Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Dynamic Monte Carlo Technique in Proton Beam Radiotherapy using Geant4 Simulation Toolkit

Application of Dynamic Monte Carlo Technique in Proton Beam Radiotherapy Using Geant4 Simulation Toolkit. (May 2012) Fada Guan, B.E. , Tsinghua University; M.S., Texas A&M University Chair of Advisory Committee: Dr. John W. Poston, Sr. Monte Carlo method has been successfully applied in simulating the particles transport problems. Most of the Monte Carlo simulation tools are static and they can only be used to perform the static simulations for the problems with fixed physics and geometry settings. Proton therapy is a dynamic treatment technique in the clinical application. In this research, we developed a method to perform the dynamic Monte Carlo simulation of proton therapy using Geant4 simulation toolkit. A passive-scattering treatment nozzle equipped with a rotating range modulation wheel was modeled in this research. One important application of the Monte Carlo simulation is to predict the spatial dose distribution in the target geometry. For simplification, a mathematical model of a human body is usually used as the target, but only the average dose over the whole organ or tissue can be obtained rather than the accurate spatial dose distribution. In this research, we developed a method using MATLAB to convert the medical images of a patient from CT scanning into the patient voxel geometry. Hence, if the patient voxel
Diffusion Models for Zero-Shot Open-Vocabulary Segmentation

The variety of objects in the real world is nearly unlimited and is thus impossible to capture using models trained on a fixed set of categories. As a result, in recent years, open-vocabulary methods have attracted the interest of the community. This paper proposes a new method for zero-shot open-vocabulary segmentation. Prior work largely relies on contrastive training using image-text pairs, leveraging grouping mechanisms to learn image features that are both aligned with language and well-localised. This however can introduce ambiguity as the visual appearance of images with similar captions often varies. Instead, we leverage the generative properties of large-scale text-to-image diffusion models to sample a set of support images for a given textual category. This provides a distribution of appearances for a given text circumventing the ambiguity problem. We further propose a mechanism that considers the contextual background of the sampled images to better localise objects and segment the background directly. We show that our method can be used to ground several existing pre-trained self-supervised feature extractors in natural language and provide explainable predictions by mapping back to regions in the support set. Our proposal is training-free, relying on pre-trained components only, yet, shows strong performance on a range of open-vocabulary segmentation benchmarks, obtaining a lead of more than 10% on the Pascal VOC benchmark.
Efficiency of two classes of stochastic restricted almost unbiased type principal component estimators in linear regression model

ABSTRACT In this paper, we introduce two new classes of estimators called the stochastic restricted almost unbiased ridge-type principal component estimator (SRAURPCE) and the stochastic restricted almost unbiased Liu-type principal component estimator (SRAURPCE) to overcome the well-known multicollinearity problem in linear regression model. For the two cases when the restrictions are true and not true, necessary and sufficient conditions for the superiority of the proposed estimators are derived and compared, respectively. Furthermore, a Monte Carlo simulation study and a numerical example are given to illustrate the performance of the proposed estimators.
Semantic HELM: An Interpretable Memory for Reinforcement Learning

Reinforcement learning agents deployed in the real world often have to cope with partially observable environments. Therefore, most agents employ memory mechanisms to approximate the state of the environment. Recently, there have been impressive success stories in mastering partially observable environments, mostly in the realm of computer games like Dota 2, StarCraft II, or MineCraft. However, none of these methods are interpretable in the sense that it is not comprehensible for humans how the agent decides which actions to take based on its inputs. Yet, human understanding is necessary in order to deploy such methods in high-stake domains like autonomous driving or medical applications. We propose a novel memory mechanism that operates on human language to illuminate the decision-making process. First, we use CLIP to associate visual inputs with language tokens. Then we feed these tokens to a pretrained language model that serves the agent as memory and provides it with a coherent and interpretable representation of the past. Our memory mechanism achieves state-of-the-art performance in environments where memorizing the past is crucial to solve tasks. Further, we present situations where our memory component excels or fails to demonstrate strengths and weaknesses of our new approach.
PaReprop: Fast Parallelized Reversible Backpropagation

