bluuebunny/crossref_metadata_2025_split huggingface dataset:
High-temperature concomitant metal-insulator and spin-reorientation transitions in a compressed nodal-line ferrimagnet Mn3Si2Te6
Authors: Susilo Resta A. , Kwon Chang Il , Lee Yoonhan , Salke Nilesh P. , De Chandan , Seo Junho , Kang Beomtak , Hemley Russell J. , Dalladay-Simpson Philip , Wang Zifan , Kim Duck Young , Kim Kyoo , Cheong Sang-Wook , Yeom Han Woong , Kim Kee Hoon , Kim Jun Sung 
Published: May 2024

AbstractSymmetry-protected band degeneracy, coupled with a magnetic order, is the key to realizing novel magnetoelectric phenomena in topological magnets. While the spin-polarized nodal states have been identified to introduce extremely-sensitive electronic responses to the magnetic states, their possible role in determining magnetic ground states has remained elusive. Here, taking external pressure as a control knob, we show that a metal-insulator transition, a spin-reorientation transition, and a structural modification occur concomitantly when the nodal-line state crosses the Fermi level in a ferrimagnetic semiconductor Mn3Si2Te6. These unique pressure-driven magnetic and electronic transitions, associated with the dome-shaped Tc variation up to nearly room temperature, originate from the interplay between the spin-orbit coupling of the nodal-line state and magnetic frustration of localized spins. Our findings highlight that the nodal-line states, isolated from other trivial states, can facilitate strongly tunable magnetic properties in topological magnets.
Structural insights into drug transport by an aquaglyceroporin
Authors: Chen Wanbiao , Zou Rongfeng , Mei Yi , Li Jiawei , Xuan Yumi , Cui Bing , Zou Junjie , Wang Juncheng , Lin Shaoquan , Zhang Zhe , Wang Chongyuan 
Published: May 2024

AbstractPentamidine and melarsoprol are primary drugs used to treat the lethal human sleeping sickness caused by the parasite Trypanosoma brucei. Cross-resistance to these two drugs has recently been linked to aquaglyceroporin 2 of the trypanosome (TbAQP2). TbAQP2 is the first member of the aquaporin family described as capable of drug transport; however, the underlying mechanism remains unclear. Here, we present cryo-electron microscopy structures of TbAQP2 bound to pentamidine or melarsoprol. Our structural studies, together with the molecular dynamic simulations, reveal the mechanisms shaping substrate specificity and drug permeation. Multiple amino acids in TbAQP2, near the extracellular entrance and inside the pore, create an expanded conducting tunnel, sterically and energetically allowing the permeation of pentamidine and melarsoprol. Our study elucidates the mechanism of drug transport by TbAQP2, providing valuable insights to inform the design of drugs against trypanosomiasis.
Detection of Anaplasma and Ehrlichia bacteria in humans, wildlife, and ticks in the Amazon rainforest
Authors: Buysse Marie , Koual Rachid , Binetruy Florian , de Thoisy Benoit , Baudrimont Xavier , Garnier Stéphane , Douine Maylis , Chevillon Christine , Delsuc Frédéric , Catzeflis François , Bouchon Didier , Duron Olivier 
Published: May 2024

AbstractTick-borne bacteria of the genera Ehrlichia and Anaplasma cause several emerging human infectious diseases worldwide. In this study, we conduct an extensive survey for Ehrlichia and Anaplasma infections in the rainforests of the Amazon biome of French Guiana. Through molecular genetics and metagenomics reconstruction, we observe a high indigenous biodiversity of infections circulating among humans, wildlife, and ticks inhabiting these ecosystems. Molecular typing identifies these infections as highly endemic, with a majority of new strains and putative species specific to French Guiana. They are detected in unusual rainforest wild animals, suggesting they have distinctive sylvatic transmission cycles. They also present potential health hazards, as revealed by the detection of Candidatus Anaplasma sparouinense in human red blood cells and that of a new close relative of the human pathogen Ehrlichia ewingii, Candidatus Ehrlichia cajennense, in the tick species that most frequently bite humans in South America. The genome assembly of three new putative species obtained from human, sloth, and tick metagenomes further reveals the presence of major homologs of Ehrlichia and Anaplasma virulence factors. These observations converge to classify health hazards associated with Ehrlichia and Anaplasma infections in the Amazon biome as distinct from those in the Northern Hemisphere.
Giant magneto-photoluminescence at ultralow field in organic microcrystal arrays for on-chip optical magnetometer
Authors: Wang Hong , Yin Baipeng , Bai Junli , Wei Xiao , Huang Wenjin , Chang Qingda , Jia Hao , Chen Rui , Zhai Yaxin , Wu Yuchen , Zhang Chuang 
Published: May 2024

