bluuebunny/crossref_metadata_2025_split huggingface dataset:
Permanent areas and changes in forests, grasslands, and wetlands in the North European Plain since the eighteenth century—a case study of the Kościan Plain in Poland
Authors: Medyńska-Gulij Beata , Szoszkiewicz Krzysztof , Cybulski Paweł , Wielebski Łukasz 
Published: May 2024

AbstractThis study investigates the intricate and enduring interplay of historical events, human activities, and natural processes shaping the landscape of North European Plain in western Poland over 230 years. Topographic maps serve as reliable historical data sources to quantify changes in forest, grassland, and wetland areas, scrutinizing their fragmentation and persistence. The primary objectives are to identify the permanent areas of the landscape and propose a universal cartographic visualization method for effectively mapping these changes. Using topographic maps and historical data, this research quantifies land cover changes, especially in forest, grassland, and wetland areas. With the help of retrogressive method we process raster historical data into vector-based information. Over time, wetlands experienced a substantial reduction, particularly in 1960–1982, attributed to both land reclamation and environmental factors. Grassland areas fluctuated, influenced by wetland and drier habitat dynamics. Fragmentation in grassland areas poses biodiversity and ecosystem health concerns, whereas forested areas showed limited fluctuations, with wetland forests nearly disappearing. These findings highlight wetland ecosystems’ sensitivity to human impacts and emphasize the need to balance conservation and sustainable development to preserve ecological integrity. This study advances landscape dynamics understanding, providing insights into historical, demographic, economic, and environmental transformations. It underscores the imperative for sustainable land management and conservation efforts to mitigate human impacts on ecosystems and biodiversity in the North European Plain.
Emerging opportunities of using large language models for translation between drug molecules and indications
Authors: Oniani David , Hilsman Jordan , Zang Chengxi , Wang Junmei , Cai Lianjin , Zawala Jan , Wang Yanshan 
Published: May 2024

AbstractA drug molecule is a substance that changes an organism’s mental or physical state. Every approved drug has an indication, which refers to the therapeutic use of that drug for treating a particular medical condition. While the Large Language Model (LLM), a generative Artificial Intelligence (AI) technique, has recently demonstrated effectiveness in translating between molecules and their textual descriptions, there remains a gap in research regarding their application in facilitating the translation between drug molecules and indications (which describes the disease, condition or symptoms for which the drug is used), or vice versa. Addressing this challenge could greatly benefit the drug discovery process. The capability of generating a drug from a given indication would allow for the discovery of drugs targeting specific diseases or targets and ultimately provide patients with better treatments. In this paper, we first propose a new task, the translation between drug molecules and corresponding indications, and then test existing LLMs on this new task. Specifically, we consider nine variations of the T5 LLM and evaluate them on two public datasets obtained from ChEMBL and DrugBank. Our experiments show the early results of using LLMs for this task and provide a perspective on the state-of-the-art. We also emphasize the current limitations and discuss future work that has the potential to improve the performance on this task. The creation of molecules from indications, or vice versa, will allow for more efficient targeting of diseases and significantly reduce the cost of drug discovery, with the potential to revolutionize the field of drug discovery in the era of generative AI.
Quantification of attenuation and speckle features from endoscopic OCT images for the diagnosis of human brain glioma
Authors: Aleksandrova P. V. , Zaytsev K. I. , Nikitin P. V. , Alekseeva A. I. , Zaitsev V. Y. , Dolganov K. B. , Reshetov I. V. , Karalkin P. A. , Kurlov V. N. , Tuchin V. V. , Dolganova I. N. 
Published: May 2024

AbstractApplication of optical coherence tomography (OCT) in neurosurgery mostly includes the discrimination between intact and malignant tissues aimed at the detection of brain tumor margins. For particular tissue types, the existing approaches demonstrate low performance, which stimulates the further research for their improvement. The analysis of speckle patterns of brain OCT images is proposed to be taken into account for the discrimination between human brain glioma tissue and intact cortex and white matter. The speckle properties provide additional information of tissue structure, which could help to increase the efficiency of tissue differentiation. The wavelet analysis of OCT speckle patterns was applied to extract the power of local brightness fluctuations in speckle and its standard deviation. The speckle properties are analysed together with attenuation ones using a set of ex vivo brain tissue samples, including glioma of different grades. Various combinations of these features are considered to perform linear discriminant analysis for tissue differentiation. The results reveal that it is reasonable to include the local brightness fluctuations at first two wavelet decomposition levels in the analysis of OCT brain images aimed at neurosurgical diagnosis.
Wind energy resource assessment and wind turbine selection analysis for sustainable energy production
Authors: Spiru Paraschiv , Simona Paraschiv Lizica 
Published: May 2024