The growing size of datasets and deep learning models has made faster and memory-efficient training crucial. Reversible transformers have recently been introduced as an exciting new method for extremely memory-efficient training, but they come with an additional computation overhead of activation re-computation in the backpropagation phase. We present PaReprop, a fast Parallelized Reversible Backpropagation algorithm that parallelizes the additional activation re-computation overhead in reversible training with the gradient computation itself in backpropagation phase. We demonstrate the effectiveness of the proposed PaReprop algorithm through extensive benchmarking across model families (ViT, MViT, Swin and RoBERTa), data modalities (Vision&NLP), model sizes (from small to giant), and training batch sizes. Our empirical results show that PaReprop achieves up to 20% higher training throughput than vanilla reversible training, largely mitigating the theoretical overhead of 25% lower throughput from activation recomputation in reversible training. Project page: https://tylerzhu.com/pareprop.
Segment Any Point Cloud Sequences by Distilling Vision Foundation Models

Recent advancements in vision foundation models (VFMs) have opened up new possibilities for versatile and efficient visual perception. In this work, we introduce Seal, a novel framework that harnesses VFMs for segmenting diverse automotive point cloud sequences. Seal exhibits three appealing properties: i) Scalability: VFMs are directly distilled into point clouds, obviating the need for annotations in either 2D or 3D during pretraining. ii) Consistency: Spatial and temporal relationships are enforced at both the camera-to-LiDAR and point-to-segment regularization stages, facilitating cross-modal representation learning. iii) Generalizability: Seal enables knowledge transfer in an off-the-shelf manner to downstream tasks involving diverse point clouds, including those from real/synthetic, low/high-resolution, large/small-scale, and clean/corrupted datasets. Extensive experiments conducted on eleven different point cloud datasets showcase the effectiveness and superiority of Seal. Notably, Seal achieves a remarkable 45.0% mIoU on nuScenes after linear probing, surpassing random initialization by 36.9% mIoU and outperforming prior arts by 6.1% mIoU. Moreover, Seal demonstrates significant performance gains over existing methods across 20 different few-shot fine-tuning tasks on all eleven tested point cloud datasets.
Translational Inertial Dragging

An important question in the theory of general relativity is to decide whether this theory contains the general principle of relativity for accelerated motion (including rotation). This question is also related to Mach’s principle. The aim of this theisis is to throw some new light on this question. In this connection I have deduced a solution of the full Einstein equations, describing a physical system producing perfect inertial dragging. This system is a singular shell with the metric of an accelerated black hole outside the shell and (comoving) flat spacetime inside the shell. The effect of inertial dragging is described and previous work on translational inertial dragging is reviewed. The Israel formalism is presented in full mathematical detail and applied to a few special cases before applying it to the accelerated shell.
Air pollution and mortality in patients with chronic obstructive pulmonary disease: a cohort study in South Korea

Background: Evidence on whether long-term exposure to air pollution increases the mortality risk in patients with chronic obstructive pulmonary disease (COPD) is limited. Objectives: We aimed to investigate the associations of long-term exposure to particulate matter with diameter <10 µm (PM10) and nitrogen dioxide (NO2) with overall and disease-specific mortality in COPD patients. Design: We conducted a nationwide retrospective cohort study of 121,423 adults ⩾40 years diagnosed with COPD during 1 January to 31 December 2009. Methods: Exposure to PM10 and NO2 was estimated for residential location using the ordinary kriging method. We estimated the risk of overall mortality associated with 1-, 3-, and 5-years average concentrations of PM10 and NO2 using Cox proportional hazards models and disease-specific mortality using the Fine and Gray method adjusted for age, sex, income, body mass index, smoking, comorbidities, and exacerbation history. Results: The adjusted hazard ratios (HRs) for overall mortality associated with a 10 µg/m3 increase in 1-year PM10 and NO2 exposures were 1.004 [95% confidence interval (CI) = 0.985, 1.023] and 0.993 (95% CI = 0.984, 1.002), respectively. The results were similar for 3- and 5-year exposures. For a 10-µg/m3 increase in 1-year PM10 and NO2 exposures, the adjusted HRs for chronic lower airway disease mortality were 1.068 (95% CI = 1.024, 1.113) and 1.029 (95% CI = 1.009, 1.050), respectively. In stratified analyses, exposures to PM10 and NO2 were associated with overall mortality in patients who were underweight and had a history of severe exacerbation. Conclusion: In this large population-based study of patients with COPD, long-term PM10 and NO2 exposures were not associated with overall mortality but were associated with chronic lower airway disease mortality. PM10 and NO2 exposures were both associated with an increased risk of overall mortality in underweight individuals and those with a history of severe exacerbation.
Predictions of Solar Cycle 24: How are we doing?

