bluuebunny/crossref_metadata_2025 huggingface dataset:
Present understanding of ignition and gain using indirect-drive inertial confinement fusion target designs on the U.S. National Ignition Facility
Authors: Hurricane O A , Allen A , Bachmann B L , Baker K L , Baxamusa S , Bhandarkar S D , Biener J , Bionta S R M , Braun T , Briggs T , Brunton G , Casey D T , Chapman T , Choate C , Clark D S , Dewald E , DiNicola J-M , Divol L , Do A , Fehrenbach T , Fittinghoff D N , Gatu Johnson M , Geppert Kleinrath H , Geppert Kleinrath V , Haan S , Hilsabeck T J , Hinkel D E , Hohenberger M , Humbird K D , Izumi N , Kong C , Kritcher A L , Landen O L , Lindl J , MacGowan B J , Mackinnon A J , Maclaren S A , Marinak M , Meeuwsen R , Michel P , Milovich J , Meaney K , Millot M , Moody J D , Moore A S , Nikroo A , Nora R , Pak A , Ralph J E , Ratledge M , Ross J S , Rubery M S , Schlossberg D J , Schmit P F , Sepke S M , Smalyuk V , Spears B K , Springer P T , Stadermann M , Strozzi D J , Suratwala T I , Tommasini R , Town R P J , Weber C R , Wild C , Van Wonterghem B , Woodworth B , Wu J , Young C V , Zylstra A B
Published: December 2024

For many decades, the running joke in fusion research has been that ‘fusion’ is thirty years away and always will be. Yet, these past few years we find ourselves in a position where we can now talk about the milestones of burning plasmas, fusion ignition, and target energy gain greater than unity (scientific breakeven) in the past tense. Fusion is no longer a joke! Yet getting to fusion ignition, the tipping-point of thermonuclear instability resulting in an explosive increase in ion thermal temperature and fusion reaction-rate, and scientific breakeven (target gain,

G

target

=

fusion yield/deposited laser energy

>

1

, in the laser-driven inertial confinement fusion context) has not been easy. In this publication we discuss our present understanding of the physics and technological challenges surrounding ignition and Gain as well as highlight some outstanding problems that still need resolution.
Fabrication, thermal, mechanical, and piezoelectric characterization of PLA/BT piezocomposites
Authors: Puszczykowska Natalia , Rytlewski Piotr , Mirkowska Agnieszka , Augustyn Piotr , Fiedurek Kacper
Published: December 2024

The properties of polylactide (PLA) composites containing up to 40 vol% of barium titanate (BT) powder were investigated. PLA/BT composites were fabricated using twin-screw extrusion, which ensured uniform filler dispersion. The results demonstrated that increasing the BT content in PLA improved the thermal stability, stiffness, and degree of crystallinity of the composite. The piezoelectric coefficient d
33 also increased with higher BT content and longer polarization times, reaching a maximum value of 35 pC N−1 for composites containing 40 vol% BT. Additionally, the studies revealed that the d
33 coefficient is pressure dependent. Presented PLA/BT piezocomposites highlight the suitability of these materials for applications that require both biocompatibility and piezoelectric functionality, including regenerative medicine, energy harvesting, soft robotics, and electroactive biomedical devices.
Stiffness modulation in a 3-DoF pneumatic soft actuator for single-port transvesical prostatectomies
Authors: Lu Yuxi , Zhou Zhongchao , Igarashi Tatsuo , Tortos Vinocour Pablo Enrique , Gomez Tames Jose , Yu Wenwei
Published: December 2024

Soft actuators have demonstrated potential in minimally invasive surgery (MIS), requiring multiple degrees of freedom and stiffness modulation facilitated by pneumatic antagonistic chambers. However, the hollow central passage in these actuators for single-port surgery complicates the internal stress distribution during the inflation of multiple chambers, making stiffness modulation mechanisms difficult to understand. In this study, a finite element analysis model is developed to explore the combined effect of the internal stress distribution and duct structure on the stiffness modulation in soft actuators equipped with multiple pneumatic antagonistic chambers. A prototype is developed to cross-validate the simulation and examine the effects of various antagonistic chambers on the stiffness modulation. The findings confirm that inflating specific chambers alters the internal stress distribution of the actuator by creating bending moments that influence deformation responses to external loads. These moments impact the stiffness and structure of the hollow central duct by modifying its geometrical moment of inertia and affecting the lengths of the tensile and compressive regions during bending, further influencing the stiffness. The effects of bending moments and the geometrical moment of inertia on stiffness modulation vary across different actuator sections owing to the varying lengths of the tensile and compressive regions during bending. These stiffness modulations affect the tip bending, force, and response time. The study findings provide insights into the mechanism of stiffness modulation for the design of soft actuators for complex MIS.
A modular entanglement-based quantum computer architecture
Authors: Riera-Sàbat Ferran , Dür Wolfgang
Published: December 2024

