time synchronization (FtS) or fixed-time synchronization (FxS) methods, the upper bound estimation of convergence time (UBECT) in this study can be predefined as a constant, unaffected by initial conditions or control parameters. Furthermore, the control schemes developed here are free from chattering, as they avoid using traditional discontinuous signum and absolute value functions. Through classical Lyapunov stability analysis, sufficient conditions are derived to ensure PtS between nonlinear Lorenz systems, PMSMs, and Hindmarsh-Rose neuron models. Lastly, numerical simulations are conducted to confirm the accuracy and efficiency of the theoretical findings, with comparisons and perturbation analyses also included.
Finite Time Hybrid Synchronization of Heterogeneous Duplex Complex Networks via Time-varying Intermittent Control
Authors: Xie Cheng-jun , Lu Xiang-qing
Published: January 2025

This paper study the finite time internal synchronization and the external synchronization (hybrid synchronization) for duplex heterogeneous complex networks by time-varying intermittent control. There few study hybrid synchronization of heterogeneous duplex complex networks. Therefore, we research the finite time hybrid synchronization of heterogeneous duplex networks, which employs the time-varying intermittent control to drive the duplex heterogeneous complex networks to achieve hybrid synchronization in finite time. To be specific, the switch frequency of the controllers can be changed with time by devise Lyapunov function and boundary function, the internal synchronization and external synchronization are achieved simultaneously in finite time. Finally, numerical examples are presented to illustrate the validness of theoretical results.
A novel approach to visual image encryption: 2D hyperchaos, variable Josephus, and 3D diffusion
Authors: Hong Yan , Duan Xinyan , Su Jingming , Wang Zhaopan , Fang Shihui
Published: January 2025

With the development of the Internet, image encryption technology has become critical for network security. Traditional methods often suffer from issues such as insufficient chaos, low randomness in key generation, and poor encryption efficiency. To enhance performance, this paper proposes a new encryption algorithm designed to optimize parallel processing and adapt to images of varying sizes and colors. The method begins by using SHA-384 to extract the hash value of the plaintext image, which is then processed to determine the chaotic system’s initial value and block size. The image is padded and divided into blocks for further processing. A novel two-dimensional infinite collapses hyperchaotic map (2D-ICHM) is employed to generate the intra-block scrambling sequence, while n improved variable Joseph traversal sequence is used for inter-block scrambling. After removing the padding, 3D forward and backward shift diffusions, controlled by the 2D-ICHM sequences, are applied to the scrambled image, producing the ciphertext. Simulation results demonstrate that the proposed algorithm outperforms others in terms of entropy, anti-noise resilience, correlation coefficient, robustness, and encryption efficiency.
Impact of trapping on tritium self-sufficiency and tritium inventories in fusion power plant fuel cycles
Authors: Meschini Samuele , Delaporte-Mathurin Rémi , Tynan George R. , Ferry Sara E.
Published: January 2025

The dynamic analysis of fusion power plant (FPP) fuel cycles highlights the challenge of achieving tritium self-sufficiency in future FPPs. While state-of-the-art fuel cycle models offer valuable insights into the necessary design parameters for attaining tritium self-sufficiency, none of these models currently consider the impact of tritium trapping within fuel cycle components. However, detailed analysis of individual components reveals that substantial amounts of tritium can be trapped within the first wall, divertors, and breeding blanket systems, suggesting that tritium trapping may significantly influence the FPP ability to achieve self-sufficiency. The compounded effects of additional tritium traps generated by irradiation effects and component replacements further exacerbate this challenge. The novelty of this work is the integration of an explicit, physics-based model for tritium trapping, evolution of damage-induced traps, and component replacements into a dynamic, system-level model of a fuel cycle. The results show an increase of a factor

10
3

−

10
4

of tritium inventory in the first wall and vacuum vessel of an ARC-class FPP when accounting for the aforementioned phenomena. This, coupled with the replacement of components subject to significant tritium trapping, slows down fuel cycle dynamics, resulting in an extended tritium doubling time (50% increase), higher start-up inventory (30% increase), and higher required tritium breeding ratio (2%–5%) compared to a scenario without tritium trapping.
Evaluation and optimization of physical, mechanical, and biological characteristics of 3D printed Whitlockite/calcium silicate composite scaffold for bone tissue regeneration using response surface methodology
Authors: Thangavel Mahendran , Elsen S Renold
Published: January 2025

