Quadrupedal robots are highly regarded for their superior locomotion capabilities and terrain adaptability, making them competent in a wide range of applications. In autonomous navigation tasks, they are required to track upper-level trajectories to reach designated locations with flexible obstacle avoidance. This is typically achieved by a planner which generates a reference velocity and a controller which accurately tracks the velocity commands. In this article, we propose a learning-based controller for quadrupedal robots that achieves accurate and robust velocity tracking. To bridge the gap between simulation and reality, an analytical actuator model is proposed to simulate physical actuator dynamics. We then train a control policy in simulation using Constrained Reinforcement Learning, where symmetry and smoothness constraints are incorporated into reinforcement learning. The symmetry constraint promotes coordinated locomotion and consistent velocity tracking performance, while the smoothness constraint reduces jerky actions and generates stable velocity performance. The control policy is zero-shot deployed on the Unitree AlienGo. It demonstrates a tracking error of less than 0.084 m/s over the entire velocity range and robust locomotion on natural terrain. We also test our controller by integrating it to a pedestrian tracking framework and prove its capability of trajectory following and long-term reliablitiy.

not-yet-known not-yet-known not-yet-known unknown High monetary investments and information asymmetry of non-monetary investment make the supply of green agricultural products unable to meet market demand. Application of Blockchain of Things (BoT) has provided a possible solution. This article constructs a supply chain composed of an enterprise, a bank, and a farmer with limited funds, and studies the value of BCT in green agricultural supply chain financing. Two aspects of changes after the introduction of BCT are considered: traditional purchase order financing (TPOF) requires fixed assets as collateral to obtain a loan, while BoT-based purchase order financing (BPOF) can use liquid assets; under the asymmetric information of non-capital investment efficiency, TPOF use price as the transmission signal, but BPOF uses farmer’s greening investment. The results show that under information symmetry, BPOF allows the farmer with high financing needs to participate in the green agricultural supply chain if the price of traditional agricultural products is high, and redistributes the profits if the price of traditional agricultural products is moderate and the financing needs is low. When there is uneven information, BPOF can help the enterprise by sharing information. This article also shows that TPOF is better than BPOF when traditional agricultural product price is very low.

not-yet-known not-yet-known not-yet-known unknown Born on June 1, 1940, in Lyon, Jean-François Muller studied in Autun before entering the Collège Stanislas in Paris and obtaining an engineering degree from the Strasbourg Higher National School of Chemistry (ENSCS), where he met his wife, Daniel. After graduating in 1965, he joined the Faculty of Science at the University of Metz at its foundation in 1970, as an Assistant Professor of Organic Chemistry. There, he prepared his doctorate in physical sciences, focusing on peri-series cyclisation of naphthalenic and benzo(b)thiophenic compounds (doctorat es-science of physics, 1973). After a first post-doctorate in chemistry-physics at the University of Basel (Switzerland) (1974-1975) and a second one in photochemistry at the University of Utah (USA) (1976-1977), he has specialised and became involved in the development of mass spectrometry in France.

Spacecraft discharge time constants are calculated from measurements of electron differential flux before and during operation of an ionospheric sounding radar. Determining these time constants provides insight into how the operation of a sounding radar affects the surrounding plasma’s interaction with the spacecraft. The analysis is enabled by the fixed-frequency operation mode of a sounding radar which enhances resonant interaction with the ambient plasma. This mode’s effect on measured energy spectra of ion and electron fluxes is described. Measurements of electron fluxes disturbed by radar operation serve as input to a model of spacecraft discharge for calculating capacitive discharge time constants. A case study using electron fluxes measured at Mars yields discharge time constants in the range 0.6-0.8 ms and reveals that a residual potential around −4 V remains on the spacecraft long after radar operation ceases. The minimum spacecraft potential cannot be determined with these data and model due to the narrow energy range of electrons in the ambient plasma.