Predictions of solar activity are an essential part of our Space Weather forecast capability. Users are requiring usable predictions of an upcoming solar cycle to be delivered several years before solar minimum. A set of predictions of the amplitude of Solar Cycle 24 accumulated in 2008 ranged from zero to unprecedented levels of solar activity. The predictions formed an almost normal distribution, centered on the average amplitude of all preceding solar cycles. The average of the current compilation of 105 predictions of the annual‐average sunspot number is 106 ± 31, slightly lower than earlier compilations but still with a wide distribution. Solar Cycle 24 is on track to have a below‐average amplitude, peaking at an annual sunspot number of about 80. Our need for solar activity predictions and our desire for those predictions to be made ever earlier in the preceding solar cycle will be discussed. Solar Cycle 24 has been a below‐average sunspot cycle. There were peaks in the daily and monthly averaged sunspot number in the Northern Hemisphere in 2011 and in the Southern Hemisphere in 2014. With the rapid increase in solar data and capability of numerical models of the solar convection zone we are developing the ability to forecast the level of the next sunspot cycle. But predictions based only on the statistics of the sunspot number are not adequate for predicting the next solar maximum. I will describe how we did in predicting the amplitude of Solar Cycle 24 and describe how solar polar field predictions could be made more accurate in the future.
Observing dust grain growth andsedimentation in circumstellar discs

In the present thesis, the observational effects of dust grain growth and sedimentation in circumstellar discs are investigated. The growth of dust grains from some nanometres in diameter as found in the inter- stellar medium towards planetesimal bodies some meters in diameter is an important step in the formation of planets. However, this process is currently not entirely un- derstood. Especially, in the literature several ‘barriers’ are discussed that apparently prohibit an effective growth of dust grains. Hence, it is of particular interest to compare theories and observational data in this respect. State-of-the-art radiative transfer techniques allow one to derive observable quantities from theoretical models that allow this comparison. In this thesis, generic tracers of dust grain growth in spatially high resolution multi-wavelength images are identified for the first time. Further, a possibility to detect a dust trapping mechanism for dust grains by local pressure maxima using the new interferometer, ALMA, is established. By fitting parametric models to new observations of the disc in the Bok globule CB 26, unexpected features of the system are revealed, such as a large inner void and the possibility to interpret the data without the need for grain growth. In the same way, new observations and their interpretation of IRAS 04302+2247 provide evidence for the first time for radial dependent settling of dust grains in images. Moreover, in this thesis the applicability of the T Tauri disc paradigm to the high-mass disc candidate IRAS 18151-1208 is demonstrated.
Lactose or milk oligosaccharide: which is significant among mammals?

https://doi.org/10.1093/af/vfad017 This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons. org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com © Urashima, Horiuchi, Sakanaka, Katayama, Fukuda Featured Article Lactose or milk oligosaccharide: which is significant among mammals?
Lumbar Discectomy With Bone-Anchored Annular Closure Device in Patients With Large Annular Defects: One-Year Results