We propose a modular quantum computation architecture based on utilizing multipartite entanglement. Each module consists of a small-scale quantum computer comprising data, memory and entangling qubits. Entangling qubits are used to selectively couple different modules by harnessing some non-controllable, distance-dependent interaction, which is effectively controlled and enhanced via a proper adjusting of the internal state of the qubits. In this way, multipartite entangled states with different entanglement topologies can be shared between modules. These states are stored in memory qubits where they can be further processed so they can eventually be used to deterministically perform certain classes of gates or circuits between modules on demand, including parallel controlled-Z gates with arbitrary interaction patterns, multi-qubit gates or whole Clifford circuits, depending on their entanglement structure. The usage of different kinds of multipartite entanglement rather than Bell pairs allows for more efficient and flexible coupling between modules, leading to a scalable quantum computation architecture.
Novel approach by shifted Schröder polynomials for solving the fractional Bagley-Torvik equation
Authors: Yassin N M , Aly Emad H , Atta A G
Published: December 2024

This work is dedicated to proposing a spectral tau solution for the fractional Bagley-Torvik equation (FBTE). The suggested solution is stated as a sum of basis functions, which are selected to be the Schr

o

̈

der polynomials (SPs). By applying the proposed spectral tau approach, we derive a system of linear equations, and we solve it approximately by applying the Gauss elimination method. The error analysis is analyzed in detail. Additionally, numerical comparisons with other methods found in the literature are conducted. The numerical results validate the suggested method's accuracy, computational efficiency, and ease of use.
Electric current through atoms arranged in concentric circles induced by applying static magnetic field
Authors: Inui Norio , Shiga Yuta
Published: December 2024

The induction of electric current between atoms arranged in concentric circles by an external magnetic field is studied using a tight-binding model. In particular, the dependence of electric current on the strength of the magnetic field, number of atoms, and temperature is examined. Substantial changes are observed in the electric current distribution when the difference in the transfer integral along the circumference and between circles is increased. Additionally, the difference in the electric current flow compared with that through a graphene ring is analyzed.
Parametric continuation analysis of heat and mass transfer of Ethylene Glycol nanofluid flow between two vertical plates
Authors: Ahmad Adeel , Shuaib Muhammad , Rehman Hijab ur
Published: December 2024

This study examines the behavior of nanofluid with three nano-particles namely ZnO
2, TiO
2 and graphene with base fluid as Ethylene glycol trapped between two vertical plates, with particular attention to the temperature-dependent electrical and magnetic conductivity are affected by the Soret and Dufour effects. The governing equations for fluid flow are transformed into dimensionless ordinary differential equations using the Adeosun and Ukaegbu method. The Parametric Continuation Method (PCM) is then employed to analyze the numerical results. The numerical results obtained using the (PCM) method are graphically validated against the solutions provided by the bvp4c package, showing excellent agreement between them. Additionally, numerical results of the (PCM) method are also compared with previously published studies and about two decimal places accuracy is reported. It is found that ZnO
2 is more effective in enhancing the nanofluids temperature. The temperature of fluid usning ZnO
2, TiO
2 and graphene is 1.2985, 0.6932 and 0.4834 respectively. While graphene has minor contribution in upsurging temperature of fluid. So ZnO
2 can be used in various mechanical and electrical appliances to upsurge its temperature according to our needs. Graphene plays major role in enhancing fluids concentration and ZnO
2 has less effect on concentration of nanofluid. Using graphene the concentration of fluid is 1.6834, while using ZnO
2 its concentration is 1.2985.
A novel asymmetric encryption framework based on a 2D hyperchaotic map and enhanced S-box for secure medical image transmission
Authors: Tang Jianeng , Lu Mingsheng , Zhang Zezong
Published: December 2024

Recently, the advent of Internet of Medical Things (IoMT) has effectively alleviated the problem of difficulty in accessing medical services. However, during telemedicine, various medical images containing sensitive private information are exposed in communication channels. Therefore, there is an immediate need for an effective encryption method to ensure the secure transmission of medical images. In this paper, an image encryption algorithm is proposed based on a new chaotic model and an enhanced S-box. Furthermore, the proposed encryption algorithm is applied within a novel asymmetric image encryption framework. Firstly, to address the problems of narrow chaotic intervals and uneven trajectory distribution present in some existing chaotic maps, a two-dimensional cross-sine-modular model (2D-CSMM) is constructed. Secondly, in conjunction with the DNA algorithm, an enhanced S-box is proposed. Finally, in order to effectively protect key transmission as well as to enhance the system's resistance against chosen plaintext attacks, a novel asymmetric image encryption framework is designed by integrating the Elliptic Curve Diffie-Hellman (ECDH), Elliptic Curve Cryptography (ECC) and SHA-256 functions. And the secret key is computed from the cipher key, the shared key, and the native key associated with the plain image. Comprehensive experimental results demonstrate the high efficiency and the resilience of this new algorithm against common attacks.
Coherence and imaginarity of quantum states
Authors: Xu Jianwei
Published: December 2024

Baumgratz, Cramer and Plenio established a rigorous framework (BCP framework) for quantifying the coherence of quantum states (2014, Phys. Rev. Lett.
113, 140401). In BCP framework, a quantum state is called incoherent if it is diagonal in the fixed orthonormal basis, and a coherence measure should satisfy some conditions. For a fixed orthonormal basis, if a quantum state ρ has nonzero imaginary part, then ρ must be coherent. How to quantitatively characterize this fact? In this work, we show that any coherence measure C in BCP framework has the property C(ρ) − C(Reρ)≥0 if C is invariant under state complex conjugation, i.e. C(ρ) = C(ρ*), here ρ*is the conjugate of ρ, Reρis the real part of ρ. If C does not satisfy C(ρ) = C(ρ*), we can define a new coherence measure

C

′

(
ρ
)
=

1

2

[
C
(
ρ
)
+
C
(

ρ

*

)
]

such that

C

′

(
ρ
)
=

C

′

(
ρ
*
)
.