The occurrence variability on a day-to-day basis of severe S4 scintillation and Range-Spread F (RSF) which are {the manifestations of} the most robust dynamical Spread F phenomenon in the nighttime equatorial-low-latitude ionosphere, remains intriguing to date. The complex nature of Large-to-Meso-Scale-Wave-Structure (LSWS) that results from the two most important determining factors, Large-Scale Pre-Reversal Electric Field (PREF) and Meso-Scale wave electric field, poses a severe obstacle to the short-term forecasting of S4-RSF. The present study aims to investigate the competing role of the two factors by presenting S4-RSF events that occur during the summer months of 2021-2022 over the Equatorial region of Brazil. The scintillation index (S4) and Total-Electron-Content (TEC) from the GNSS network and ionospheric drift measurements from digisonde found more frequent occurrences of severe S4-RSF during December 2021 than in January 2022. The measurements detect LSWS in both months, though December reveals phase propagation of TEC and drift oscillations for longer horizontal distances and altitudes. The strength variability of S4-RSF is understood by conducting the numerical simulation of Collisional-Interchange Instability (CII). In line with the observations, the simulation shows the stronger and faster Equatorial Plasma Bubble (EPB) formations from the combined action of PREF and phase-coherent mesoscale electric field. Despite the comparatively weak PREF, the stronger S4-RSF activities highlight the role of mesoscale wave electric field in defining the strength of S4-RSF.

Breast cancer remains a pervasive global health issue, affecting diverse populations worldwide and posing significant challenges for public health. As the most common cancer among women worldwide, breast cancer also occasionally affects men. The gravity of the disease and the urgency for effective treatment are underscored by its high mortality rate. Traditionally, breast cancer detection relies on human radiologists who analyze mammograms to classify breast masses and subsequently provide treatment recommendations based on the diagnostic assessments. However, the exclusive reliance on human radiologists for breast mass classification can lead to diagnostic inconsistencies, human errors, and delays in timely care, potentially resulting in missed or incorrect diagnoses and exacerbating healthcare disparities. Enhancing the mammogram classification process through the development and implementation of computer-aided diagnosis (CAD) systems can address these challenges. By improving the accuracy, efficiency, and consistency of CAD systems, the likelihood of human error is reduced, and a standardized approach to analysis is provided, offering crucial support to radiologists, particularly in complex cases. This article introduces a novel approach, termed MammoDenseInvoNet, which leverages the combined power of deep convolutional neural networks (CNNs) and involution neural networks (INNs) for precise and automated classification of breast masses. The study explores three distinct mammography datasets: the Digital Database for Screening Mammography (DDSM), the King Abdulaziz University Breast Cancer Mammography Dataset (KAU-BCMD) and a privately collected dataset named PioneerMammoBD. The images from these datasets are categorized into benign and malignant classes. The proposed architecture employs the DenseNet169 model as a feature extractor, incorporating a custom involution layer that adaptively generates kernels based on input features. The robustness of the MammoDenseInvoNet model is evaluated through various performance metrics and experiments, where it notably surpasses other models, achieving an impressive average accuracy of 97.58%. Specifically, the individual highest accuracies for the PioneerMammoBD, DDSM, and KAU-BCMD datasets are 98%, 100%, and 97%, respectively.

Nucleotide-binding leucine-rich repeat (NLR) genes play a critical role in plant effector-triggered immunity (ETI) against pathogen invasion. However, the regulatory mechanisms governing NLR expression and functional dynamics, particularly in head-to-head NLR gene pairs, remain poorly understood. In this study, we investigated the regulatory mechanisms, subcellular localization, and functional pathways associated with Pik-H4 gene pair. Bidirectional Pik-H4 promoter (P Pik-H4) strengths were found across the whole plants and exhibited co-expressed patterns in tissues and cells, and the P Pik-H4 activity was up-regulated in vascular bundles during blast fungus invasion. Additionally, altering the co-expression of Pik1-H4 and Pik2-H4 via overexpression in rice or Nicotiana benthamiana did not compromise the immune response. Promoter analysis identified two minimal promoter regions that are essential for bidirectional transcription, and mutagenesis of the bidirectional TATA box confirmed its role in gene regulation. This dual-function promoter coordinates Pik-H4 expression in both directions, a regulatory innovation previously unreported in NLR-mediated immunity. In planta subcellular localization revealed Pik 1-H4 relocates to vesicles, indicating its role in effector recognition, while Pik 2-H4 predominantly accumulated in the nucleus. These new discoveries of Pik protein extended putative immune function of NLR pairs. Transcriptome analysis demonstrated that Pik-H4-mediated resistance induces significant transcriptome reprogramming between 12- and 24-hours post-inoculation. In summary, these findings provide novel insights into the regulatory complexity and functional divergence within NLR bidirectional gene pairs in response to pathogen invasion.