Calcium phosphate-based bioscaffolds are used for bone tissue regeneration because of their physical and chemical resemblance to human bone. Calcium, phosphate, sodium, potassium, magnesium, and silicon are important components of human bone. The successful biomimicking of human bone characteristics involves incorporating all the human bone elements into the scaffold material. In this work, Mg-Whitlockite (WH) and Calcium Silicate (CS) were selected as matrix and reinforcement respectively, because of their desirable elemental composition and regenerative properties. The magnesium in WH increases mineralization in bone, and the silicon ions in CS support vascularization. The Mg-WH was synthesized using the wet chemical method, and powder characterization tests were performed. Response surface methodology (RSM) is used to design the experiments with a combination of material compositions, infill ratios (IFs), and sintering temperatures (STs). The WH/CS bioceramic composite is 3D printed in three different compositions: 100/0, 75/25, and 50/50 wt%, with IFs of 50%, 75%, and 100%. The physical and mechanical characterization study of printed samples is conducted and the result is optimized using RSM. ANOVA (Analysis of Variance) is used to establish the relationship between input parameters and responses. The optimized input parameters were the WH/CS composition of 50/50 wt%, IF of 50%, and ST of 1150 °C, which bring out the best possible combination of physical and mechanical characteristics. The RSM optimized response was a density of 2.27 g cm−3, porosity of 36.74%, wettability of 45.79%, shrinkage of 25.13%, compressive strength of 12 MPa, and compressive modulus of 208.49 MPa with 92% desirability. The biological characterization studies were conducted for the scaffold samples prepared with optimized input parameters. The biological studies confirmed the capabilities of the WH/CS composite scaffolds in bone regenerative applications.
Climate change risk trap: low-carbon spatial restructuring and disaster risk in petroleum-based economies
Authors: Rözer Viktor , Mehryar Sara , Alsahli Mohammad M M
Published: January 2025

The economic risks from climate change can be separated into two categories: physical risks from increased frequency and magnitude of extreme weather and climate events, and transition risks due to rapid decarbonisation leading to stranded assets and shifts in production and the labour market. On the global level, the two risks are widely recognized as trade-offs by the academic and policy literature: rapid decarbonisation increases transition risks while reducing physical risks, and vice versa for a delayed reduction of greenhouse gas emissions. In contrast, little is known about the interaction between the two risks on smaller geographical scales. This paper investigates the interactions between physical and transition risks on the sub-national level for petroleum-based economies. Their strong dependency on the export of fossil fuels requires a more far-reaching economic restructuring to meet both local and global emission targets than most other economies, exposing them to high transition risks. At the same time, the profound economic changes resulting from a low-carbon transition lead to a spatial redistribution of assets and labour, when brown assets and jobs get stranded and new green assets and jobs are created elsewhere. Building on the literature on spatial economic restructuring and climate disaster risk, we show that, unlike the common conceptualisation as a trade-off, physical and transition risk can increase simultaneously on the sub-national level. We call this dynamic the climate change risk trap. The paper provides an empirical illustration of this trap using the example of flash flood risk in Kuwait, a wealthy petroleum-based economy in the Gulf region. It shows how decisions on urban planning and low-carbon economic restructuring have increased flash flood risk. The analysis highlights the importance of considering climate disaster risk and environmental impact assessments in low-carbon transition planning to avoid falling into the climate change risk trap.
Have crops already reached peak suitability: assessing global climatic suitability decreases for crop cultivation
Authors: Mombo Vhiny-Guilley , Duvallet Mathilde , Schaeffer Michiel , Baarsch Florent
Published: January 2025