We also establish some similar results for bosonic Gaussian states.
Quantum sensitivity of a photon-added molecular wave packet
Authors: Das Jayashree , Ghosh Suranjana , Roy Utpal
Published: December 2024

We study the temporal dynamics of a photon-added SU(2) coherent state, involving vibrational bound states of an iodine molecule. The nonclassicality of Schrödinger cat-like and compass-like photon-added states of this anharmonic potential is explored through the Mandel Q parameter and the negative region in their phase spaces. The Wigner phase space distribution is thoroughly studied for the photon-added molecular state and displayed for cat- and compass-like states. Generation and control of the sub-Planck interference structures become intriguing with photon addition. We ensure that the photon addition helps to improve the quantum sensitivity for a diatomic molecular system by comparing it between photon-added and photon-subtracted states. The detailed study of quantum sensitivity reveals that one can use a photon-added molecular wave packet as a probe to attain sensitivity to displacement that greatly exceeds the standard quantum limit. We also report that the nature of variation of the quantum sensitivity becomes qualitatively commensurate with that of the Wigner-negativity.
Characterization of nonlinear spectral linewidth and light shift in diffuse laser-cooled atoms
Authors: Yin 殷 Yiran 怡然 , Xu 许 An-Ning 安宁 , Peng 彭 Jin 瑾 , Liu 刘 Bei 贝
Published: December 2024

We demonstrate an integrating sphere to cool 87Rb atoms and measure the recoil-induced resonance and electromagnetically induced absorption spectrum. We measure the relationship between their linewidth and light shift with variation of the detuning and power of the cooling laser and study the performance of the diffuse laser cooling mechanism by the absorption linewidth radio Δν
E/Δν
R and light shift |Δ
R–Δ
E| using nonlinear spectroscopy. Specifically, when Δν
E/Δν
R reaches a value of 1.57, the temperature and number of cold atoms achieve the optimal cooling effect. This characterization of absorption linewidth and light shift will provide a method to estimate whether diffuse light cooling achieves the best cooling effect, contributing to the future development of isotropic laser cooling for application in quantum sensing.
Relativistic hyperpolarizabilities of atomic H, Li, and Be+ systems
Authors: Lu 卢 Shan-Shan 闪闪 , Zheng 郑 Hong-Yuan 弘远 , Yan 严 Zong-Chao 宗朝 , Babb James F. , Tang 唐 Li-Yan 丽艳
Published: December 2024

For atoms in external electric fields, the hyperpolarizabilities are the coefficients describing the nonlinear interactions contributing to the induced energies at the fourth power of the applied electric fields. Accurate evaluations of these coefficients for various systems are crucial for improving precision in advanced atom-based optical lattice clocks and for estimating field-induced effects in atoms for quantum information applications. However, there is a notable scarcity of research on atomic hyperpolarizabilities, especially in the relativistic realm. Our work addresses this gap by establishing a novel set of alternative formulas for the hyperpolarizability based on the fourth-order perturbation theory. These formulas offer a more reasonable regrouping of scalar and tensor components compared to previous formulas, thereby enhancing their correctness and applicability. To validate our formulas, we perform the calculations for the ground and low-lying excited pure states of few-electron atoms H, Li, and Be+. The highly accurate results obtained for the H atom could serve as benchmarks for further development of other theoretical methods.
Model-agnostic meta-learning for EEG-based inter-subject emotion recognition
Authors: Chen Cheng , Fang Hao , Yang Yuxiao , Zhou Yi
Published: December 2024

Objective. Developing an efficient and generalizable method for inter-subject emotion recognition from neural signals is an emerging and challenging problem in affective computing. In particular, human subjects usually have heterogeneous neural signal characteristics and variable emotional activities that challenge the existing recognition algorithms from achieving high inter-subject emotion recognition accuracy. Approach. In this work, we propose a model-agnostic meta-learning algorithm to learn an adaptable and generalizable electroencephalogram-based emotion decoder at the subject’s population level. Different from many prior end-to-end emotion recognition algorithms, our learning algorithms include a pre-training step and an adaptation step. Specifically, our meta-decoder first learns on diverse known subjects and then further adapts it to unknown subjects with one-shot adaptation. More importantly, our algorithm is compatible with a variety of mainstream machine learning decoders for emotion recognition. Main results. We evaluate the adapted decoders obtained by our proposed algorithm on three Emotion-EEG datasets: SEED, DEAP, and DREAMER. Our comprehensive experimental results show that the adapted meta-emotion decoder achieves state-of-the-art inter-subject emotion recognition accuracy and outperforms the classical supervised learning baseline across different decoder architectures. Significance. Our results hold promise to incorporate the proposed meta-learning emotion recognition algorithm to effectively improve the inter-subject generalizability in designing future affective brain–computer interfaces.
The ‘Sandwich’ meta-framework for architecture agnostic deep privacy-preserving transfer learning for non-invasive brainwave decoding
Authors: Wei Xiaoxi , Narayan Jyotindra , Faisal A Aldo
Published: December 2024

