Hiroshima City University

In the last few decades, a number of clustering methods for vectorial data have matured. Occasionally, researchers are interested in making them workable for data of other types, such as an object’s shape. The current difficulty in applying them to shape clustering is that clustering must be invariant to several similarity transformations of shapes. Therefore, we use the ordinary Procrustes sum of squares (OSS) in Procrustes analysis, which refers to analysis that is invariant to the similarity transformations between shapes. Thus, in this study, we aim to make mature methods workable in shape clustering. To achieve this, the essential points that we need to address are to rewrite the optimization problem associated with each method and to present a feasible method for computing the solution to the problem. As a result, we base the method on the OSS, its derivative, or a symmetric matrix concerning the OSS. Another aim of this study is to identify specific applications of shape clustering. We demonstrate the applications through experiments using datasets that contain skewed line drawings, American football formations, and baseball pitch trajectories. We examine the OSS-based methods by considering shape classification and determining the best method for implementing the OSS. As a result, regardless of the dataset, we demonstrate that the OSS in every method is more effective than other shape distances and that the convex clustering method incorporating the OSS is best performed in several ways. • Revisiting some mature clustering methods for processing shapes. • Using the ordinary Procrustes sum of squares to formulate object functions in optimization. • Comparing the revisited clustering methods in shape classification.

Abstract Panoramic cameras, capable of capturing a 360-degree field of view, are crucial in robotic vision, particularly in environments with sparse features. However, non-upright panoramas due to unstable robot postures hinder downstream tasks. Traditional IMU-based correction methods suffer from drift and external disturbances, while vision-based approaches offer a promising alternative. This study presents a dual-stream angle-aware generation network that jointly estimates camera inclination angles and reconstructs upright panoramic images. The network comprises a CNN branch that extracts local geometric structures from equirectangular projections and a ViT branch that captures global contextual cues from cubemap projections. These are integrated through a dual-projection adaptive fusion module that aligns spatial features across both domains. To further enhance performance, we introduce a high-frequency enhancement block, circular padding, and channel attention mechanisms to preserve 360° continuity and improve geometric sensitivity. Experiments on the SUN360 and M3D datasets demonstrate that our method outperforms existing approaches in both inclination estimation and upright panorama generation. Ablation studies further validate the contribution of each module and highlight the synergy between the two tasks. The code and related datasets can be found at: https://github.com/YuhaoShine/DualProjectionFusion.

The first time-resolved leader spectra associated with a downward Terrestrial Gamma-ray Flash (TGF) observed by the Telescope Array Surface Detector (TASD) were recently reported by \citeA{kieu2024first}. Building on that study, this paper presents th

Although several clinical trials have suggested the usefulness of drug-coated balloons (DCB) for side-branch lesions, their efficacy and safety have not yet been established. The Osaka Cardiovascular Conference (OCVC) will conduct a multicenter, randomized, open-label, controlled trial aiming to examine whether additional DCB treatment for the side branch after main vessel stenting followed by kissing balloon inflation (KBI) is superior to only KBI by conventional balloons in PCI patients with coronary bifurcation lesions. The primary endpoint is restenosis of side branches documented by scheduled or symptom-driven coronary angiography during 9-month follow-up period after the index PCI. The key secondary endpoints include major adverse cardiac event which consists of cardiac death, myocardial infarction, target lesion revascularization, and stent thrombosis, and optical coherence tomography findings. A total of 300 patients will be enrolled and followed up to 1year. The OCVC-BIF trial is a randomized controlled trial designed to assess whether additional DCB treatment for side branch is superior to only KBI by conventional balloons in patients with coronary bifurcation lesions undergoing PCI with main vessel stenting.

Abstract In four spacetime dimensions, the spin angular momentum in the Bhabha theory is governed by the five-dimensional Lorentz group L 5 . Using the quadratic Casimir operator of the L 5 , we obtain an analogous orbital angular momentum relation under the spin-orbit duality.