AbstractThe objective of this study is to perform an analysis to determine the most suitable type of wind turbine that can be installed at a specific location for electricity generation, using annual measurements of wind characteristics and meteorological parameters. Wind potential analysis has shown that the analyzed location is suitable for the development of a wind farm. The analysis was carried out for six different types of wind turbines, with a power ranging from 1.5 to 3.0 MW and a hub height set at 80 m. Wind power potential was assessed using the Weibull analysis. The values of the scale coefficient c were determined, and a large monthly variation was observed, with values ranging from 1.92 to 8.36 m/s and an annual value of 4.95 m/s. Monthly values for the shape coefficient k varied between 0.86 and 1.53, with an annual value of 1.07. Additionally, the capacity factor of the turbines was determined, ranging from 17.75 to 22.22%. The Vestas turbine, with a nominal power of 2 MW and a capacity factor of 22.22%, proved to be the most efficient wind turbine for the specific conditions of the location. The quantity of greenhouse gas emissions that will be reduced if this type of turbine is implemented was also calculated, considering the average CO2 emission intensity factor (kg CO2/kWh) of the national electricity system.
The central executive network moderates the relationship between posttraumatic stress symptom severity and gastrointestinal related issues
Authors: Howard Kia A. , Ahmad Salman S. , Chavez Jennifer V. , Hoogerwoerd Hannah , McIntosh Roger C. 
Published: May 2024

AbstractAlthough most adults experience at least one traumatic event in their lifetime, a smaller proportion will go on to be clinically diagnosed with post-traumatic stress disorder (PTSD). Persons diagnosed with PTSD have a greater likelihood of developing gastrointestinal (GI) disorders. However, the extent to which subclinical levels of post-traumatic stress (PTS) correspond with the incidence of GI issues in a normative sample is unclear. Resting state fMRI, medical history, psychological survey, and anthropometric data were acquired from the Enhanced Nathan Kline Institute-Rockland Sample (n = 378; age range 18–85.6 years). The primary aim of this study was to test the main effect of subclinical PTS symptom severity on the number of endorsed GI issues. The secondary aim was to test the moderating effect of high versus low resting state functional connectivity (rsFC) of the central executive network (CEN) on the relationship between PTS symptom severity and GI issues. Trauma Symptom Checklist-40 (TSC-40) scores were positively associated with the number of endorsed GI issues (b = −0.038, SE = .009, p < .001). The interaction between TSC-40 scores and rsFC within the CEN was significant on GI issues after controlling for sociodemographic and cardiometabolic variables (b = −0.031, SE = .016, p < .05), such that above average rsFC within the CEN buffered the effect of TSC-40 scores on GI issues. Our findings of higher rsFC within the CEN moderating the magnitude of coincidence in PTS and GI symptom severity may reflect the mitigating role of executive control processes in the putative stress signaling mechanisms that contribute to gut dysbiosis.
The analysis of ecological security and tourist satisfaction of ice-and-snow tourism under deep learning and the Internet of Things
Authors: Zhang Baiju 
Published: May 2024

AbstractThis paper aims to propose a prediction method based on Deep Learning (DL) and Internet of Things (IoT) technology, focusing on the ecological security and tourist satisfaction of Ice-and-Snow Tourism (IST) to solve practical problems in this field. Accurate predictions of ecological security and tourist satisfaction in IST have been achieved by collecting and analyzing environment and tourist behavior data and combining with DL models, such as convolutional and recurrent neural networks. The experimental results show that the proposed method has significant advantages in performance indicators, such as accuracy, F1 score, Mean Squared Error (MSE), and correlation coefficient. Compared to other similar methods, the method proposed improves accuracy by 3.2%, F1 score by 0.03, MSE by 0.006, and correlation coefficient by 0.06. These results emphasize the important role of combining DL with IoT technology in predicting ecological security and tourist satisfaction in IST.
Delineating organizational principles of the endogenous L-A virus by cryo-EM and computational analysis of native cell extracts
Authors: Schmidt Lisa , Tüting Christian , Kyrilis Fotis L. , Hamdi Farzad , Semchonok Dmitry A. , Hause Gerd , Meister Annette , Ihling Christian , Stubbs Milton T. , Sinz Andrea , Kastritis Panagiotis L. 
Published: May 2024