Objective. Machine learning has enhanced the performance of decoding signals indicating human behaviour. Electroencephalography (EEG) brainwave decoding, as an exemplar indicating neural activity and human thoughts non-invasively, has been helpful in neural activity analysis and aiding paralysed patients via brain-computer interfaces. However, training machine learning algorithms on EEG encounters two primary challenges: variability across data sets and privacy concerns using data from individuals and data centres. Our objective is to address these challenges by integrating transfer learning for data variability and federated learning for data privacy into a unified approach. Approach. We introduce the ‘Sandwich’ as a novel deep privacy-preserving meta-framework combining transfer learning and federated learning. The ‘Sandwich’ framework comprises three components: federated networks (first layers) that handle data set differences at the input level, a shared network (middle layer) learning common rules and applying transfer learning techniques, and individual classifiers (final layers) for specific brain tasks of each data set. This structure enables the central network (central server) to benefit from multiple data sets, while local branches (local servers) maintain data and label privacy. Main results. We evaluated the ‘Sandwich’ meta-architecture in various configurations using the BEETL motor imagery challenge, a benchmark for heterogeneous EEG data sets. Compared with baseline models like Shallow ConvNet and EEGInception, our ‘Sandwich’ implementations showed superior performance. The best-performing model, the Inception SanDwich with deep set alignment (Inception-SD-Deepset), exceeded baseline methods by 9%. Significance. The ‘Sandwich’ framework demonstrates advancements in federated deep transfer learning for diverse tasks and data sets. It outperforms conventional deep learning methods, showcasing the potential for effective use of larger, heterogeneous data sets with enhanced privacy. In addition, through its diverse implementations with various backbone architectures and transfer learning approaches, the ‘Sandwich’ framework shows the potential as a model-agnostic meta-framework for decoding time series data like EEG, suggesting a direction towards large-scale brainwave decoding by combining deep transfer learning with privacy-preserving federated learning.
Stimulation artefact removal: review and evaluation of applications in evoked responses
Authors: Zhang Tianshu , Lawson Kiaran , Lee Wee-Lih , Petoe Matthew , Moorhead Ashton , Bulluss Kristian , Thevathasan Wesley , McDermott Hugh , Perera Thushara
Published: December 2024

Objective. This study investigated software methods for removing stimulation artefacts in recordings undertaken during deep brain stimulation (DBS). We aimed to evaluate artefact attenuation using sample recordings of evoked resonant neural activity (ERNA), as well as a synthetic ground-truth waveform that emulated observed ERNA characteristics. Approach. The synthetic waveform and eight raw DBS recordings were processed by fourteen algorithms spanning the following categories: signal modification, signal decomposition, and template subtraction. For the synthetic waveform, performance was quantified by comparing each reconstructed signal against the ground-truth waveform. For DBS recordings, performance was contrasted amongst each other. The stimulation artefact was quantified by its amplitude and subsequent decay to baseline by the time to first zero-crossing. Each reconstructed ERNA signal was characterised by peak-to-peak-amplitude, root-mean-square amplitude, latency, and number of zero-crossings. Main results. None of the methods performed overall as well as the Backward Filter. Signal decomposition techniques were able to attenuate stimulation artefact albeit with unacceptable ERNA distortion. Significance. Upon evaluation of common software methods for DBS artefact attenuation, we advocate the use of the Backward Filter for reducing such artefacts while reconstructing ERNA.
EKFNet: edge-based Kalman filter network for real-time EEG signal denoising
Authors: Yan Jiaquan , He Zhuoli , Ur Rehman Junejo Naveed , Li Zuoyong , Grau Antoni , Huang Jiayan , Wang Chuansheng
Published: December 2024

Objective. Signal denoising methods based on deep learning have been extensively adopted on electroencephalogram devices. However, they are unable to deploy on edge-based portable or wearable (P/W) electronics due to the high computational complexity of the existed models. To overcome such issue, we propose an edge-based lightweight Kalman filter network (EKFNet) that does not require manual prior knowledge estimation. Approach. Specifically, we construct a multi-scale feature fusion module to capture multi-scale feature information and implicitly compute the prior knowledge. Meanwhile, we design an adaptive gain estimation module that incorporates long short-term memory and sequential channel attention module to dynamically predict the Kalman gain. Furthermore, we present an optimization strategy utilizing operator fusion and constant folding to reduce the model’s computational overhead and memory footprint. Main results. Experimental results show that the EKFNet reduces the sum of the square of the distances by at least 12% and improves the cosine similarity by at least 2.2% over the state-of-the-art methods. Besides, the model optimization shortens the inference time by approximately 3.3×. The code of our EKFNet is available at https://github.com/cathnat/EKFNet. Significance. By integrating Kalman filter with deep learning, the approach addresses the parameter-setting challenges in traditional algorithms while reducing computational overhead and memory consumption, which exhibits a good tradeoff between algorithm performance and computing power.
Nanoparticle targeting strategies for traumatic brain injury
Authors: Flores-Prieto David E , Stabenfeldt Sarah E
Published: December 2024