Crop yield and the availability of arable land are impacted by climate change, leading to effects on global patterns of production and trading. To gain more precise insights in how future climate change might lead to redistributing productive crop areas, we developed a new method to assess climatic crop suitability, which combines temperature and precipitation suitability through water balance calculations. We applied the method to evaluate the effects of climate change under two climatic scenarios (SSP2-4.5 and SSP5-8.5), using an ensemble of five general circulation models, for nine crops (Arabica coffee, cassava, common beans, common wheat, maize, plantain, rice, sorghum and sugarcane) for four periods of time: past (1995–2014), present day (2015–2034), medium term (2040–2059), long term (2080–2099). We observed that the fraction of area with optimal suitability might be on a downward trajectory for coffee, cassava, beans, wheat and plantain, and could be halved by the end of the century. The tropics and sub-tropics are negatively affected for all crops, while mid-latitudes see large decreases in suitability for beans, wheat and maize. Global patterns show that suitability decreases at local levels (in about 30% of the global area for bean and wheat) are not compensated by increases in suitability elsewhere (in about 19% of the area for bean and wheat). As relocation and expansion of production areas are constrained by available arable land, other strategies might be considered to improve suitability, such as irrigation, which would increase the area of optimal suitability from 5%–25% to 40%–50% of total arable land for the nine crops. Drainage could improve the optimal suitability area fivefold for maize and sorghum, while shading increases suitability for coffee (by up to 20% in both cases). The increased risk of food supply shortages led by climatic suitability loss may trigger increased deforestation if adaptation measures are not implemented.
Advancements and opportunities to improve bottom–up estimates of global wetland methane emissions
Authors: Zhu Qing , Jacob Daniel J , Yuan Kunxiaojia , Li Fa , Runkle Benjamin R K , Chen Min , Bloom A Anthony , Poulter Benjamin , East James D , Riley William J , McNicol Gavin , Worden John , Frankenberg Christian , Halabisky Meghan
Published: January 2025

Wetlands are the single largest natural source of atmospheric methane (CH4), contributing approximately 30% of total surface CH4 emissions, and they have been identified as the largest source of uncertainty in the global CH4 budget based on the most recent Global Carbon Project CH4 report. High uncertainties in the bottom–up estimates of wetland CH4 emissions pose significant challenges for accurately understanding their spatiotemporal variations, and for the scientific community to monitor wetland CH4 emissions from space. In fact, there are large disagreements between bottom–up estimates versus top–down estimates inferred from inversion of atmospheric CH4 concentrations. To address these critical gaps, we review recent development, validation, and applications of bottom–up estimates of global wetland CH4 emissions, as well as how they are used in top–down inversions. These bottom–up estimates, using (1) empirical biogeochemical modeling (e.g. WetCHARTs: 125–208 TgCH4 yr−1); (2) process-based biogeochemical modeling (e.g. WETCHIMP: 190 ± 39 TgCH4 yr−1); and (3) data-driven machine learning approach (e.g. UpCH4: 146 ± 43 TgCH4 yr−1). Bottom–up estimates are subject to significant uncertainties (∼80 Tg CH4 yr−1), and the ranges of different estimates do not overlap, further amplifying the overall uncertainty when combining multiple data products. These substantial uncertainties highlight gaps in our understanding of wetland CH4 biogeochemistry and wetland inundation dynamics. Major tropical and arctic wetland complexes are regional hotspots of CH4 emissions. However, the scarcity of satellite data over the tropics and northern high latitudes offer limited information for top–down inversions to improve bottom–up estimates. Recent advances in surface measurements of CH4 fluxes (e.g. FLUXNET-CH4) across a wide range of ecosystems including bogs, fens, marshes, and forest swamps provide an unprecedented opportunity to improve existing bottom–up estimates of wetland CH4 estimates. We suggest that continuous long-term surface measurements at representative wetlands, high fidelity wetland mapping, combined with an appropriate modeling framework, will be needed to significantly improve global estimates of wetland CH4 emissions. There is also a pressing unmet need for fine-resolution and high-precision satellite CH4 observations directed at wetlands.
Improved bounds on quantum uncommon information
Authors: Lee Yonghae , Bae Joonwoo , Yamasaki Hayata , Lee Soojoon
Published: January 2025

