Miracle-dz/UniFAR-FTUs huggingface dataset:
A methodology to abridge microdosimetric distributions without a significant loss of the spectral information needed for the RBE computation in carbon ion therapy

Abstract Background In order to compute the relative biological effectiveness (RBE) of ion radiation therapy with the Mayo Clinic Florida microdosimetric kinetic model (MCF MKM), it is necessary to process entire microdosimetric distributions. Therefore, a posteriori RBE recalculations (i.e., for a different cell line or another biological endpoint) would require whole spectral information. It is currently not practical to compute and store all this data for each clinical voxel. Purpose To develop a methodology that allows to store a limited amount of physical information without losing accuracy in the RBE calculations nor the possibility of a posteriori RBE recalculations. Methods Computer simulations for four monoenergetic 12C ion beams and a 12C ion spread‐out Bragg peak (SOBP) were performed to assess lineal energy distributions as a function of the depth within a water phantom. These distributions were used in combination with the MCF MKM to compute the in vitro clonogenic survival RBE for human salivary gland tumor cells (HSG cell line) and human skin fibroblasts (NB1RGB cell line). The RBE values were also calculated with a new abridged microdosimetric distribution methodology (AMDM) and compared with the reference RBE calculations using the entire distributions. Results The maximum relative deviation between the RBE values computed using the entire distributions and the AMDM was 0.61% (monoenergetic beams) and 0.49% (SOBP) for the HSG cell line, while 0.45% (monoenergetic beams) and 0.26% (SOBP) for the NB1RGB cell line. Conclusion The excellent agreement between the RBE values computed using the entire lineal energy distributions and the AMDM represents a milestone for the clinical implementation of the MCF MKM.
An unusual right atrial myxoma triggering presumed takotsubo syndrome in a 97-year-old female

Summary A 97-year-old female was admitted to the emergency department of our hospital due to paroxysmal nocturnal dyspnea and chest pain. At the hospital admission, the patient manifested transient psychomotor agitation and dysarthria. On physical examination, blood pressure was 115/60 mmHg and pulse 96 b.p.m. On blood tests, troponine I was 0.08 ng/mL (normal range <0.04 ng/mL). Electrocardiography (ECG) showed sinus rhythm and ST segment elevation in both inferior and anterior leads except in lead V1. Transthoracic echocardiography (TTE) revealed a right atrial multilobulated, hypermobile, echogenic cauliflower mass (maximum size of 5 cm × 4 cm), which was attached to the tricuspid lateral annulus with a short stalk (Figure 1A). The right atrial mass, which had filiform extremities and was found to prolapse through the tricuspid valve into the right ventricle, was ascribed to a peduncolated myxoma. Its motion was very rapid and uncoordinated, with increased peak antegrade velocity (Vmax = 35 cm/s), as precisely measured by pulsed wave tissue Doppler imaging (PW-TDI) (Figure 1B). Estimated left ventricular ejection fraction (LVEF) was normal (60%), and no significant valvulopathy was detected. Finally, a bulging of the interatrial septum with right-to-left shunt, through a patent foramen ovale (PFO), was observed by using colour Doppler (Figure 1C). Acute ischaemic lesions were excluded by brain computed tomography scan.
Terahertz Meets AI: The State of the Art

Terahertz (THz) is a promising technology for future wireless communication networks, particularly for 6G and beyond. The ultra-wide THz band, ranging from 0.1 to 10 THz, can potentially address the limited capacity and scarcity of spectrum in current wireless systems such as 4G-LTE and 5G. Furthermore, it is expected to support advanced wireless applications requiring high data transmission and quality services, i.e., terabit-per-second backhaul systems, ultra-high-definition streaming, virtual/augmented reality, and high-bandwidth wireless communications. In recent years, artificial intelligence (AI) has been used mainly for resource management, spectrum allocation, modulation and bandwidth classification, interference mitigation, beamforming, and medium access control layer protocols to improve THz performance. This survey paper examines the use of AI in state-of-the-art THz communications, discussing the challenges, potentials, and shortcomings. Additionally, this survey discusses the available platforms, including commercial, testbeds, and publicly available simulators for THz communications. Finally, this survey provides future strategies for improving the existing THz simulators and using AI methods, including deep learning, federated learning, and reinforcement learning, to improve THz communications.
Ownership changes of Japanese affiliates in China: lessons from the perspective of growth options exercising

