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The FLASH effect, characterized by potential sparing of organs at risk (OAR) through ultra-high dose rate irradiation, has garnered significant attention for its capability to address indications previously untreatable at conventional dose rates (DR) with hypofractionated schemes. While considerable biological research is needed to understand the FLASH effect and determine the FLASH modifying factors (FMF) for individual OARs, exploratory treatment planning studies have also emerged. This study aims to show that spinal metastases are candidate treatment sites likely to benefit from this phenomenon and establish the requisite FMFs to achieve the protective FLASH effect. A conformal FLASH Proton SBRT plan was generated for a patient with spine metastasis in a research version of RayStation11B (RaySearch laboratories AB, Stockhom) on an IBA Proteus Plus system. Two oblique posterior beams were used in the plan. The prescribed dose to the CTV was set according to 3 different fractionation regimens: 5 fractions (fx) of 7 Gy, 8 fx of 5 Gy, and 10 fx of 4.2 Gy. Spot filtering and sorting techniques were applied to maximize the 5% pencil beam scanning DR in the spinal cord (SC). The FLASH effect was assumed to be observed within irradiated regions above 40 Gy/s and 4 Gy per fraction. The generated plans successfully ensure robust target coverage in each fraction. The volume of SC that does not comply with the clinical goal adheres to the FLASH effect conditions in each fraction. Depending on the aforementioned fractionation schemes used, a FMF of approximately 0.6 to 0.8 is necessary to enable such treatment in FLASH conditions. Our study demonstrates the potential of hypofractionated FLASH PT in treating spine metastasis while preserving SC integrity. This approach could enable more effective treatment of spinal metastases, potentially preventing SC compression and paralysis in these patients., Comment: 7 pages, 3 figures (+ supplementary material)

The advent of ultra-high dose rate irradiation, known as FLASH radiation therapy, has shown promising potential in reducing toxicity while maintaining tumor control. However, the clinical translation of these benefits necessitates efficient treatment planning strategies. This study introduces a novel approach to optimize proton therapy for FLASH effects using traveling salesperson problem (TSP) heuristics. We applied these heuristics to optimize the arrangement of proton spots in treatment plans for 26 prostate cancer patients, comparing the performance against conventional sorting methods and global optimization techniques. Our results demonstrate that TSP-based heuristics significantly enhance FLASH coverage to the same extent as the global optimization technique, but with computation times reduced from hours to a few seconds. This approach offers a practical and scalable solution for enhancing the effectiveness of FLASH therapy, paving the way for more effective and personalized cancer treatments. Future work will focus on further optimizing run times and validating these methods in clinical settings.

Numerous applications have resulted from the automation of agricultural disease segmentation using deep learning techniques. However, when applied to new conditions, these applications frequently face the difficulty of overfitting, resulting in lower segmentation performance. In the context of potato farming, where diseases have a large influence on yields, it is critical for the agricultural economy to quickly and properly identify these diseases. Traditional data augmentation approaches, such as rotation, flip, and translation, have limitations and frequently fail to provide strong generalization results. To address these issues, our research employs a novel approach termed as PotatoGANs. In this novel data augmentation approach, two types of Generative Adversarial Networks (GANs) are utilized to generate synthetic potato disease images from healthy potato images. This approach not only expands the dataset but also adds variety, which helps to enhance model generalization. Using the Inception score as a measure, our experiments show the better quality and realisticness of the images created by PotatoGANs, emphasizing their capacity to resemble real disease images closely. The CycleGAN model outperforms the Pix2Pix GAN model in terms of image quality, as evidenced by its higher IS scores CycleGAN achieves higher Inception scores (IS) of 1.2001 and 1.0900 for black scurf and common scab, respectively. This synthetic data can significantly improve the training of large neural networks. It also reduces data collection costs while enhancing data diversity and generalization capabilities. Our work improves interpretability by combining three gradient-based Explainable AI algorithms (GradCAM, GradCAM++, and ScoreCAM) with three distinct CNN architectures (DenseNet169, Resnet152 V2, InceptionResNet V2) for potato disease classification.