In classical information theory, channel capacity quantifies the maximum number of messages that can be reliably transmitted using shared information. An equivalent concept, termed uncommon information, represents the number of messages required to be exchanged to completely share all information in common. However, this equivalence does not extend to quantum information theory. Specifically, quantum uncommon information (QUI) is operationally defined as the minimal amount of entanglement required for the quantum communication task of quantum state exchange (QSE), where two parties exchange quantum states to share all quantum messages in common. Currently, an analytical closed-form expression for the QUI remains undetermined. In this work, by investigating underlying characterization of the QUI, we derive improved bounds on it. To obtain these bounds, we develop a subspace exchange strategy that leverages a common subspace of two parties to identify the unnecessary qubits for exchange. We also consider a referee-assisted exchange, wherein a referee aids two parties in efficiently performing the QSE. Our bounds provide more precise estimations for the QUI. Furthermore, we demonstrate that the subspace technique is a versatile tool for characterizing uncommon information not only in the bipartite scenario but also in various multi-partite ones.
Coupled modelling and analysis of lubrication-wear evolution of textured piston/cylinder pair in high-pressure common rail pumps
Authors: Zhan Menghao , Huang Dan , Yan Kanghao , Zhou Guangde
Published: January 2025

Surface texturing is an important approach to enhance fluid lubrication performance and reduce friction and wear. Research on the surface texturing of the piston/cylinder pair considering various characteristics such as multi-physical fields and the evolution of friction and wear is still insufficient. The novelty of this work aims to establish a coupled numerical simulation model considering the coupling effect of multiple physical fields, wear of the cylinder bore and surface texture, and determine the effective surface texture parameters to improve the friction performance of the mechanical components of high-pressure common rail pump. The influence of surface texture on friction and wear characteristics and the evolution of lubrication-wear under different geometric cases were in-depth investigated, and the action mechanism of surface texture on lubrication and wear was revealed. Through numerical analysis, optimal parameters were identified that significantly reduce the friction coefficient and wear amount, offering practical insights for mitigating friction and wear in mechanical systems.
Fatigue life study of milled surfaces based on stress concentration factor
Authors: Zhang Wei , Zhu Zhimin , Zheng Minli , Su Peibin
Published: January 2025

This paper adopts the method of combining theoretical modeling, experimental detection analysis and finite element simulation. The improved stress concentration factor solution equation is derived, and the fatigue life prediction model of plane milling surface is established accordingly. The fatigue life simulation analysis method based on surface stress concentration factor is used to obtain the influence law of surface morphology of typical parts on fatigue life, verify the accuracy of fatigue life prediction model, and provide an effective means for the analysis and prediction of fatigue performance of milling surface.
Production and testing of Al-12%Si composites strengthened with ZrO2 using an innovative disintegrated melt deposition manufacturing technique
Authors: Nataraja M , Balakumar G , Santhosh N , Rudra Naik M
Published: January 2025

This study aims to produce Al 12% Si-ZrO2 composites using the Disintegrated Melt Deposition (DMD) technique and assess their microstructure and mechanical properties. The Al-12%Si alloy is recognized for its strength and corrosion resistance, making it valuable in industries such as shipbuilding and aviation. ZrO2, a ceramic known for its corrosion resistance and hardness, enhances the strength and hardness of the composites. It also reduces elongation percentage and promotes lubrication between silicon and aluminum in the matrix alloy. Specimens with varying ZrO2 wt% (AS, AS0.5Z, AS1Z, AS1.5Z, AS2Z, AS2.5Z, AS3Z) were fabricated from DMD process. Results indicated that hardness increased from 59.7 HB (as cast) to 75.2 HB (2.5 wt% ZrO2), with a slight decrease at 3 wt% ZrO2. Elongation percentage decreased from 12.3% to 8.5%, ultimate tensile strength ranged from 239.2 MPa to 281.9 MPa, ultimate compression strength from 313.7 MPa to 375.6 MPa, and impact energy absorbed increased from 3.6 J to 5.3 J. These findings suggest potential applications of aluminum-12% Si-ZrO2 composites in various applications by improving their properties.
Dynamical structure factors of warm dense matter from time-dependent orbital-free and mixed-stochastic-deterministic density functional theory
Authors: White Alexander J
Published: January 2025