AbstractOptical detection of magnetic field is appealing for integrated photonics; however, the light-matter interaction is usually weak at low field. Here we observe that the photoluminescence (PL) decreases by > 40% at 10 mT in rubrene microcrystals (RMCs) prepared by a capillary-bridge assembly method. The giant magneto-PL (MPL) relies on the singlet-triplet conversion involving triplet-triplet pairs, through the processes of singlet fission (SF) and triplet fusion (TF) during radiative decay. Importantly, the size of RMCs is critical for maximizing MPL as it influences on the photophysical processes of spin state conversion. The SF/TF process is quantified by measuring the prompt/delayed PL with time-resolved spectroscopies, which shows that the geminate SF/TF associated with triplet-triplet pairs are responsible for the giant MPL. Furthermore, the RMC-based magnetometer is constructed on an optical chip, which takes advantages of remarkable low-field sensitivity over a broad range of frequencies, representing a prototype of emerging opto-spintronic molecular devices.
Firefly-inspired bipolar information indication system actuated by white light
Authors: Huang Hanwen , Yin Jiamiao , Zhou Qianwen , Li Huateng , Yang Junying , Wang Yaoben , Xu Ming , Wang Changchun 
Published: May 2024

AbstractThe indication of information in materials is widely used in our daily life, and optical encoding materials are ideal for information loading due to their easily readable nature and adjustable optical properties. However, most of them could only indicate one type of information, either changing or unchanging due to the mutual interference. Inspired by firefly, we present a non-interfering bipolar information indication system capable of indicating both changing and unchanging information. A photochemical afterglow material is incorporated into the photonic crystal matrix through a high-throughput technique called shear-induced ordering technique, which can efficiently produce large-area photonic crystal films. The indication of changing and unchanging information is enabled by two different utilizations of white light by the afterglow material and photonic crystals, respectively, which overcome the limitations of mutual interference. As a proof of concept, this system is used to indicate the changing photodegradation level of mecobalamin (a photosensitive medicine) and unchanging intrinsic drug information with anti-counterfeiting functionality, which is a promising alternative to instantly ascertain the efficacy of medicine at home where conventional assays are impractical.
Urban development pattern’s influence on extreme rainfall occurrences
Authors: Yang Long , Yang Yixin , Shen Ye , Yang Jiachuan , Zheng Guang , Smith James , Niyogi Dev 
Published: May 2024

AbstractGrowing urban population and the distinct strategies to accommodate them lead to diverse urban development patterns worldwide. While local evidence suggests the presence of urban signatures in rainfall anomalies, there is limited understanding of how rainfall responds to divergent urban development patterns worldwide. Here we unveil a divergence in the exposure to extreme rainfall for 1790 inland cities globally, attributable to their respective urban development patterns. Cities that experience compact development tend to witness larger increases in extreme rainfall frequency over downtown than their rural surroundings, while the anomalies in extreme rainfall frequency diminish for cities with dispersed development. Convection-permitting simulations further suggest compact urban footprints lead to more pronounced urban-rural thermal contrasts and aerodynamic disturbances. This is directly responsible for the divergent rainfall responses to urban development patterns. Our analyses offer significant insights pertaining to the priorities and potential of city-level efforts to mitigate the emerging climate-related hazards, particularly for countries experiencing rapid urbanization.
Dataset of weekly intra-treatment diffusion weighted imaging in head and neck cancer patients treated with MR-Linac
Authors: El-Habashy Dina M. , Wahid Kareem A. , He Renjie , McDonald Brigid , Mulder Samuel J. , Ding Yao , Salzillo Travis , Lai Stephen Y. , Christodouleas John , Dresner Alex , Wang Jihong , Naser Mohamed A. , Fuller Clifton D. , Mohamed Abdallah Sherif Radwan ,   Joint Head and Neck Radiation Therapy-MRI Development Cooperative
Published: May 2024