Nanoparticle (NP)-based drug delivery systems hold immense potential for targeted therapy and diagnosis of neurological disorders, overcoming the limitations of conventional treatment modalities. This review explores the design considerations and functionalization strategies of NPs for precise targeting of the brain and central nervous system. This review discusses the challenges associated with drug delivery to the brain, including the blood–brain barrier and the complex heterogeneity of traumatic brain injury. We also examine the physicochemical properties of NPs, emphasizing the role of size, shape, and surface characteristics in their interactions with biological barriers and cellular uptake mechanisms. The review concludes by exploring the options of targeting ligands designed to augment NP affinity and retention to specific brain regions or cell types. Various targeting ligands are discussed for their ability to mimic receptor-ligand interaction, and brain-specific extracellular matrix components. Strategies to mimic viral mechanisms to increase uptake are discussed. Finally, the emergence of antibody, antibody fragments, and antibody mimicking peptides are discussed as promising targeting strategies. By integrating insights from these scientific fields, this review provides an understanding of NP-based targeting strategies for personalized medicine approaches to neurological disorders. The design considerations discussed here pave the way for the development of NP platforms with enhanced therapeutic efficacy and minimized off-target effects, ultimately advancing the field of neural engineering.
Electroencephalographic power ratio and peak frequency difference associate with central sensitization in chronic pain
Authors: Ding Keqin , Arginteanu Toren , Anderson White Mirinda , Lovell Lyndah , Thakor Nitish V , Doshi Tina
Published: December 2024

Objective. Central sensitization, or increased responsiveness of the central nervous system to sensory input, is present in many chronic pain patients. Clinically, it is detected through subjective, patient-reported measures. There is a need for reliable, direct measurements of neural response to controlled stimuli to quantify neuronal dysfunction in pain. The goal of this work is to investigate cortical activity, recorded via electroencephalogram (EEG), during objective and calibrated painful stimulation in chronic pain patients. Approach. Chronic pain patients (N = 8) and healthy controls (N = 8) participated in this study. We recorded electroencephalography (EEG) at rest (baseline) and during evoked pain tasks, including thermal and mechanical stimuli. The evoked pain was applied following the quantitative sensory testing (QST) protocol, which is a research technique that applies objective, calibrated painful stimuli. Main results. Peak alpha frequency at rest was significantly lower in chronic pain patients compared to healthy controls (p < 0.0002), while EEG alpha/theta and alpha/beta power ratios at rest were higher in patients (p < 0.0002). During thermal QST, these power ratios decreased in patients and increased in controls (p < 0.0002 for both). During mechanical QST, power ratios decreased or did not change. Furthermore, the peak theta–beta frequency difference at baseline was significantly lower in patients compared to controls (p < 0.0002). During thermal QST, this difference increased in patients and decreased in controls; during mechanical QST, this difference increased in both patients and controls (p < 0.0002). Functional connectivity analysis showed that controls had greater baseline theta connectivity strength that increased during mechanical QST (p < 0.0002). Significance. This work demonstrates differential patterns of EEG activity at rest and during acute painful stimulation in chronic pain patients compared to healthy controls. These measures may quantify an individual’s tendency to experience chronic pain and central sensitization and serve as diagnostic biomarkers.
Characteristics of plasma disruption mitigation achieved by MGI and SPI on EAST
Authors: Zhao S.B. , Yuan J.S. , Zhuang H.D. , Zuo G.Z. , Li L. , Tang T. , Zeng L. , Duan Y.M. , Shi T.H. , Mao S.T. , Chen D.L. , Huang M. , Chen Y. , Hu J.S.
Published: December 2024

This study systematically compares the influence of shattered pellet injection (SPI) and massive gas injection (MGI) on plasma disruption mitigation within the Experimental Advanced Superconducting Tokamak. The results reveal that SPI demonstrates significant advantages over MGI in plasma disruption mitigation, as it predominantly deposits impurities within the plasma core. This leads to more rapid emission of thermal radiation and a significantly shorter total disruption duration compared to MGI. Conversely, MGI primarily deposits impurities at the plasma edge, and its impurity penetration duration is longer compared to that of SPI. During the current quench phase, MGI displays an evident radiation tail extending from the plasma core to its edge, accompanied by a second current spike. These phenomena are primarily attributed to cold vertical displacement events, which cause the plasma to directly contact the first wall, thereby generating halo currents and emitting hard x-rays. Furthermore, both SPI and MGI exhibit clear magnetohydrodynamic (MHD) mode switching, wherein the inherent n = 1 and n = 2 modes transition to a new n = 1 mode. This new mode features a reversed rotation direction and is accompanied by a burst of soft x-rays from the plasma core. This observation suggests that the observed MHD mode switching is driven by impurity‒plasma interactions rather than the impurity injection method. Future research endeavors must focus on high-resolution diagnostics and further experimentation to better understand the impacts of impurities on MHD modes. Overall, this study provides crucial data support for improving plasma disruption mitigation strategies for ITER and other future fusion reactors.
Comment on ‘Cropland abandonment in the context of drought, economic restructuring, and migration in Northeast Syria’
Authors: Ash Konstantin , Trinh Duy
Published: December 2024