Abstract Based on Real Options Theory and taking the perspective of growth options exercising, as well as Tobit model, this paper explores how Japanese enterprises adjust ownership structures in their affiliates as a portfolio in China. Empirical results show that: both demand uncertainty and industry growth opportunity in China enhance Japanese enterprises’ ownership expansion in their affiliates as a real option portfolio; Industry competition and capability to control and coordinate the affiliates strengthen the roles of uncertainty and industry growth opportunity play in enhancing Japanese enterprises’ ownership expansion within these affiliates as a portfolio. This paper enriches studies on growth options exercising and illustrates that the logic for real options establishing should not be simply and directly transplanted to real options exercising indiscriminately. Conclusions derived from this paper are of great significance for MNEs’ growth option exercising by adjusting ownership structures in their affiliates as a portfolio within a host country according to changes in the focal host market.
Kinetics and Mechanism of Camptothecin Release from Transferrin-Gated Mesoporous Silica Nanoparticles through a pH-Responsive Surface Linker

Stimuli-responsive nanomaterials have emerged as a promising strategy for inclusion in anticancer therapy. In particular, pH-responsive silica nanocarriers have been studied to provide controlled drug delivery in acidic tumor microenvironments. However, the intracellular microenvironment that the nanosystem must face has an impact on the anticancer effect; therefore, the design of the nanocarrier and the mechanisms that govern drug release play a crucial role in optimizing efficacy. Here, we synthesized and characterized mesoporous silica nanoparticles with transferrin conjugated on their surface via a pH-sensitive imine bond (MSN-Tf) to assess camptothecin (CPT) loading and release. The results showed that CPT-loaded MSN-Tf (MSN-Tf@CPT) had a size of ca. 90 nm, a zeta potential of −18.9 mV, and a loaded content of 13.4%. The release kinetic data best fit a first-order model, and the predominant mechanism was Fickian diffusion. Additionally, a three-parameter model demonstrated the drug-matrix interaction and impact of transferrin in controlling the release of CPT from the nanocarrier. Taken together, these results provide new insights into the behavior of a hydrophobic drug released from a pH-sensitive nanosystem.
Generalized Approach to Aeroelastic CFD Time Simulation of Morphing Flight Vehicles

A new approach for time-domain CFD-based simulation of morphing flight vehicles, taking into account multi-body dynamics and aeroelastic effects due to structural flexibility, is presented. The vehicle consists of a number of components interconnected by actuators and contact constraints. Due to aerodynamic, inertial and actuation loads the overall structure undergoes large-displacement morphing. The simulation assumes that each component experiences large rigid-body displacements and small elastic deformations. The small displacements are defined for each component as a linear combination of its own freefree vibration modes generated with fictitious masses loading the interface degrees of freedom. Modal coupling of the component modes with compatibility constraints at the interface points yields a generalized-coordinate nonlinear matrix equation of motion that is embedded into the time-accurate CFD code. The vector of generalized forces includes aerodynamic forces from the CFD solution, inertial forces due to modal accelerations and relative component rotations, and actuation forces. The time derivations of the constraint equations are taken into account to allow large and fast relative rotations of the different components. These derivatives yield non-symmetric structural damping and stiffness matrices that affect the numerical integration process. The computational process is demonstrated for a two-wings-and-body configuration. The wings are rotated rapidly from parallel position along a fuselage to perpendicular position. The morphing simulation demonstrates a robust and stable computational process that exhibits significant aeroelastic effects.
Detection of DDoS attack in IoT traffic using ensemble machine learning techniques