Objective. Extended length of stay (eLOS) has been contributing to the reduction of hospital resources and patient satisfaction in inpatient psychiatry. With the mean LOS in psychiatry being almost twice the length of other medical conditions, our study aims to identify factors that are associated with eLOS in order to make quality improvements. Methods. This was a retrospective, observational study. A total of 17,257 patients admitted into the inpatient psychiatry unit at Queen’s Medical Center between January 2019 and December 2023 in Honolulu, Hawaii were included in this analysis. Descriptive analysis was used to identify associations of eLOS between various clinical and demographic variables. Results. The strongest sociodemographic predictors of LOS came from: sex (p=0.005), age (p=<0.0001), employment (p=<0.0001), race (p=<0.0001), marital status (p=0.03), homelessness (p=0.006), and having access to Medicaid and/or Medicare (p=<0.0001). The following clinical predictors revealed a strong relationship with LOS: establishment of a PCP (p=<0.0001), diagnosis of intellectual disability (p=0.002), low CSSRS (p=<0.0001), the non-use of illicit drugs, cannabis, ethanol, and the rising number of prescribed psychotherapeutics per patient (p=<0.0001). Conclusion. Identifying strong predictors of eLOS in the United States still remains under-investigated. Enhancing our understanding about factors associated with eLOS will lead to improved treatment planning and resource allocation for inpatient psychiatric hospitalization.

Objective: Many people with Anorexia Nervosa experience ambivalence and impoverished motivation to change, yet current motivation enhancing interventions require improvements. Chairwork is a collection of therapeutic methods that incorporate movement and dialogue between chairs to elicit change. The “future selves” chairwork intervention (FSCI) is a novel chairwork task that aims to increase motivation by enacting and interacting with future ‘non-recovered’ and ‘recovered’ version of the self in different chairs. Method: Nine people living with Anorexia Nervosa completed the FSCI and were interviewed about their experience of the task. An interpretative phenomenological analysis was conducted, using change process research methods to explore acceptability, feasibility, and associated change processes. Results: The following Group Experiential Themes (GETs) were identified: ‘Delivery and Task factors’, ‘Motivation towards a demanding recovery journey’, ‘Intense and strange emotions led to realisations’ and ‘Living as the future self”. Conclusions: The findings suggest that FSCI is acceptable and feasible, although more research would

Prolonged loneliness can be detrimental to both mental and physical health. However, variability in how individuals respond to loneliness can shape health outcomes. Here, we explored whether loneliness is related to perceptions of support and strain given in family and friend relationships. Specifically, we assessed whether resting parasympathetic nervous system (PNS) activity, a marker of emotion regulation and flexible adaptation, moderates self-evaluation of support and strain given. Participants were from the Midlife Development in the US (MIDUS) dataset who had measures of loneliness, perceived support given and perceived strain given in relationships, and resting PNS activity. Loneliness was associated with decreased support and increased strain given in both family and friend relationships. Resting parasympathetic activity moderated the relationship between loneliness and strain given to family, with lower PNS activity associated with a stronger relationship. These findings contribute to our understanding of how loneliness shapes social perception.