An article recently published in Environmental Research Letters made available data on land abandonment in Syria before the onset of the Syrian civil war. The article claims that land abandonment was driven by mismanagement of irrigation through neoliberal economic policies before the 2006–10 Syrian drought and that agriculture quickly recovered after the drought. We use inferential statistics to test the authors’ claims. We find that before the drought, land abandonment occurred in areas with more rain-fed agriculture and was associated with population growth in sub-districts with more urban land cover. This finding suggests that pre-drought land abandonment was driven by increased urban development, rather than water mismanagement and irrigation policy reform. After drought onset, we find climatic stress caused first-year land abandonment, consistent with the authors’ claims. We also find third-year land abandonment is associated with population decline through 2010, going against the claim of a quick recovery. Our evidence suggests that the drought interrupted a long-term trend of decreasing agricultural use related to local urban expansion, bringing about a new trend of agricultural abandonment as a result of climate-induced out-migration. We find no evidence that land abandonment is associated with neoliberal policy reforms, or that there was a recovery when the drought ended.
Policy mixes for sustainable development pathways: representation in integrated assessment models
Authors: Dombrowsky Ines , Iacobuţă Gabriela Ileana , Daioglou Vassilis , Keppler Dorothee , Soergel Bjoern , Weindl Isabelle , Kriegler Elmar
Published: December 2024

The Paris Agreement on climate change and the 2030 Agenda on Sustainable Development require unprecedented transformations to sustainability, while maximising synergies and minimising trade-offs between the two agendas. The policy studies and sustainability transition literatures suggest that addressing the complex policy interlinkages requires ambitious, coherent, comprehensive and credible policy mixes supported by synergistic combinations of governance modes. We investigate to which extent these assumptions are reflected in quantitative scenarios produced with integrated assessment models. As a case study, we assess a new set of target-seeking sustainable development pathway (SDP) scenarios. We scrutinise the modelling protocols and the scenario results to analyse the extent to which these modelled SDPs represent governance modes and policy instrument types and purposes, and assess the resulting policy mix characteristics. As such, we bridge the scenario modelling and policy mix literatures and provide an initial pathway appraisal. We find that the modelled SDPs use policy mixes to constrain negative side-effects of unmitigated climate measures to achieve several SDGs simultaneously. The policy mixes speak to several policy mix characteristics. However, they are only partially spelled so far and their credibility remains limited. This calls for additional policy-translation efforts.
Study on the rheological properties of nano-SiO2 composite modified basalt mineral fiber asphalt mortar
Authors: Gao Haiwei , Zheng Nanxiang , Zhang Xiang , Li Zhihui , Cong Zhuohong
Published: December 2024

To investigate the impact of mineral fiber modification and dosage on the rheological properties of fiber asphalt mastic, basalt fiber surface roughness was enhanced using nano-SiO2 solution. Fiber asphalt mastic was prepared with a filler-bitumen ratio of 1.6 and fiber dosages of 0%, 1.3%, 2.6%, 3.9%, and 5.2%. The taper entry test, dynamic shear rheology test, and bending beam rheology test were employed to analyze the variations in taper entry, shear strength, complex modulus (G*), phase angle (δ), rutting factor (G*/sinδ), modulus of strength (S), and rate of change of strength (m) of the fiber asphalt mastic. The results indicate that the optimal dosage of mineral fibers in fiber asphalt mastic is 2.6%. Nano-modified basalt fibers significantly enhance the anti-shear capacity of asphalt mastic. The high-temperature stability of fiber asphalt mastic improves with increasing fiber dosage, but the improvement becomes negligible beyond a 2.6% dosage. The interfacial bonding layer formed by asphalt on the fiber surface enhances the high-temperature performance and stress dissipation at low temperatures, thereby improving low-temperature cracking resistance.
Development of objective test functions for modeling and sensitivity analysis of the mechanical behaviour of aluminum-agro-marine waste composites
Authors: Barah Obinna Onyebuchi , Nnamchi Stephen Ndubuisi , Selvam Milon Dennison , Mundu Mustafah Muhamad , Abdulkarim Abubakar
Published: December 2024

Aluminum-based composites reinforced with agro-marine waste materials present an eco-friendly, cost-effective solution for industries needing lightweight and durable materials. This study develops and evaluates the mechanical properties of aluminum (AA6061) composites reinforced with plantain stem ash, eucalyptus wood ash, and periwinkle shell powder for potential aerospace, automotive, and marine applications. Composite samples were prepared according to ASTM standards for tensile, compressive, flexural, wear, and fatigue tests. Objective Test Functions (OTFs) were derived using physical modeling and sensitivity analysis to filter impactful variables. Testing was conducted using universal testing machines, and wear/friction tests followed ASTM G99 guidelines. The physical models showed strong correlations (adjusted R2: 0.9033–1.0000). Measured properties included tensile strength (1907.46–2000.05 Pa), compressive strength (30.33–215.14 Pa), flexural strength (412.72–556.42 N-m2), wear rate (55.01–63.27 m3/m), coefficient of friction (0.102), and fatigue cycle (13.81–27.63 cycles). Except for the coefficient of friction, all results were consistent with the developed OTFs, confirming the material’s structural integrity. The composites displayed favourable properties for use in aerospace, automotive, and marine industries, offering strength, lightweight characteristics, and corrosion resistance. The OTFs validated the material’s performance, making it a viable alternative to conventional materials. Consequently, aluminum-agro-marine waste composites demonstrate excellent mechanical properties, with high potential for industrial applications.
Wear behaviour of friction surfaced Al-Ni and Al-SiC coatings over mild steel
Authors: Sivalingam Vinodh , Thirumalaisamy Ramakrishnan , Ramasamy Padmanaban
Published: December 2024