AbstractThe high abundance of most viruses in infected host cells benefits their structural characterization. However, endogenous viruses are present in low copy numbers and are therefore challenging to investigate. Here, we retrieve cell extracts enriched with an endogenous virus, the yeast L-A virus. The determined cryo-EM structure discloses capsid-stabilizing cation-π stacking, widespread across viruses and within the Totiviridae, and an interplay of non-covalent interactions from ten distinct capsomere interfaces. The capsid-embedded mRNA decapping active site trench is supported by a constricting movement of two flexible opposite-facing loops. tRNA-loaded polysomes and other biomacromolecules, presumably mRNA, are found in virus proximity within the cell extract. Mature viruses participate in larger viral communities resembling their rare in-cell equivalents in terms of size, composition, and inter-virus distances. Our results collectively describe a 3D-architecture of a viral milieu, opening the door to cell-extract-based high-resolution structural virology.
Overcoming thermostability challenges in mRNA–lipid nanoparticle systems with piperidine-based ionizable lipids
Authors: Hashiba Kazuki , Taguchi Masamitsu , Sakamoto Sachiko , Otsu Ayaka , Maeda Yoshiki , Ebe Hirofumi , Okazaki Arimichi , Harashima Hideyoshi , Sato Yusuke 
Published: May 2024

AbstractLipid nanoparticles (LNPs) have emerged as promising platforms for efficient in vivo mRNA delivery owing to advancements in ionizable lipids. However, maintaining the thermostability of mRNA/LNP systems remains challenging. While the importance of only a small amount of lipid impurities on mRNA inactivation is clear, a fundamental solution has not yet been proposed. In this study, we investigate an approach to limit the generation of aldehyde impurities that react with mRNA nucleosides through the chemical engineering of lipids. We demonstrated that piperidine-based lipids improve the long-term storage stability of mRNA/LNPs at refrigeration temperature as a liquid formulation. High-performance liquid chromatography analysis and additional lipid synthesis revealed that amine moieties of ionizable lipids play a vital role in limiting reactive aldehyde generation, mRNA–lipid adduct formation, and loss of mRNA function during mRNA/LNP storage. These findings highlight the importance of lipid design and help enhance the shelf-life of mRNA/LNP systems.
Alternative climate metrics to the Global Warming Potential are more suitable for assessing aviation non-CO2 effects
Authors: Megill Liam , Deck Kathrin , Grewe Volker 
Published: May 2024

AbstractA growing body of research has highlighted the major contribution of aviation non-CO2 emissions and effects to anthropogenic climate change. Regulation of these emissions, for example in the EU Emissions Trading System, requires the use of a climate metric. However, choosing a suitable climate metric is challenging due to the high uncertainties of aviation non-CO2 climate impacts, their variability in atmospheric lifetimes and their dependence on emission location and altitude. Here we use AirClim to explore alternatives to the conventional Global Warming Potential (GWP) by analysing the neutrality, temporal stability, compatibility and simplicity of existing climate metrics and perform a trade-off. We find that using the temperature-based Average Temperature Response (ATR) or using an Efficacy-weighted GWP (EGWP) would enable a more accurate assessment of existing as well as future aircraft powered by novel aviation fuels.
Terrestrial records of two hyperthermal events in the Cretaceous-Paleogene boundary suggest different control mechanisms
Authors: Ma Mingming , Wang Mengdi , Huang Huixin , Liu Xiuming 
Published: May 2024