A denial-of-service (DoS) attack aims to exhaust the resources of the victim by sending attack packets and ultimately stop the legitimate packets by various techniques. The paper discusses the consequences of distributed denial-of-service (DDoS) attacks in various application areas of Internet of Things (IoT). In this paper, we have analyzed the performance of machine learning(ML)-based classifiers including bagging and boosting techniques for the binary classification of attack traffic. For the analysis, we have used the benchmark CICDDoS2019 dataset which deals with DDoS attacks based on User Datagram Protocol (UDP) and Transmission Control Protocol (TCP) in order to study new kinds of attacks. Since these protocols are widely used for communication in IoT networks, this data has been used for studying DDoS attacks in the IoT domain. Since the data is highly unbalanced, data balancing is done using an ensemble sampling approach comprising random under-sampler and ADAptive SYNthetic (ADASYN) oversampling technique. Feature selection is achieved using two methods, i.e., (a) Pearson correlation coefficient and (b) Extra Tree classifier. Further, performance is evaluated for ML classifiers viz. Random Forest (RF), Naïve Bayes (NB), support vector machine (SVM), AdaBoost, eXtreme Gradient Boosting (XGBoost) and Gradient Boosting (GB) algorithms. It is found that RF has given the best performance with the least training and prediction time. Further, it is found that feature selection using extra trees classifier is more efficient as compared to the Pearson correlation coefficient method in terms of total time required in training and prediction for most classifiers. It is found that RF has given best performance with least time along with feature selection using Pearson correlation coefficient in attack detection.
History, Current Techniques, and Future Prospects of Surgery to the Sellar and Parasellar Region

Simple Summary This paper provides a definition of the sella, a description of common pathologies affecting the region, and an overview of the historical development of surgical approaches, as well as the advantages of techniques that are commonly used today. Abstract The sellar and parasellar region can be affected by diverse pathologies. The deep-seated location and surrounding critical neurovascular structures make treatment challenging; there is no singular, optimal approach for management. The history and development of transcranial and transsphenoidal approaches by pioneers in skull base surgery were largely aimed at treating pituitary adenomas, which are the most common lesions of the sella. This review explores the history of sellar surgery, the most commonly used approaches today, and future considerations for surgery of the sellar/parasellar region.
Species-level classification of mangrove forest using AVIRIS-NG hyperspectral imagery

ABSTRACT Species-level classification of mangroves provides important inputs for conservation, rehabilitation and understanding of ecosystem functions. The hyperspectral sensor, Airborne Visible InfraRed Imaging Spectrometer-New Generation (AVIRIS-NG), holds promises for species-level discrimination by virtue of its coverage across a wider spectrum at very high spatial resolution. Using the continuum removal (CR) technique and absorption band depth (ABD), this study applied Random Forest (RF) model to classify the distribution of three species (Heritiera fomes, Excoecaria agallocha and Avicennia officinalis) and two of their combinations (Heritiera fomes-Excoecaria agallocha and Avicennia officinalis-Excoecaria agallocha). The classified map demonstrated good accuracy (overall accuracy = 88%; kappa coefficient = 0.84) using ABD as an independent variable. The important wavelengths (972, 1172, 1177 nm) identified for mangrove species discrimination correspond to water absorption bands. This characteristic may be replicated for species-level classification of other mangrove forests with similar species.
Estimates of Emission-Region Locations of Fermi Flat-Spectrum Radio Quasars

We study the locations of emission regions through modelling the quasi-simultaneous multi-frequency spectral energy distributions of 21 Fermi flat spectrum radio quasars (FSRQs) in the frame of a multicomponent one-zone leptonic model. In our calculations, we take the detailed broad line region (BLR) structure into account and discuss the effect of the uncertainty of the BLR structure on constraining the location of the emission regions for each FSQR, meanwhile we also include both the internal and external absorptions. Our results indicate that (1) the contribution of external Compton-BLR component is important to γ-ray emission, and the energy density of external target photon fields depends on the location of the emission region, which can be derived through reproducing the observed γ-ray emission, and (2) the emission regions of FSRQs with relative low accretion disk luminosity lie in the region of 7.9× 10 – 1.3× 10 cm (300 – 4300 Schwarzschild radii) from central black hole, and for FSRQs with high accretion disk luminosity, the emission regions locate in the larger region of 2.6×1017 – 4.2×1018 cm (300 – 5600 Schwarzschild radii).
Event-triggered feedback for power allocation in wireless networks