The friction surfacing (FS) method offers solid-state deposition of both identical and distinct coatings while avoiding a number of the issues that encompass the traditional fusion coating process. This study investigates FS for depositing aluminium based metal matrix composites (MMCs) onto AISI1018 mild steel substrates. The Al-2Si-15SiC and Al7075-15Ni MMC consumables used for the FS process were fabricated via stir casting. The FS process, optimized at 1200 rpm for Al-SiC and 1500 rpm for Al-Ni, resulted in refined microstructures and enhanced properties. Scanning electron microscopy (SEM) and energy dispersive x-ray analysis (EDAX) of the coating reveals surface with equiaxed and fine grains. The development of Al3Ni intermetallic compounds at the coating’s interface strengthens the bond by allowing the substrate and coating material to diffuse into each other. An excellent bonding strength of 147 MPa and 142 MPa is observed for the Al7075-15Ni and Al-2Si-15SiC coating deposits, respectively. In comparison to MMC consumable rods, the FS composite coating delivers 80%–85% reduction in grain size and enhances hardness. Vickers microhardness tests showed substantial hardness increases, with Al-Ni coatings reaching 183 HV. Wear tests indicated that Al-Ni coatings outperformed Al-SiC coatings and the steel substrate, exhibiting lower wear rates and friction coefficients. This research underscores FS’s effectiveness in improving the properties of aluminium MMC coatings on mild steel, with Al-Ni coatings showing exceptional wear resistance and bond strength for industrial applications.
Modelling long-term greenhouse gas mitigation pathways for Mongolia
Authors: Namkhainyam Tsolmon , Ovgor Bavuudorj , Jargal Dorjpurev , Malley Christopher S
Published: December 2024

Mongolia’s faces substantial challenges to reduce its Greenhouse Gas (GHG) emissions due to reliance on coal to meet electricity, heat and other energy demand and large livestock emissions. Despite this, Mongolia has committed to reduce GHG emissions by 22.7% in 2030 compared to a baseline scenario. Greenhouse gas mitigation assessments for Mongolia have focussed on actions to achieve emission reductions by 2030, but not on the potential for further reductions over the longer-term. This study addresses this gap through the development of long-term (2050) GHG emission pathways for Mongolia. These pathways aim to inform what level of GHG reduction targets Mongolia could commit to for the period after its current target expires. Greenhouse gas emissions are quantified for historic years (2010–2019) for all major GHG emitting sectors, and projected to 2050 based on the population and economic forecasts. Finally, mitigation scenarios modelling implementation of 49 specific mitigation measures are developed, to quantify their emission reduction potential. Without mitigation, GHG emissions were estimated to increase by 67% and 139% in 2030 and 2050, respectively, compared to 2019 levels (39 million tonnes CO2-eq emissions). Implementation of the 49 mitigation measures could reduce GHG emissions by 40% in 2050 compared to the baseline. Therefore, post-2030, Mongolia could increase its climate change mitigation ambition. Renewable Electricity generation, and energy efficiency were the measures that could achieve the majority of these additional emission reductions. However, there remains a substantial gap between the emission reduction potential of technically feasible measures currently being considered in Mongolia’s climate change mitigation planning, and full decarbonisation.
Stakeholder perspectives on fostering the water-energy-food nexus in Jordan: lessons beyond agricultural water management
Authors: Chemura Abel , Al-Smadi Walaa , Abkar Ali , Sawwan Jamal , Alananbeh Azzam , Farhan Ibrahim , Ghnaimat Amina , Alkhatatbeh Hamad Adel , Al Daraien Reem , Al-Qudah Tamara , Hassouneh Kholoud , Naimat Maram Al , Hamdi Luma , Abu Hammour Wafaa , Handam Ahmed , Hamdan Mutaz M , Daoud Hussein , Issa Ala Bani , Al-Salaymeh Bilal , Hammour Rashed Abu , Awamleh Ali , Alnimri Nataly , Alzyoud Samia , Ellsäßer Florian J , Dou Yue , Nelson Andrew , Al-Salaymeh Ahmed , Darvishzadeh Roshanak
Published: December 2024