The Bangla linguistic variety is a fascinating mix of regional dialects that adds to the cultural diversity of the Bangla-speaking community. Despite extensive study into translating Bangla to English, English to Bangla, and Banglish to Bangla in the past, there has been a noticeable gap in translating Bangla regional dialects into standard Bangla. In this study, we set out to fill this gap by creating a collection of 32,500 sentences, encompassing Bangla, Banglish, and English, representing five regional Bangla dialects. Our aim is to translate these regional dialects into standard Bangla and detect regions accurately. To achieve this, we proposed models known as mT5 and BanglaT5 for translating regional dialects into standard Bangla. Additionally, we employed mBERT and Bangla-bert-base to determine the specific regions from where these dialects originated. Our experimental results showed the highest BLEU score of 69.06 for Mymensingh regional dialects and the lowest BLEU score of 36.75 for Chittagong regional dialects. We also observed the lowest average word error rate of 0.1548 for Mymensingh regional dialects and the highest of 0.3385 for Chittagong regional dialects. For region detection, we achieved an accuracy of 85.86% for Bangla-bert-base and 84.36% for mBERT. This is the first large-scale investigation of Bangla regional dialects to Bangla machine translation. We believe our findings will not only pave the way for future work on Bangla regional dialects to Bangla machine translation, but will also be useful in solving similar language-related challenges in low-resource language conditions.

Background: Proton arc therapy is an emerging radiation therapy technique where either the gantry or the patient continuously rotates during the irradiation treatment. One of the perceived advantages of proton arc therapy is the reduced treatment time, but it is still unclear exactly how long these treatment times will be, given that no machine capable of its delivery is available at the market at the time of writing. Purpose: We introduce the algorithm Arc Trajectory Optimization Method (ATOM), which aims to determine an efficient velocity profile for the gantry for rapid delivery of a given proton arc treatment plan. Methods: ATOM computes the trajectory with the shortest delivery time while ensuring there is enough time to deliver all spots in each energy layer and switch energy between layers. The feasibility of the dynamic gantry movement was assured by enforcing maximum and minimum limits for velocity, acceleration, and jerk. This was achieved by discretizing the gantry velocity and combining the A* algorithm with the open-source motion generation library Ruckig. The algorithm was tested on a synthetic data set as well as a liver case, a prostate case and a head and neck case. Results: Arc trajectories for plans with 360 energy layers were calculated in under a second using 256 discrete velocities. Conclusions: ATOM is an open-source C++ library with a Python interface that rapidly generates velocity profiles, making it a highly efficient tool for determining proton arc delivery times, which could be integrated into the treatment planning process.

Proton arc therapy (PAT) has emerged as a promising approach for improving dose distribution, but also enabling simpler and faster treatment delivery in comparison to conventional proton treatments. However, the delivery speed achievable in proton arc relies on dedicated algorithms, which currently do not generate plans with a clear speed-up and sometimes even result in increased delivery time. This study aims to address the challenge of minimizing delivery time through a hybrid method combining a fast geometry-based energy layer (EL) pre-selection with a dose-based EL filtering. Three methods of EL filtering were developed; The unrestricted method filters the lowest weighted EL while the SU gap filtering removes the EL around a new SU to minimize the gantry rotation braking. The SU filtering removes the lowest weighted group of EL that includes a SU. These filters were combined with the RayStation dynamic proton arc optimization framework (ELSA). Four bilateral oropharyngeal and four lung cancer patients' data were used for evaluation. Objective function values, target coverage robustness, organ-at-risk doses and NTCP evaluations, as well as comparisons to IMPT plans, were used to assess plan quality. The SU gap filtering algorithm performed best in five out of the eight cases, maintaining plan quality within tolerance while reducing beam delivery time, in particular for the oropharyngeal cohort. It achieved up to approximately 22% and 15% reduction in delivery time for oropharyngeal and lung treatment sites, respectively. The unrestricted filtering algorithm followed closely. In contrast, the SU filtering showed limited improvement, suppressing one or two SU without substantial delivery time shortening. Robust target coverage was kept within 1% of variation compared to the PAT baseline plan while organs-at-risk doses slightly decreased or kept about the same for all patients., Comment: 22 pages, 7 figures