Nirmatrelvir is a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro) inhibitor that exerts its antiviral activity by covalently binding to the catalytic cysteine (Cys145) of Mpro; however, the emergence of drug-resistant variants remains an obstacle to successful antiviral therapy. In this study, we established 23 artificial SARS-CoV-2 Mpro mutants by substituting each active-site residue with alanine in the Mpro–nirmatrelvir complex using a computational approach referred to as a virtual alanine scan. Although the methods were primarily used for non-covalent inhibitor complexes, we conducted a virtual alanine scan for a protein–covalent inhibitor complex. Mutants, in which the structural changes of the main chain and the catalytic dyad were minimal, while the ligand configuration was significantly shifted, were considered to potentially confer drug resistance. The analysis revealed 13 residues: Ser1, His41, Tyr54, Phe140, Leu141, Gly143, Ser144, Cys145, Met165, Glu166, Pro168, Gln189, and Gln192 that are important for the recognition of nirmatrelvir by Mpro, and mutations at these residues may result in drug resistance. The ligand shifts observed in the experimentally reported resistant mutant G143S and the artificially mutant G143A were very similar. These results also indicate that a virtual alanine scan can be applied to covalent inhibitors.

BackgroundAccurate automatic recognition of surgical instruments is important for enhancing the safety and efficiency of transcanal endoscopic ear surgery (TEES). Segment Anything Model 2 (SAM 2) is a state-of-the-art artificial intelligence (AI) model featuring “zero-shot segmentation”, which allows it to identify objects without extensive training data. The purpose of this study was to be the first to apply SAM 2 to TEES videos to evaluate its performance in segmenting and classifying surgical instruments.MethodsFrom videos of three clinical TEES cases (tympanoplasty), we created a 684-frame evaluation video that simulated the sequential use of four types of surgical instruments: cupped forceps, pick, alligator forceps, and circular knife. SAM 2 was instructed to identify the instruments using only 12 reference images. Performance was quantitatively evaluated using four metrics—Precision, Recall, dice similarity coefficient (DSC), and intersection over union (IoU)—as well as a confusion matrix to assess frame-level classification accuracy by comparing the model’s output to manually created ground-truth annotations.ResultsFor segmentation without classification, SAM 2 demonstrated excellent performance, with a mean Precision of 0.98, a mean Recall of 0.89, a mean DSC of 0.93, and a mean IoU of 0.87. When classifying the four specific instrument types, performance varied, with mean Precision ranging from 0.68 to 0.98, mean Recall from 0.79 to 0.86, mean DSC from 0.62 to 0.89, and mean IoU from 0.58 to 0.84. Notably, false-positive detections in non-instrument regions were extremely rare. A trend of lower classification accuracy was observed for articulating instruments with moving parts (cupped forceps and alligator forceps).ConclusionsThis study demonstrated that SAM 2 can accurately identify surgical instruments in TEES videos without the need to prepare large, costly training datasets. This zero-shot segmentation characteristic significantly lowers the barrier to clinical implementation of AI, suggesting it is a promising foundational technology for future surgical navigation and robotic automation. Key future challenges include improving classification accuracy for articulating instruments and accelerating processing speed for practical, real-time use.

Wild animals cause damage to crops in Japan. Existing studies have worked on various wildlife detection using the Internet of Things (IoT) systems with cameras or infrared sensors. However, conventional approaches based on these modalities have limited detection coverage. This study aims to enlarge the detection area of wildlife detection systems with 920 MHz band radio waves, which are widely used in Low Power Wide Area (LPWA) communication systems. In this paper, we measured the variation of the received signal strength indicator (RSSI) by placing a human subject around the receiver to emulate an animal. These measurements were conducted under some of the antenna configurations with different types of the antenna height and the polarization. The measurement results show that the RSSI fluctuation due to human influence was larger when the antenna height was 0.1 m than when it was 1 m.