The water–energy–food (WEF) nexus is an integrated conceptual tool for achieving sustainable development especially for countries facing limitations in one or more of its three pillars. The approach relies on bringing different stakeholders from the water, food and energy sectors together to collaboratively plan and adopt a holistic approach to resources management. This enables them to address sector-specific issues and develop a comprehensive understanding of the connected sectors leading to better outcomes. However, WEF nexus implementation is currently in its infancy in many countries and stakeholders are in the process of learning how to effectively communicate and collaborate with each other. In this paper, we report the state of the WEF nexus in Jordan, a dry country grappling with water, energy and food production challenges in a changing climate. Stakeholders from line ministries, academics, private sector players and non-state actors were brought together to discuss the status of the WEF nexus and identify challenges that need to be overcome for full realization of the WEF nexus as an operational framework for integrated development at country level. Stakeholders identified 7 cardinal lessons in the process of WEF nexus implementation in Jordan. These are that (i) data/information sharing is vital (ii) WEF nexus requires funding, (iii) collaborations among actors is key, (iv) inclusivity in planning is necessary, (v) clear responsibilities and boundaries among stakeholders are needed, (vi) sustainability and cohesion are a must and (vii) building trust among and within organizations is a primary ingredient for success. A deeper understanding of the interrelated dynamics of these challenges is required to foster the WEF nexus in Jordan as the issues are grave but not insurmountable. It is therefore suggested that deliberate efforts are needed from a technical and policy angle to ensure full operationalization of the WEF nexus approach in Jordan and elsewhere.
On positivity for the Peterson variety
Authors: Goldin Rebecca
Published: December 2024

We aim in this manuscript to describe a specific notion of geometric positivity that manifests in cohomology rings associated to the flag variety

G

/

B

G/B

and, in some cases, to subvarieties of

G

/

B

G/B

. We offer an exposition on the the well-known geometric basis of the homology of

G

/

B

G/B

provided by Schubert varieties, whose dual basis in cohomology has nonnegative structure constants. In recent work [R. Goldin, L. Mihalcea, and R. Singh, Positivity of Peterson Schubert Calculus, arXiv2106.10372] we showed that the equivariant cohomology of Peterson varieties satisfies a positivity phenomenon similar to that for Schubert calculus for

G

/

B

G/B

. Here we explain how this positivity extends to this particular nilpotent Hessenberg variety, and offer some open questions about the ingredients for extending positivity results to other Hessenberg varieties.
The SLE‐associated TREX1‐P212fs mutation disrupts ER association leading to type I interferonopathy
Authors: Xu Shan , Xiao Nanyang , Du Hekang , Zhou Xueyuan , Huang Miaohui , Feng Sisi , Hu Shun , Zhang Xiaoxiong , Zhang Sitong , Cui Dongya , Zhang Sheng , Chen Qi
Published: December 2024

The TREX1 gene encodes a highly efficient DNA exonuclease that plays an important role in maintaining DNA homeostasis in the cytoplasm. TREX1 mutations lead to a spectrum of type I interferonopathies that are characterized by systemic inflammation, high blood levels of autoantibodies, and spontaneously activated immunity. The TREX1‐P212fs mutation is thought to be linked to systemic lupus erythematosus (SLE). Here, we analyzed the functions of 20 TREX1 mutants and found that the TREX1‐P212fs mutant was able to reduce DNA enzyme activity and missed endoplasmic reticulum localization. Mouse‐derived in situ Trex1 models of transcoding mutations have not been reported. We successfully constructed Trex1‐P212fs mice by CRISPR‐Cas9 technology. Trex1P212fs/P212fs mice exhibit systemic inflammation, lymphocytosis, vasculitis, and kidney disease. The excessive autoantibody production was also present in these mice. We further demonstrated that TREX1 (1–212) protein lost its interaction with RPN1, the subunit that makes up the oligosaccharyl transferase (OST) complex. These data suggest an important role of TREX1‐C‐terminal association with the endoplasmic reticulum in inducing immune activation and the Trex1‐P212fs model may provide theoretical support for a better understanding of SLE treatment and defense.
Chloroquine‐induced proinsulin misfolding in the endoplasmic reticulum underlies the attenuation of mature insulin synthesis
Authors: Xu Jialu , Zhu Ruimin , Chen Yiyu , Li Xin , Chen Xuequn , Liu Ming , Huang Yumeng
Published: December 2024

Chloroquine (CQ), initially introduced for the clinical treatment of malaria, has subsequently been found to exhibit beneficial effects in combating diabetes mellitus. The anti‐hyperglycemic properties of chloroquine may be attributed to its anti‐inflammatory response and its ability to activate the insulin signaling pathway. However, both animal and clinical studies have yielded mixed results. Moreover, the impact of chloroquine on pancreatic β‐cells, the key player of glycemic control, was not known. To fill this knowledge gap, we investigated the effects of chloroquine on pancreatic β‐cell functions. Our findings revealed that while chloroquine did not alter proinsulin expression, it interfered with the conversion of proinsulin to insulin, resulting in reduced insulin levels. Using multiple independent approaches, we further showed that chloroquine disrupted proinsulin oxidative folding in the endoplasmic reticulum (ER) and impaired proinsulin trafficking from ER to Golgi, leading to ER stress and decreased insulin production. Notably, the elevated ER stress observed in chloroquine‐treated β‐cells was reversed upon knockout of insulin genes, indicating that chloroquine‐induced β‐cell ER stress primarily through the accumulation of misfolded proinsulin, rather than directly affecting ER homeostasis. Further investigation into the mechanisms underlying chloroquine‐induced proinsulin misfolding revealed that the accumulation of misfolded proinsulin was not caused by autophagy inhibition or the alkaline pH of chloroquine. Instead, it was primarily due to the disruption of the interaction between proinsulin and protein disulfide isomerase (PDI). Our findings unveiled new mechanisms of chloroquine treatment and raised important safety considerations regarding the use of chloroquine in diabetes treatment.