Background: Reherniation rates following lumbar discectomy are low for most patients; however, patients with a large defect in the annulus fibrosis have a significantly higher risk of recurrence. Previous results from a randomized controlled trial (RCT) demonstrated that the implantation of a bone-anchored annular closure device (ACD) during discectomy surgery lowered the risk of symptomatic reherniation and reoperation over one year with fewer serious adverse events (SAEs) compared to discectomy alone. Objective: The objective of this prospective, post-market, historically controlled study was to evaluate the use of an ACD during discectomy, and to confirm the results of the RCT that was used to establish regulatory approval in the United States. Methods: In this post-market study, all patients (N = 55) received discectomy surgery with a bone-anchored ACD. The comparison population was patients enrolled in the RCT study who had discectomy with an ACD (N = 262) or discectomy alone (N = 272). All other eligibility criteria, surgical technique, device characteristics, and follow-up methodology were comparable between studies. Endpoints included rate of symptomatic reherniation or reoperation, SAEs, and patient-reported measures of disability, pain, and quality of life. Results: Fifty-five patients received ACD implants at 12 sites between May 2020 and February 2021. In the previous RCT, 272 control patients had discectomy surgery alone (RCT-Control), and 262 patients had discectomy surgery with an ACD implant (RCT-ACD). Baseline characteristics across groups were typical of the overall population undergoing lumbar discectomy. The proportion of patients who experienced reherniation and/or reoperation was significantly lower in the ACD group compared to RCT-ACD and RCT-Control groups (p < 0.05). In the ACD study, the one-year rate of symptomatic reherniation was 3.7%, compared to 8.5% in the RCT-ACD group and 17.0% in the RCT-Control group. In the ACD group, the risk of reoperation was 5.5%, compared to 6.5% in the RCT-ACD group and 12.5% in the RCT-Control group. There were no device-related SAEs or device integrity failures in the ACD, and there were clinically meaningful improvements in patient-reported measures of disability, pain, and quality of life. Conclusion: In this post-market study of bone-anchored ACD in patients with large annular defects, rates of symptomatic reherniation, reoperation, and SAEs were all low. Compared to the RCT, the post-market ACD study demonstrated lower rates of reherniation and/or reoperation and measures of back pain one-year post-surgery.
NOTES AND CORRESPONDENCE Jet Drops Produced by Bubbles Bursting at the Surface of Seawater

Several empirical formulas were reported to describe the production of jet drops by bubbles bursting at the surface of seawater; they were, however, based on scanty data. Recent observations of Spiel have provided new data for intermediate-size bubbles; his results are further quantified here, aiming for their extrapolations to both small and large bubbles. A greater number of jet drops are shown to be produced by smaller bubbles; the production follows a combined exponential and linear decline for larger bubbles, rather than the exponential or linear decline proposed earlier. The largest number of jet drops produced by the smallest bubble may not exceed seven. The largest bubble that can produce jet drops may not exceed about 1.7 mm, a radius somewhat smaller than the analytical value. The ratio between the radius of jet drops and that of their parent bubble is always greater than the oft-quoted 1-to-10 value; it approaches a minimum value of 0.110 for zero bubble radius and reaches a maximum value of 0.147 for bubbles having a radius larger than 0.8 mm.
Limonin, a natural ERK2 agonist, protects against ischemic acute kidney injury

Acute kidney injury (AKI) is a refractory clinical syndrome with limited effective treatments. Amid AKI, activation of the extracellular signal-regulated kinase (ERK) cascade plays a critical role in promoting kidney repair and regeneration. However, a mature ERK agonist in treating kidney disease remains lacking. This study identified limonin, a member of the class of compounds known as furanolactones, as a natural ERK2 activator. Employing a multidisciplinary approach, we systemically dissected how limonin mitigates AKI. Compared to vehicles, pretreatment of limonin significantly preserved kidney functions after ischemic AKI. We revealed that ERK2 is a significant protein linked to the limonin's active binding sites through structural analysis. The molecular docking study showed a high binding affinity between limonin and ERK2, which was confirmed by the cellular thermal shift assay and microscale thermophoresis. Mechanistically, we further validated that limonin promoted tubular cell proliferation and reduced cell apoptosis after AKI by activating ERK signaling pathway in vivo. In vitro and ex vivo, blockade of ERK abolished limonin's capacity of preventing tubular cell death under hypoxia stress. Our results indicated that limonin is a novel ERK2 activator with strong translational potential in preventing or mitigating AKI.
BY INTERACTING BOSON MODEL (IBM-1)