The relaxation dynamics in two van der Waals bonded and one hydrogen-bonding molecular liquids is studied as a function of pressure and temperature by incoherent neutron scattering using simultaneous dielectric spectroscopy. The dynamics is studied in a range of alpha relaxation times from nano- to milliseconds, primarily in the equilibrium liquid state. In this range we find that isochronal superposition and density scaling work not only for the two van der Waals liquids, but also for the hydrogen-bonding liquid, though the density scaling exponent is much smaller for the latter. Density scaling and isochronal superposition are seen to break down for intra-molecular dynamics when it is separated in time from the $\alpha$-relaxation in close agreement with previous observations from molecular dynamics simulations., Comment: 10 pages, 12 figures

A large class of liquids have hidden scale invariance characterized by a scaling exponent. In this letter we present experimental evidence that the scaling exponent of liquid dynamics is state-point dependent for the glass-forming silicone oil tetramethyl-tetraphenyl-trisiloxane (DC704) and 5-polyphenyl ether (5PPE). From dynamic and thermodynamic properties at equilibrium, we use a method to estimate the value of $\gamma$ at any state point of the pressure-temperature plane, both in the supercooled and normal liquid regimes. We find agreement between the average exponents and the value obtained by superposition of relaxation times over a large range of state-points. We confirm the state-point dependence of $\gamma$ by reanalyzing data of 20 metallic liquids and two model liquids.

In this article we report on the design, manufacture and testing of a high-pressure cell for doing simultaneous dielectric and neutron spectroscopy. This cell is a unique tool for studying dynamics on different timescales, from kilo- to picoseconds, covering universal features such as the alpha relaxation and fast vibrations at the same time. The cell, constructed in cylindrical geometry, is made in high-strength aluminum alloy and operates up to 500 MPa in a temperature range between roughly 2 and 320 K. In order to measure the scattered neutron intensity and the sample capacitance simultaneously, a cylindrical capacitor is positioned within the bore of the high-pressure container. The capacitor consists of two concentric electrodes separated by insulating spacers. The performance of this setup has been successfully verified by collecting simultaneous dielectric and neutron spectroscopy data on dipropylene glycol, using both backscattering and time-of-flight instruments. We have carried out the experiments at different combinations of temperature and pressure in both supercooled liquid and glassy state., Comment: A.S. and H.W.H. contributed equally to this work

The glass transition plays a central role in nature as well as in industry, ranging from biological systems such as proteins and DNA to polymers and metals. Yet the fundamental understanding of the glass transition which is a prerequisite for optimized application of glass formers is still lacking. Glass formers show motional processes over an extremely broad range of timescales, covering more than ten orders of magnitude, meaning that a full understanding of the glass transition needs to comprise this tremendous range in timescales. Here we report on first-time simultaneous neutron and dielectric spectroscopy investigations of three glass-forming liquids, probing in a single experiment the full range of dynamics. For two van der Waals liquids we locate in the pressure-temperature phase diagram lines of identical dynamics of the molecules on both second and picosecond timescales. This confirms predictions of the isomorph theory and effectively reduces the phase diagram from two to one dimension. The implication is that dynamics on widely different timescales are governed by the same underlying mechanisms.

The temperature dependence of the high-frequency shear modulus measured in the kHz range is compared to the mean-squared displacement measured in the nanosecond range for the two van der Waals bonded glass-forming liquids cumene and 5PPE. This provides an experimental test for the assumption connecting two versions of the shoving model for the non-Arrhenius temperature dependence of the relaxation time in glass formers. The two versions of the model are also tested directly and both are shown to work well for these liquids., Comment: 7 pages, 6 figures