This paper addresses the bipartite consensus problem of general linear multi-agent systems, where cooperation and competition exist among agents. First, a fully distributed adaptive double dynamic event-triggered control protocol is designed under directed signed graphs. By combining adaptive technique with a double dynamic event-triggered mechanism, this protocol not only avoids reliance on global information of the system but also ensures intermittent communication and control signal updating. Secondly, the proposed control protocol is analyzed using graph theory and Lyapunov stability theory, demonstrating that it enables the multi-agent system to achieve bipartite consensus and proving the absence of Zeno behavior in the system. Due to the construction of two internal dynamic variables that couple system information, and the separate design of dynamic event-triggered mechanisms for communication and controller update based on these two variables, the proposed control algorithm has significant advantages in reducing communication overhead among agents and computational costs for the controllers. Finally, numerical simulations further validate the feasibility and effectiveness of the theoretical results.

Note: Due to the specific surface area and high surface energy, the multiplied nanoparticles stick together and form a mass. This phenomenon leads to the loss of properties resulting from the small size of these particles.To prevent the accumulation of nanoparticles in the synthesis stage, stabilizers are used. Usually, two types of methods, electrostatic and spatial drift, are used to stabilize nanoparticles. In the first method, ions are used to stabilize nanoparticles. These ions are absorbed into the particles and form an electrically charged layer around the nanoparticles, and as a result of the molecular drift of the produced nanoparticles, due to the specific surface area and high surface energy, they stick together and form a mass. This phenomenon leads to the loss of properties resulting from the small size of these particles. To prevent the accumulation of nanoparticles in the synthesis stage, stabilizers are used.

Molecular modification methods can directly eliminate the influence of unstable groups on the properties of natural ester insulating oils. In order to verify the modification effect, we will explore the microscopic mechanism of the difference in the properties of insulating oils before and after the structural modification from the atomic molecular level. The TME-C 10 and GT molecules of electronic structure properties have been calculated using density-functional theory, such as molecular orbital and density of states, electronic excitation features, electron affinity potentials, electron ionization energies, UV/Vis spectrum, molecular vibration and IR spectrum and so on. Additionally the polarity profiles and dielectric strengths of the two molecular systems with changes in electric field were also discussed. The results indicate that the electronic behavior of the TME-C 10 molecule is related to the ester group in its structure, while the GT molecule is more affected by the unsaturated C=C double bond, which leads to the two molecular systems having different electronic transitions, and , respectively. The HOMO orbital energy levels, electron transition energies, and ionization energies of the GT molecule are smaller than those of the TME-C 10 molecule are also due to the influence of the different functional groups. Under the influence of the ester group, it is found that the dipole moment of TME-C 10 molecule is larger in the basal state in the vibration analysis, and further comparing and analyzing the molecular polarity of the two systems under the action of the external electric field, it is found that GT molecules with smaller dipole moments in the basal state are more easily polarized with the change of the electric field strength, and it is possible to judge that the dielectric properties of the modified TME-C 10 are better in combination with the relevant calculated parameters.

This article investigates the methodological advancements and challenges in climate modelling, focusing on hydrological projections and their application in adaptive water governance frameworks. By exploring the evolution of the Coupled Model Intercomparison Project (CMIP), the paper highlights key advancements, including improved representations of biogeochemical cycles, regional variability, and advanced parameterizations. Specific emphasis is placed on microphysical processes that are critical to precipitation formation but remain major sources of uncertainty in hydrological projections. The article emphasizes the need to address these uncertainties through refined modelling methodologies and the incorporation of robust observational data. Experimental studies and advanced tools, including numerical simulations and machine learning emulators, are essential for linking fine-scale dynamics with global models and enhancing predictions of hydrological feedbacks. The synthesis highlights practical applications, emphasizing how refined models and a precise understanding of uncertainties support adaptive and sustainable water management, particularly in regions under acute stress. This interdisciplinary approach bridges technical precision and governance, providing actionable pathways for addressing global water challenges.