AbstractTwo hyperthermal events with different carbon cycle perturbations occurred across the Cretaceous-Palaeogene boundary, i.e., the late Maastrichtian Warming Event and the Early Danian Dan-C2 event. However, the roles played by Deccan volcanism and orbital forcing in these two hyperthermal events are still debated. Here we obtain a terrestrial δ13Ccarb record in the Nanxiong Basin (southeastern China) and compare it with marine records. The results show that both hyperthermal events can be well distinguished and that the Dan-C2 event is characterized by a typical hyperthermal event. In addition, the δ13C excursion during the late Maastrichtian Warming Event was more muted and prolonged than that during the Dan-C2 event, and the short-eccentricity cycle disappeared in the marine record during the late Maastrichtian Warming Event, indicating that Deccan volcanism perturbed the carbon cycle during the late Maastrichtian Warming Event, while the Dan-C2 event was less influenced by volcanic perturbation.
Semantically enhanced attention map‐driven occluded person re‐identification
Authors: Ge Yiyuan , Yu Mingxin , Chen Zhihao , Lu Wenshuai , Shi Huiyu 
Published: May 2024

AbstractOccluded person re‐identification (Re‐ID) is to identify a particular person when the person's body parts are occluded. However, challenges remain in enhancing effective information representation and suppressing background clutter when considering occlusion scenes. This paper proposes a novel attention map‐driven network (AMD‐Net) for occluded person Re‐ID. In AMD‐Net, human parsing labels are introduced to supervise the generation of partial attention maps, while a spatial‐frequency interaction module is suggested to complement the higher‐order semantic information from the frequency domain. Furthermore, a Taylor‐inspired feature filter for mitigating background disturbance and extracting fine‐grained features is proposed. Moreover, a part‐soft triplet loss, which is robust to non‐discriminative body partial features is also designed. Experimental results on Occluded‐Duke, Occluded‐Reid, Market‐1501, and Duke‐MTMC datasets show that this method outperforms existing state‐of‐the‐art methods. The code is available at: https://github.com/ISCLab‐Bistu/SA‐ReID.
9.1 µW keyword spotting processor based on optimized MFCC and small‐footprint TENet in 28‐nm CMOS
Authors: Yu Haohai , He Keyan , Liu Yang , Chen Dihu 
Published: May 2024

AbstractThis letter proposes a low‐power keyword spotting (KWS) architecture based on a modified temporal efficient neural network (TENet) and a simplified mel‐frequency cepstrum coefficient (MFCC) algorithm. The optimized MFCC algorithm reduces the computational load by 82% for multiplications and 66% for additions. An efficient hardware architecture and data flow for TENet have been designed, resulting in a 3.1× reduction in the operating cycle compared to similar work. The parameter count and computational load are reduced by 3.7× and 2.8×, respectively, and the accuracy reaches 95.36% for ten keywords in the Google Speech Command Dataset (GSCD). Operating at a frequency of 16 KHz for MFCC and 100 KHz for NN accelerator on a 28 nm process, the power consumption overhead is 9.1 µW.
Predicting transformer temperature field based on physics‐informed neural networks
Authors: Tang Pengfei , Zhang Zhonghao , Tong Jie , Long Tianhang , Huang Can , Qi Zihao 
Published: May 2024

AbstractThe safe operation of oil‐immersed transformers is critical to the safety and stability of the power grid. As the operating time increases, the failure rate of oil‐immersed transformers shows an increasing trend, posing serious challenges to safe operation. It is necessary to investigate the internal state of the oil‐immersed transformer to improve the digital degree and achieve digitalisation and intelligent operation and maintenance. A physics‐informed neural network (PINN) for oil‐immersed transformers was introduced to reconstruct the temperature distribution inside the transformer. According to the approach, the loss function of the network would be optimised by incorporating physical constraint loss terms including heat transfer equations, initial conditions and boundary conditions. The results show that the method proposed can be used to reconstruct and predict the temperature field of transformers in a few seconds with satisfactory accuracy. In conclusion, the PINN proposed outperforms deep neural networks in terms of accuracy, reliability and interpretability, especially in data‐poor cases.
Design and evaluation of a monostable symmetric piezoelectric energy harvester based on cantilever structure and magnetic excitation action
Authors: Wang Liang , Zhang Yaxun , Wang Tianqi 
Published: May 2024