AbstractRadiation therapy (RT) is a crucial treatment for head and neck squamous cell carcinoma (HNSCC); however, it can have adverse effects on patients’ long-term function and quality of life. Biomarkers that can predict tumor response to RT are being explored to personalize treatment and improve outcomes. While tissue and blood biomarkers have limitations, imaging biomarkers derived from magnetic resonance imaging (MRI) offer detailed information. The integration of MRI and a linear accelerator in the MR-Linac system allows for MR-guided radiation therapy (MRgRT), offering precise visualization and treatment delivery. This data descriptor offers a valuable repository for weekly intra-treatment diffusion-weighted imaging (DWI) data obtained from head and neck cancer patients. By analyzing the sequential DWI changes and their correlation with treatment response, as well as oncological and survival outcomes, the study provides valuable insights into the clinical implications of DWI in HNSCC.
Extension of Japan’s Prefectural Emission Accounting and Enrichment of Socioeconomic Data from 1990 to 2020
Authors: Chen Zhiheng , Huang Liqiao , Liu Yang , Yoshikuni Yoshida , Tanaka Kenji , Long Yin 
Published: May 2024

AbstractWith the continuous increase in carbon dioxide emissions due to human activities and the resulting severe climate issues, there is global concern about energy conservation and emission reduction. However, detailed data on energy consumption and emissions at a fine-grained scale, particularly regarding spatial dimensions and sector-specific emissions, remains insufficient and in need of refinement and timely updates. In Japan, following the Fukushima nuclear disaster, there has been a significant shift from nuclear power generation to reliance on fossil fuels across various sectors, highlighting disparities in emissions data across different regions and industries. Our work extends the emissions time series for Japan’s 47 prefectures, incorporating their socioeconomic characteristics over a broader time frame and with a more detailed sectoral classification. The emissions inventory, covering the period from 1990 to 2020, is based on the consumption of the three main fossil fuels across 32 sectors, with emissions carefully allocated for regional power generation. This dataset, presented in a unified format, is expanded to include longer time scales and more detailed socioeconomic data. It is anticipated to offer crucial insights for establishing regional emission reduction targets and identifying sectoral priorities for decarbonization.
Data-driven optimization for microgrid control under distributed energy resource variability
Authors: Mathur Akhilesh , Kumari Ruchi , Meena V. P. , Singh V. P. , Azar Ahmad Taher , Hameed Ibrahim A. 
Published: May 2024

AbstractThe integration of renewable energy resources into the smart grids improves the system resilience, provide sustainable demand-generation balance, and produces clean electricity with minimal leakage currents. However, the renewable sources are intermittent in nature. Therefore, it is necessary to develop scheduling strategy to optimise hybrid PV-wind-controllable distributed generator based Microgrids in grid-connected and stand-alone modes of operation. In this manuscript, a priority-based cost optimization function is developed to show the relative significance of one cost component over another for the optimal operation of the Microgrid. The uncertainties associated with various intermittent parameters in Microgrid have also been introduced in the proposed scheduling methodology. The objective function includes the operating cost of CDGs, the emission cost associated with CDGs, the battery cost, the cost of grid energy exchange, and the cost associated with load shedding. A penalty function is also incorporated in the cost function for violations of any constraints. Multiple scenarios are generated using Monte Carlo simulation to model uncertain parameters of Microgrid (MG). These scenarios consist of the worst as well as the best possible cases, reflecting the microgrid’s real-time operation. Furthermore, these scenarios are reduced by using a k-means clustering algorithm. The reduced procedures for uncertain parameters will be used to obtain the minimum cost of MG with the help of an optimisation algorithm. In this work, a meta-heuristic approach, grey wolf optimisation (GWO), is used to minimize the developed cost optimisation function of MG. The standard LV Microgrid CIGRE test network is used to validate the proposed methodology. Results are obtained for different cases by considering different priorities to the sub-objectives using GWO algorithm. The obtained results are compared with the results of Jaya and PSO (particle swarm optimization) algorithms to validate the efficacy of the GWO method for the proposed optimization problem.
Ambient floor vibration sensing advances the accessibility of functional gait assessments for children with muscular dystrophies
Authors: Dong Yiwen , Iammarino Megan , Liu Jingxiao , Codling Jesse , Fagert Jonathon , Mirshekari Mostafa , Lowes Linda , Zhang Pei , Noh Hae Young 
Published: May 2024