Cardiomyopathies represent a diverse group of myocardial disorders characterized by structural and functional abnormalities in the absence of significant coronary artery disease or other primary causes. This review highlights the diagnostic and prognostic value of cardiac magnetic resonance and computed tomography in the assessment of cardiomyopathies. While echocardiography remains the first-line imaging modality, CMR and CCT offer superior tissue characterization, morphological assessment, and functional evaluation, crucial for phenotyping cardiomyopathies into hypertrophic, dilated, restrictive, arrhythmogenic, and non-dilated left ventricular subtypes. For hypertrophic cardiomyopathy, CMR enables precise identification of fibrosis, hypertrophy distribution, and risk stratification for sudden cardiac death. CMR is pivotal in identifying phenocopies, like cardiac amyloidosis and Anderson-Fabry disease, and differentiating between pathological and physiological remodeling in athlete's heart. For dilated cardiomyopathy, late gadolinium enhancement, T1 mapping, and extracellular volume measurements aid in distinguishing etiologies and predicting adverse outcomes. In arrhythmogenic right ventricular cardiomyopathy CMR demonstrates superior sensitivity for detecting structural abnormalities in the right ventricle, and the presence of fibrosis, which is associated with arrhythmic risk. CCT main roles are excluding coronary artery disease and complementing CMR. This review proposes a diagnostic pathway integrating multimodality imaging for clinical management in cardiomyopathies.

not-yet-known not-yet-known not-yet-known unknown Background and aims: The assessment of left ventricular (LV) outflow velocity time integral (LVOT-VTI) has gained favor in the stratification of patients with heart failure (HF). We evaluated the prognostic significance of LVOT-VTI compared with the commonly used indices of LV outflow: cardiac index (CI) and stroke volume index (SVI), their reproducibility and cut-off values. Methods and results: 424 outpatients diagnosed with HF and LV systolic dysfunction (LV ejection fraction <50%) underwent a Doppler echocardiographic examination, including the assessment of CI, SVI and LVOT-VTI. The Bland-Altman analysis showed LVOT-VTI the most reproducible outflow index. The study follow-up duration was 3.5 years (interquartile range 1.6 to 6.5), at the end of which there were 94 cardiovascular deaths (29%). Cox regression univariate analysis showed that LVOT-VTI was the most predictive of the study end-point. The ratio of tricuspid annular displacement-to-pulmonary artery systolic pressure (TAPSE/PASP) (p<0.0001), LVOT-VTI (p=0.0001) and end-systolic volume index (p=0.0006) independently predicted the study end-point. At Receiver-operating characteristic (ROC) analysis, LVOT-VTI <12.0 cm had the best sensitivity and specificity for predicting cardiovascular mortality. Reduced LV EF (p=0.0011), raised BNP levels (p=0.0053) and high LV filling pressure (p=0.044) were associated with low LVOT-VTI in multivariate logistic regression analysis. Patients with low LVOT-VTI and TAPSE/PASP<0.32 mm/mmHg exhibited the worst prognosis on Kaplan-Meier survival curves (p<0.0001). Conclusions. A LVOT-VTI < 12.0 cm represents the best predictor of the cardiovascular outcome and proved the most reproducible index of LV forward flow in patients with chronic HF and systolic dysfunction.

not-yet-known not-yet-known not-yet-known unknown Left main coronary artery atresia (LMCAA) is a rare congenital coronary anomaly and sometimes presents with non-specific clinical symptoms that make the diagnosis challenging. We are presenting an interesting case that required multimodality imaging to establish the diagnosis.

This review focuses on the key non-invasive cardiac imaging techniques, including cardiac CT and MRI, and highlights essential publications pertinent to clinicians managing ischemic and non-ischemic cardiomyopathy. Cardiac computed tomography (CT) Provides an anatomical assessment that offers superior diagnostic accuracy compared to functional tests. It is a valuable tool for understanding the impact of non-obstructive coronary artery disease on patient outcomes. Additionally, cardiac CT is beneficial in defining the morphology of vulnerable plaque, which closely aligns with IVUS findings. It also demonstrates safety advantages, including reduced contrast volume and radiation dose and lower risk of contrast-induced nephropathy when used in post-CABG besides conventional coronary angiograms. Cardiac MRI provides invaluable insight into the MI size and microvascular obstruction, critical for understanding a patient’s prognosis. The assessment of scar tissue with CMR has become an essential tool for risk stratification and informs therapeutic decisions regarding the implantation of ICD.