We present the first calculations of the inelastic part of the dynamical structure factor (DSF) for warm dense matter (WDM) using time-dependent orbital-free density functional theory (TD-OF-DFT) and mixed-stochastic-deterministic (mixed) Kohn Sham TD-DFT (KS TD-DFT). WDM is an intermediate phase of matter found in planetary cores and laser-driven experiments, where the accurate calculation of the DSF is critical for interpreting x-ray Thomson scattering measurements. Traditional TD-DFT methods, while highly accurate, are computationally expensive, motivating the exploration of TD-OF-DFT and mixed TD-KS-DFT as more efficient alternatives. We applied these methods to experimentally measured WDM systems, including solid-density aluminum and beryllium, compressed beryllium, and carbon–hydrogen mixtures. Our results show that TD-OF-DFT requires a dynamical kinetic energy potential in order to qualitatively capture the plasmon response. Additionally, it struggles with capturing bound electron contributions. In contrast, mixed TD-KS-DFT offers greater accuracy in distinguishing bound and free electron effects, aligning well with experimental data, though at a higher computational cost. This study highlights the trade-offs between computational efficiency and accuracy, demonstrating that TD-OF-DFT remains a valuable tool for rapid scans of parameter space, while mixed TD-KS-DFT should be preferred for high-fidelity simulations. Our findings provide insight into the future development of DFT methods for WDM and suggest potential improvements for TD-OF-DFT.
Outlier detection of monitored data and unsupervised recognition of construction activities during seismic performance enhancement of historic stone monuments
Authors: Xue Songtao , Shi Qinhao , Xie Liyu , Zhou Shuning , Lu Wensheng , Zhang Mansheng
Published: January 2025

To enhance the seismic resilience of historical and cultural heritage sites, protective measures were implemented through the installation of advanced heritage protection platform facilities. A structural health monitoring system was developed to safeguard historical relics during construction activities by continuously monitoring the overall condition of the relics and the integrity of critical components. Key parameters, such as settlement differences, tilt, crack width, and acceleration, were meticulously tracked, with predefined warning and alarm thresholds established. Alerts were triggered whenever these parameters exceeded their respective thresholds, ensuring timely interventions. To ensure the reliability and consistency of the collected data, this study proposes an evaluation method that integrates multi-source data fusion with statistical analysis techniques. Building on this foundation, an unsupervised algorithm was employed to identify construction activities impacting the structural health of the relics. The results demonstrate the effectiveness of combining multi-source data and intelligent algorithms for reliable monitoring and early detection of risks during conservation. The developed system offers automated, real-time assessments and can serve as a model for future heritage protection projects. Looking forward, integrating wireless sensors and diverse data sources could improve system accuracy, efficiency, and cost-effectiveness, further enhancing the protection of cultural heritage.
Application of improved multi-population genetic algorithm in structural optimization of automotive electrical equipment
Authors: Zhang Jia
Published: January 2025

The structure of automotive electrical equipment is becoming increasingly complex. How to optimize the structure without affecting the performance of the car itself to reduce the weight and manufacturing cost of electrical equipment has become particularly important. Based on this, this study introduces diversity preservation mechanism and adaptive mutation strategy to improve the multi-population genetic algorithm, and proposes the objective function and constraint conditions for the results of automotive electrical equipment, constructing an optimization model for the structure of automotive electrical equipment. The results showed that at 500 iterations, the improved multi-population genetic algorithm had optimal and average fitness values of 0.96 and 0.94, respectively, demonstrating higher accuracy and search capability compared to other algorithms. After using optimization models for different automotive electrical equipment structures, the average energy consumption decreased by 18%, the total cost decreased by 16.55%, and the average total weight of electrical equipment structures decreased by 16.475%. This model is effective in optimizing the structure of electrical equipment. This study contributes to improving the performance and design efficiency of automotive electrical equipment, and has significant implications for promoting the application of intelligent optimization technology in the automotive industry.