AbstractMuscular dystrophies (MD) are a group of genetic neuromuscular disorders that cause progressive weakness and loss of muscles over time, influencing 1 in 3500–5000 children worldwide. New and exciting treatment options have led to a critical need for a clinical post-marketing surveillance tool to confirm the efficacy and safety of these treatments after individuals receive them in a commercial setting. For MDs, functional gait assessment is a common approach to evaluate the efficacy of the treatments because muscle weakness is reflected in individuals’ walking patterns. However, there is little incentive for the family to continue to travel for such assessments due to the lack of access to specialty centers. While various existing sensing devices, such as cameras, force plates, and wearables can assess gait at home, they are limited by privacy concerns, area of coverage, and discomfort in carrying devices, which is not practical for long-term, continuous monitoring in daily settings. In this study, we introduce a novel functional gait assessment system using ambient floor vibrations, which is non-invasive and scalable, requiring only low-cost and sparsely deployed geophone sensors attached to the floor surface, suitable for in-home usage. Our system captures floor vibrations generated by footsteps from patients while they walk around and analyzes such vibrations to extract essential gait health information. To enhance interpretability and reliability under various sensing scenarios, we translate the signal patterns of floor vibration to pathological gait patterns related to MD, and develop a hierarchical learning algorithm that aggregates insights from individual footsteps to estimate a person’s overall gait performance. When evaluated through real-world experiments with 36 subjects (including 15 patients with MD), our floor vibration sensing system achieves a 94.8% accuracy in predicting functional gait stages for patients with MD. Our approach enables accurate, accessible, and scalable functional gait assessment, bringing MD progressive tracking into real life.
Evaluating the strengths and weaknesses of large language models in answering neurophysiology questions
Authors: Shojaee-Mend Hassan , Mohebbati Reza , Amiri Mostafa , Atarodi Alireza 
Published: May 2024

AbstractLarge language models (LLMs), like ChatGPT, Google’s Bard, and Anthropic’s Claude, showcase remarkable natural language processing capabilities. Evaluating their proficiency in specialized domains such as neurophysiology is crucial in understanding their utility in research, education, and clinical applications. This study aims to assess and compare the effectiveness of Large Language Models (LLMs) in answering neurophysiology questions in both English and Persian (Farsi) covering a range of topics and cognitive levels. Twenty questions covering four topics (general, sensory system, motor system, and integrative) and two cognitive levels (lower-order and higher-order) were posed to the LLMs. Physiologists scored the essay-style answers on a scale of 0–5 points. Statistical analysis compared the scores across different levels such as model, language, topic, and cognitive levels. Performing qualitative analysis identified reasoning gaps. In general, the models demonstrated good performance (mean score = 3.87/5), with no significant difference between language or cognitive levels. The performance was the strongest in the motor system (mean = 4.41) while the weakest was observed in integrative topics (mean = 3.35). Detailed qualitative analysis uncovered deficiencies in reasoning, discerning priorities, and knowledge integrating. This study offers valuable insights into LLMs’ capabilities and limitations in the field of neurophysiology. The models demonstrate proficiency in general questions but face challenges in advanced reasoning and knowledge integration. Targeted training could address gaps in knowledge and causal reasoning. As LLMs evolve, rigorous domain-specific assessments will be crucial for evaluating advancements in their performance.
Efficient simulation of potential energy operators on quantum hardware: a study on sodium iodide (NaI)
Authors: Laskar Mostafizur Rahaman , Bhattacharya Atanu , Dasgputa Kalyan 
Published: May 2024