Transmission power control constitutes a core feature required to achieve a desired quality of service in wireless networks. A practical implementation calls on the intuition of using limited resources, only when are strictly required. Thus, the appeal of an event-triggered scheme arises naturally over more traditional, but less efficient, periodic time-triggered control solutions. Motivated by these ideas, the authors present here a power allocation strategy based on an event-triggered transmission (ETT) to reduce the feedback signalling in the network. The power allocation under ETT is based on a nominal control that guarantees internal stability and performance. Hence, if the feedback signalling does not change significantly from the previous sample, no feedback transmission is assigned to reduce bandwidth usage. Two schemes are employed to define the ETT while preserving closed-loop stability: a piecewise quadratic Lyapunov argument and a perturbed linear system approach. These two approaches establish a trade-off between complexity and conservativeness. The power allocation under ETT was thoroughly evaluated under two nominal control schemes to establish a relation between performance and feedback reduction.
Continuous Mid-Infrared Star Formation Rate Indicators

Abstract We present continuous, monochromatic star formation rate (SFR) indicators over the mid-infrared wavelength range of 6–70 μm. We use a sample of 58 star forming galaxies (SFGs) in the Spitzer-SDSS-GALEX Spectroscopic Survey (SSGSS) at z<0.2, for which there is a rich suite of multi-wavelength photometry and spectroscopy from the ultraviolet through to the infrared. The data from the Spitzer infrared spectrograph (IRS) of these galaxies, which spans 5–40 μm, is anchored to their photometric counterparts. The spectral region between 40-70 μm is interpolated using dust model fits to the IRS spectrum anchored by Spitzer 70 and 160 μm photometry. Since there are no sharp spectral features in this region, we expect these interpolations to be robust. This spectral range is calibrated as a SFR diagnostic using several reference SFR indicators to mitigate potential bias. Our band-specific continuous SFR indicators are found to be consistent with monochromatic calibrations in the local universe, as derived from Spitzer, WISE, and Herschel photometry. Additionally, in the era of the James Webb Space Telescope this will become a flexible tool, applicable to any SFG up to z∼3.
Does Cognitive–Physical Dual-Task Training Have Better Clinical Outcomes than Cognitive Single-Task Training Does? A Single-Blind, Randomized Controlled Trial

Purpose: At present, there is a controversy regarding the effect of dual-task training on improving the cognitive function of people with mild cognitive impairment (MCI). This study was to develop and verify the effects of the cognitive–physical dual-task training program on the executive function of older adults with MCI. Method: Participants were randomly allocated to the experimental group (EG) receiving cognitive–physical dual-task training (n = 21) or the control group (CG) receiving cognitive single-task training (n = 21). Results: After 16 sessions for 8 weeks, the Korean version of the Executive Function Performance Task (EFPT-K), the Frontal Assessment Battery (FAB), and Korean version of the Instrumental Activities of Daily Living (K-IADL) tests were implemented to assess people’s executive function and instrumental activities during daily living. As the result, there were no significant differences in general characteristics between both groups (p > 0.05). After 16 sessions, the EG showed greater improvements in the EFPT-K (p < 0.05; η2 = 0.133), the FAB (p < 0.001; η2 = 0.305), and the K-IADL (p < 0.01; η2 = 0.221) compared to those of the CG. Conclusion: These results indicate that cognitive–physical dual-task training is clinically beneficial to improve the executive function and daily instrumental activities of older adults with MCI. Cognitive–physical dual-task training is a promising intervention for older adults with MCI.
Oxidative Stress, Cytotoxic and Inflammatory Effects of Azoles Combinatorial Mixtures in Sertoli TM4 Cells