This work proposes a monostable symmetric piezoelectric energy harvester based on the cantilever structure and magnetic excitation action (M-PEH). The governing equations of M-PEH are derived based on its kinematic properties. The intrinsic frequency of the piezoelectric cantilever beam was obtained by modal simulation. It has been demonstrated that the mode of arrangement of the magnetic poles has a significant effect on the output voltage of the energy harvester. The proposed M-PEH has four driving magnets with a mass of 6 g and a radial driving distance of 15 mm for more efficient energy harvesting. The experimental results show that the maximum voltage of the M-PEH with the double U-type rotor was 31.2 V at 240 rpm and 110 kΩ external resistance. The average power of the PEH with the double U-type rotor was 16.562 mW at a speed of 240 rpm with an outer resistance of 20 kΩ. The energy harvester with a double U-type rotor can realize a voltage output of not less than 10 V in the range of 60–300 rpm when the same poles of the tip magnets are arranged outward. The M-PEH can also easily light up LEDs or miniature electronic watches with speeds of 120 rpm and 240 rpm. This further proves that the proposed piezoelectric energy harvester (M-PEH) has a better energy harvesting effect and great potential for practical applications.
Emergent two-band conduction at Ti delta-doped LaAlO3/KTaO3 (111) heterointerface
Authors: Fan Haiyang , Liu Jia , Ye Fei , Bao Mingrui , Zhang Ziheng , Li Zhuojun , Cheng Long , Zhai Xiaofang 
Published: May 2024

Recently, several intriguing interfacial phenomena have been discovered at the KTaO3 (111)-based heterointerfaces, such as the two-dimensional electron gas, superconductivity, anisotropic conductivity, etc. However, the available techniques to systematically manipulate such interfacial states are quite limited. Here, we devise a delta-doping strategy by inserting a sub-nanometer Ti layer with distinct reducibilities to the LaAlO3/KTaO3 (111) interface. In the delta-doped samples, we observe an unforeseen two-band conduction, evidenced by the emergence of a new type of electron carrier with an order-of-magnitude enhancement of mobility (∼1800 cm2V−1s−1) than the original carriers. Moreover, the appearance of the high-mobility carriers causes a sharp transition between the non-Fermi-liquid superconducting state and the Fermi-liquid state with reduced spin–orbit scattering. Further evidence shows that the new type of carriers stems from another in-gap state with a shallower energy level compared to the original carriers. Our study broadens the spectrum of interfacial carrier manipulation by introducing an extra band/channel for carrier conduction, which not only opens up new possibilities in device applications but also shines a light on the underlying physics of interfacial superconductivity.
Kinetic energy dependence and potential energy surface of the spin-forbidden reaction Sm+ (8F) + N2O (1Σ+) → SmO+ (6Δ) + N2 (1Σg+)
Authors: Loertscher David H. , Stevenson Brandon C. , Armentrout P. B. 
Published: May 2024

The kinetic energy dependence of the title reaction is examined using guided ion beam tandem mass spectrometry. Because this reaction is spin-forbidden, crossings between octet and sextet hypersurfaces presumably must occur. Furthermore, Sm+ must transition from a 4f66s1 configuration in the reactant to 4f55d2 in order to have the orbital occupancy required to form the triple bond in SmO+ (6Δ). Despite being strongly exothermic (∼4 eV), the reaction proceeds with low efficiency (18% ± 4%) via a barrierless process at low energies. Below ∼0.3 eV, the cross section follows a kinetic energy dependence that roughly parallels that of the collision rate for ion–dipole reactions. At higher collision energies, the reaction cross section increases until it follows the trajectory cross section closely from 3 to 5 eV, indicating that another pathway opens on the reaction hypersurface. Modeling this increase yields a threshold energy for this new pathway at 0.54 ± 0.05 eV. Theoretical potential energy surfaces that do not include spin–orbit interactions for the reaction show that there is a barrier of height 1.19 eV (MP2) or 0.49 eV [CCSD(T)] to insertion of Sm+ into the N2–O bond and that there are several places where octet and sextet surfaces can intersect and interact. By considering the distribution of spin–orbit states generated in the ion source, the internal energy of the N2O reactant, and the influence of coupling between electronic, orbital, and rotational angular momentum, the low-efficiency, exothermic behavior as well as the increase in efficiency at higher energies can plausibly be explained.