Abstract –This paper reports on the electric quadrupole reduced transition probabilities BE () 2 between 6 + to 4 + and 4 + to 2 + states of 114,116,118,122 Cd isotopes using interacting boson model (IBM-1). The values of reduced transition probabilities of 114 Cd, 116 Cd, 118 Cd, 122 Cd nuclei from transitions 4 + to 2 + and 6 + to 4 + are 0.180 and 0.237 eb 22 , 0.197, and 0.253 eb 22 , 0.194 and 0.243 eb 22 , and 0.143 and 0.168 eb 22 , respectively. In addition, the systematic BE () 2 values are studied as a function of neutron numbers from N =66, 68, 70, 74. The calculated results of BE ( 2 ) in IBM-1 are in good agreement with experimental values. Keywords : reduced transition probabilities, Cd, 6, + 4, + 2 + states 1. Introduction The interacting boson model 1 (IBM-1), developed by Arima and Lachello [1], is a nuclear model developed for the description of collective structures. In the first version, IBM-1, no district ion is made between neutron and proton degree of freedom. There is no clear connection with a microscopic structure that it is important to treat the neutron and proton degrees of freedom independently. It can provide theoretical level energies and transition strengths while including anharmonicities from residual interactions. The IBM employs a severely truncated model space and as such, calculations are possible for nuclei with N nucleons, providing a quantitative mechanism to compare experimental results and calculated values [2,3]. Neutron rich Cd isotopes are particularly interesting because they are existed with two less of protons near the magic number proton 50. It has been considered as an anharmonic vibration-like nucleus. This corresponds to the
The Use of Membranes (ST-100, oXiris, and M60) for Continuous Renal Replacement Therapy in a Child with Sepsis

Sepsis is a critical condition affecting patients worldwide. Systemic inflammatory response syndrome in sepsis contributes to organ dysfunction and mortality. The oXiris is a recently developed continuous renal replacement therapy (CRRT) hemofilter indicated for the adsorption of cytokines from the bloodstream. In our study, in a septic child, CRRT with three filters, including the oXiris hemofilter, resulted in a downregulation of inflammatory biomarkers and a reduction of vasopressors. Herein, we described the first report of such usage in septic children.
Prominent 18F-FDG Uptake in the Adrenal Gland after Contralateral Adrenalectomy in a Known Case of Adrenocortical Oncocytic Carcinoma

Adrenocortical carcinoma (ACC) is a rare type of cancer that is associated with a high rate of recurrence and poor prognosis. The main diagnostic approaches to adrenocortical cancer include CT scan, MRI and the promising role of 18F-FDG PET/CT. The main therapeutic approaches include radical surgery of local disease and recurrences, as well as adjuvant mitotane therapy. The evaluation of adrenocortical carcinoma (ACC) could be difficult by using 18F-FDG PET/CT in view of the significant association between the 18F-FDG uptake and ACC. At the same time, not all adrenal glands with 18F-FDG uptake are considered to be malignant, so awareness of these various findings is substantial for ACC management, especially with limited data regarding the role of 18F-FDG PET/CT in ACC post-operative settings. This report discusses the case of a 47-year-old man with a history of left adrenocortical carcinoma who underwent adrenalectomy and received adjuvant mitotane therapy. 9 months after the surgery, a follow-up 18F-FDG PET/CT scan showed that the 18F-FDG uptake was prominent in the right adrenal gland without corresponding abnormal CT scan findings.
Exosomes released from macrophages infected with Talaromyces marneffei activate the innate immune responses and decrease the replication

Recent studies have demonstrated that exosomes play roles in pathogenesis and in the treatment of various diseases. We explored the influence of exosomes released from Talaromyces marneffei (T. marneffei)‐infected macrophages on human macrophages to determine whether they play a role in the pathogenesis of T. marneffei infection.