Triazole and imidazole fungicides are an emerging class of contaminants with an increasing and ubiquitous presence in the environment. In mammals, their reproductive toxicity has been reported. Concerning male reproduction, a combinatorial activity of tebuconazole (TEB; triazole fungicide) and econazole (ECO; imidazole compound) in inducing mitochondrial impairment, energy depletion, cell cycle arrest, and the sequential activation of autophagy and apoptosis in Sertoli TM4 cells (SCs) has recently been demonstrated. Given the strict relationship between mitochondrial activity and reactive oxygen species (ROS), and the causative role of oxidative stress (OS) in male reproductive dysfunction, the individual and combined potential of TEB and ECO in inducing redox status alterations and OS was investigated. Furthermore, considering the impact of cyclooxygenase (COX)-2 and tumor necrosis factor-alpha (TNF-α) in modulating male fertility, protein expression levels were assessed. In the present study, we demonstrate that azoles-induced cytotoxicity is associated with a significant increase in ROS production, a drastic reduction in superoxide dismutase (SOD) and GSH-S-transferase activity levels, and a marked increase in the levels of oxidized (GSSG) glutathione. Exposure to azoles also induced COX-2 expression and increased TNF-α production. Furthermore, pre-treatment with N-acetylcysteine (NAC) mitigates ROS accumulation, attenuates COX-2 expression and TNF-α production, and rescues SCs from azole-induced apoptosis, suggesting a ROS-dependent molecular mechanism underlying the azole-induced cytotoxicity.
Cool Things you can do with Lasers

Theoretical and experimental investigations into a variety of laser cooling phenomena are presented. An overview of the history of laser cooling is followed by an in-depth study of analytic Doppler theory, as applied to both MOTs and optical molasses. The 3D distributions of Gajda et al. [27] are generalised, allowing the inclusion of both intensity and frequency imbalances. Forces arising from reradiation and absorption are then added to the description, with particular emphasis on the non-conservative absorptive force. Constant-temperature solutions do not appear to exist for the differential equations which arise in such a regime, raising questions about the validity of commonly used density relations based on this assumption. Possible errors in the formalism are covered, as well as their means of rectification. Work on the theoretical Doppler forces involved in ring-shaped MOT structures is reviewed, and possible solutions to the present discrepancy between theoretical and experimental studies in this field are discussed in the context of reradiation. Analytic theory as well as a Doppler Monte Carlo simulation are employed. A brief description of sub-Doppler theory is succeeded by a theoretical study of the 3D standing waves in laser cooling apparatus, focusing on the relative phases of the laser beams. Properties of various laser polarisation configurations are discussed with respect to the Sisyphus parameter p, of Steane et al. [71]. The (analytic) variance of p is evaluated spatially, enabling a simple comparison between different configurations and any combination of relative beam phases. The thesis concludes with an experimental investigation attempting to replicate the method of Kasevich et al. [39]. The expected behaviour of an optical molasses expansion is also considered.
Storage and controlling factors of soil organic carbon in alpine wetlands and meadow across the Tibetan Plateau

Alpine wetlands and meadows across the Three Rivers Source Region (TRSR) store high soil organic carbon (SOC). However, information on factors affecting SOC storage is scanty. Herein, we investigated SOC storage and explored factors affecting SOC storage, including climate, soil properties and above‐ and belowground biomass, using 50 soil profiles across the TRSR on the Tibetan Plateau. The SOC storage was 491.9 ± 158.5 Tg C and 545.2 ± 160.8 Tg C in the TRSR alpine wetlands and meadow, respectively. The SOC stock was positively correlated with the mean annual precipitation. However, no significant correlation between SOC stock and mean annual temperature was observed, as opposed to the global trend. In addition, SOC stock was positively correlated with both the aboveground biomass (AGB) and belowground biomass (BGB). Soil pH indirectly affected SOC stock, while SOC stock positively correlated with Al and Fe oxyhydroxides. Compared with vegetation biomass and climatic factors, soil properties, including soil pH and Al and Fe oxyhydroxides (Alo and Feo), affected not only SOC stock variation but also affected the impact of vegetation and climatic factors on SOC stock. Climate factors, AGB, BGB, soil pH, Alo and Feo jointly accounted for 59% of SOC stock variation in alpine wetlands and 64% of SOC stock variation in alpine meadow. This study suggests that soil properties are the dominant factors affecting SOC variation in alpine wetlands and meadow on the Tibetan Plateau.