AbstractThis study introduces a conceptually novel polynomial encoding algorithm for simulating potential energy operators encoded in diagonal unitary forms in a quantum computing machine. The current trend in quantum computational chemistry is effective experimentation to achieve high-precision quantum computational advantage. However, high computational gate complexity and fidelity loss are some of the impediments to the realization of this advantage in a real quantum hardware. In this study, we address the challenges of building a diagonal Hamiltonian operator having exponential functional form, and its implementation in the context of the time evolution problem (Hamiltonian simulation and encoding). Potential energy operators when represented in the first quantization form is an example of such types of operators. Through systematic decomposition and construction, we demonstrate the efficacy of the proposed polynomial encoding method in reducing gate complexity from $$\mathcal {O}(2^n)$$

O
(

2
n

)

to $$\mathcal {O}\left( \sum _{i=1}^{r} {} ^nC_r \right)$$

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∑

i
=
1

r

n

C
r

(for some $$r\ll n$$

r
≪
n

). This offers a solution with lower complexity in comparison to the conventional Hadamard basis encoding approach. The effectiveness of the proposed algorithm was validated with its implementation in the IBM quantum simulator and IBM quantum hardware. This study demonstrates the proposed approach by taking the example of the potential energy operator of the sodium iodide molecule (NaI) in the first quantization form. The numerical results demonstrate the potential applicability of the proposed method in quantum chemistry problems, while the analytical bound for error analysis and computational gate complexity discussed, throw light on issues regarding its implementation.
Dynamic characteristics and evolution laws of underground brine in Mahai salt lake of Qaidam Basin during mining process
Authors: Kong Zhihan , Wang Guangcai , Li Qingyu , Zhao Quansheng , Hu Shuya 
Published: May 2024

AbstractIn the late stage of underground brine mining in salt lakes, the method of injecting fresh water is often used to extract the salt from the brine storage medium. This method of freshwater displacement breaks the original water–rock equilibrium and changes the evolution process of the original underground brine. To explore the mechanism of salt release in saline water-bearing media under conditions of relatively fresh lake water dissolution, this paper analyzes the changes in the chemical parameters of brine from 168 sampling points in the Mahai salt lake in the Qaidam Basin at three stages (before exploitation, during exploitation, and late exploitation) by correlation analysis, ion ratio analysis, and other methods and investigate the variations in porosity and the evolution laws of brine. The results show that the changes in the main ion content and brine mineralization during the exploitation process are small. The changes in Ca2+ content are significant due to the low solubility of calcium minerals, the precipitation of gypsum during the mixing process, and the adsorption of cations by alternating with Ca2+. Primary intergranular pore skeletons are easily corroded to form secondary pores, which increase the geological porosity. Na+ and Cl- are the dominant ions in the brine in the study area, but the concentration of Ca2 + decreased significantly under the influence of mining, by 41.7% in the middle period and 24.5% in the late period. The correlation between Ca2+ and salinity changes significantly in different mining stages, and the reason for the decrease of Ca2+ may be due to the influence of mineral dissolution, mixing, and anion-cation exchange. The porosity of the layer in the study area showed the opposite trend of Ca2+, and the porosity increased first and then decreased. The innovation of this paper lies in analyzing the reasons and mechanisms of the disturbance of artificial dissolution mining on stratum structure by comparing the hydrochemical characteristics and porosity of underground brine storage media in three different mining stages. The research in this paper provides a theoretical basis for the calculation of brine resource reserves and the sustainable development of underground brine in salt lake areas.
Integral terminal sliding mode fault tolerant control of quadcopter UAV systems
Authors: Nguyen Ngoc P. , Pitakwachara Phongsaen 
Published: May 2024

AbstractThe article presents an active fault-tolerant control scheme with an integral terminal sliding mode controller for the UAV systems. This scheme effectively addresses saturation issues, disturbances, and sensor and actuator faults. Initially, the quadcopter UAV's model is represented in state space form. Subsequently, an augmented system incorporating auxiliary states from sensor faults is developed. An adaptive sliding mode observer is proposed for estimating the actuator and sensor faults. The integral terminal sliding mode fault-tolerant control, designed for altitude and attitude regulation, relies on fault estimation data. In contrast, a cascade proportional-integral-derivative (PID) controller is employed for position control. Simulation results demonstrate the superiority of the proposed method over existing control algorithms.