Cardiac tumors are rare but should be considered in differential diagnoses for cardiovascular masses. This case describes a 62-year-old woman with multiple comorbidities presenting with neurological symptoms and a cardiac mass identified on imaging. The tumor, confirmed as a papillary fibroelastoma, was surgically removed due to embolic risk. Imaging modalities including echocardiography and cardiac MRI aided in diagnosis and surgical planning, leading to successful excision without complications. This case underscores the importance of recognizing rare cardiac tumors like papillary fibroelastoma, which can cause significant embolic events, necessitating prompt diagnosis and intervention to prevent further complications.

Abstract: Note :  Noise is a low-frequency random oscillation that occurs in many nanocommunication devices, including nanoelectronics, the environment, and organisms.  Noise can obscure signals, so it is often omitted from electronic and radio transmissions. Introduction: The origin of noise in nanoelectronics is currently mostly in carbon nanotubes based on the nanocommunicative functions and the structure of graphene particles in nanotubes in interaction for nanocommunication purposes by (nanoparticles) in single-walled carbon nanotubes (CNTs) and multi-walled CNTs. Nanomaterials with high surface-to-volume ratio are very attractive for noise generated by nanoelectrons because they are very sensitive to changes in their surface.  A representative material of this type is carbon nanotubes, which are rolled sheets of hexagonal graphene lattice, which are only one carbon atom thick. Simple nanocommunication devices consist of a carbon nanotube that forms two electrodes.  These magnetic communication particles are exposed to different large molecules, causing some of them to bind to the surface of the carbon nanotube. In nanocommunications,  different molecules give off unique acoustic signals related to the properties of the molecules.  The strength of the interaction between the carbon nanotubes and the molecules arises from the noise signals. In nanocommunicators  interacting with carbon nanotube-based electronic nanoparticles,  the signal generated by the carbon nanotube device is modified following the absorption of specific single molecules. This is because the absorbing molecule creates a trap state in the carbon nanotube, which causes it to conduct. This means that carbon nanotube-based nanocommunicators are very sensitive. They can  detect an unprecedented amount of single molecules.  The ability to characterize single molecules using highly sensitive nanoelectronics is an exciting prospect in the field of sensors, especially for neural and biosensor applications. The use of acoustic signals to detect molecular activity ((interaction) or (active orbital)) is attractive. In nanocommunicators and interacting with carbon nanotube-based electronic nanoparticles, the sensitivity of signal detection may be increased by the generation of controllable noise.  These carbon nanotube-based nanocommunicators demonstrate that it is possible to detect single molecules through their unique noise particles in current nanocommunicator signals.  Improved knowledge about the molecular origin and interaction of noise with carbon nanotube-based electronic nanoparticles should lead to the development of electronics that use noise to improve their performance rather than degrade it.

Preemptive therapy (PET) is safe and effective in controlling Cytomegalovirus (CMV) infection after pediatric liver transplantation (LT) and allows to observe the kinetics of quatitative CMV-DNA viral load till it reaches the treatment thresholds. While an early detection of low-to-moderate CMV-DNA levels may not indicate active viral replication, awaiting the viral load to exceed the treatment threshold may lead to viremic breakthroughs and CMV disease. We assessed the capacity of quantitative CMV-RNA (UL21.5 mRNA) to identify active viral replication, and its accuracy in predicting the need for PET in LT children. One-hundred and forty-four comparative quantitative CMV-RNA and CMV-DNA determinations were obtained from 12 children followed prospectically for 6 months after LT. Of 52 CMV-DNA-positive specimens, 17 (32%) were also CMV-RNA-positive, while CMV-RNA was undetectable in CMV-DNA-negative specimens. All children needing PET or treated for CMV disease had early detectable CMV-RNA, peaking simultaneously to CMV-DNA (median CMV-DNA: 65,906 cp/mL; median CMV-RNA: 767 cp/mL); conversely, none of those with persistently low DNAemia proved CMV-RNA-positive. In this first pilot study, CMV-RNA had 100% sensitivity and specificity in predicting the need for PET after pediatric LT. The early detection of CMV-RNA marks significant CMV infection/reactivation, thus allowing to avoid unnecessary antiviral treatment.

not-yet-known not-yet-known not-yet-known unknown Background: Following the COVID-19 pandemic, there are many chronically ill Long COVID (LC) patients with different symptoms of varying degrees of severity. The pathological pathways of LC remain unclear until recently. This makes identification of path mechanisms and exploration of therapeutic options an urgent challenge. There is an apparent relationship between LC symptoms and impaired cholinergic neurotransmission. Methods: This paper reviews the current literature on the effects of blocked nicotinic acetylcholine receptors (nAChRs) on the main affected organ and cell systems and contrasts this with the unblocking effects of the alkaloid nicotine. In addition, mechanisms are presented that could explain the previously unexplained phenomenon of post-vaccination syndrome. The fact that not only SARS-CoV-2 but numerous other viruses can bind to nAChRs is discussed under the assumption that numerous other post-viral diseases and autoimmune diseases (ADs) may also be due to impaired cholinergic transmission. A case report presents the (-)-[ 18F]Flubatine whole-body positron emission tomography (PET) imaging of cholinergic dysfunction in a LC patient and the significant neurological improvement before and after low-dose transcutaneous nicotine (LDTN) administration. Results: The literature provides a wealth of evidence that LC is adequately described based on impaired nAChR function in the cells of the human body. After 10 days of transcutaneous nicotine administration, no persistent neuropathology was detected in the patient, which was accompanied by a significant increase in free ligand binding sites (LBS) of nAChRs in (-)-[ 18F]Flubatine PET. Conclusions: In conclusion, based on current knowledge, LDTN appears to be a promising and very safe procedure with no expected long-term harm.

The International Union for Conservation of Nature (IUCN) has recently developed a global ecosystem typology (IUCN typology) based on the functional characteristics of the ecosystems. However, its low spatial resolution and lack of recognition of certain categories in Japan limits effective and precise habitat analysis for global comparisons. In this data paper, we used the Japanese vegetation map provided by the Ministry of Environment (MOE) to align Japanese vegetation categories with the IUCN typology scheme up to Level 4, Regional subgroups, developing a correspondence table and a high-resolution spatial dataset focusing on terrestrial ecosystems. In addition, we also integrated the land-use classification developed by the National Institute for Environmental Studies. The dataset includes tables describing the integration of Japanese habitat classification with IUCN typology from Level 1 to 4 (Realms, Biomes, Ecosystem functional groups, Regional subgroups), explanation of land-use categories, and the main corresponding table as well as high-resolution integrated GIS data. This integration supports both global and local studies, with the tables including English and Japanese names of the classification tree.

Climate change and range shift during glacial cycles in the Quaternary resulted in disjunct plant distributions. Geographic genetic structure can imply historical processes that formed disjunct distributions. Betula dahurica Pallas is common in continental northeast Asia but is disjunctly distributed in the Japanese archipelago. To explore the formation process of its disjunct distributions, genome-wide single nucleotide polymorphism (SNP) genotypes, chloroplast (cp) DNA sequences, and leaf morphology were investigated in 10 populations in three regions, Primorsky, Hokkaido, and Honshu. Frequency distributions of the ratio of SNP reads suggested that most individuals in the three regions were octaploid, except for some hexaploid or heptaploid individuals found in Hokkaido and Honshu. SNP genotypes of putative octaploid individuals indicated that Honshu populations were diverged from Primorsky and Hokkaido populations. This genetic divergence was relatively small (0.010 < FST < 0.035) but larger than those between Primorsky and Hokkaido (FST < 0.010) and within regions (FST < 0.008). The effective population size in Honshu was smaller than that in Primorsky and Hokkaido. CpDNA (trnL–trnF) sequences found in Honshu were different from those found in Primorsky and Hokkaido. The variations in leaf size and shape were overlapped among the ploidy levels and among the populations. The findings of geographic genetic structure suggest a plausible process that formed the disjunct distributions, which includes the isolation of persistent populations in Honshu and the post-glacial migration from continental northeast Asia to Hokkaido directly or through Sakhalin.