Symmetry-Protected Solitons and Bulk-Boundary Correspondence in Generalized Jackiw-Rebbi Models

We investigate the roles of symmetry and bulk-boundary correspondence in characterizing topological edge states in generalized Jackiw-Rebbi (JR) models. We show that time-reversal ($T$), charge-conjugation ($C$), parity ($P$), and discrete internal field rotation ($Z_n$) symmetries protect and characterize the various types of edge states such as chiral and nonchiral solitons via bulk-boundary correspondence in the presence of the multiple vacua. As two representative models, we consider the JR model composed of a single fermion field having a complex mass and the generalized JR model with two massless but interacting fermion fields. The JR model shows nonchiral solitons with the $Z_2$ rotation symmetry, whereas it shows chiral solitons with the broken $Z_2$ rotation symmetry. In the generalized JR model, only nonchiral solitons can emerge with only $Z_2$ rotation symmetry, whereas both chiral and nonchiral solitons can exist with enhanced $Z_4$ rotation symmetry. Moreover, we find that the nonchiral solitons have $C, P$ symmetries while the chiral solitons do not, which can be explained by the symmetry-invariant lines connecting degenerate vacua. Finally, we find the symmetry correspondence between multiply-degenerate global vacua and solitons such that ${T}$, ${C}$, ${P}$ symmetries of a soliton inherit from global minima that are connected by the soliton, which provides a novel tool for the characterization of topological solitons

Anti-Forensic Trace Detection in Digital Forensic Triage Investigations

Anti-forensics, whether intentionally to disrupt investigations or simply an effort to make a computer system run better, is becoming of increasing concern to digital investigators. This work attempts to assess the problem of anti-forensics techniques commonly deployed in South Korea. Based on identified challenges, a method of signature-based anti-forensic trace detection is proposed for triage purposes that will assist investigators in quickly making decisions about the suspect digital devices before conducting a full investigation. Finally, a prototype anti-forensic trace detection system is given to demonstrate the practicality of the proposed method

Particle-antiparticle duality and fractionalization of topological chiral solitons

Although a prototypical Su–Schrieffer–Heeger (SSH) soliton exhibits various important topological concepts including particle-antiparticle (PA) symmetry and fractional fermion charges, there have been only few advances in exploring such properties of topological solitons beyond the SSH model. Here, by considering a chirally extended double-Peierls-chain model, we demonstrate novel PA duality and fractional charge e/2 of topological chiral solitons even under the chiral symmetry breaking. This provides a counterexample to the belief that chiral symmetry is necessary for such PA relation and fractionalization of topological solitons in a time-reversal invariant topological system. Furthermore, we discover that topological chiral solitons are re-fractionalized into two subsolitons which also satisfy the PA duality. As a result, such dualities and fractionalizations support the topological Z4 algebraic structures. Our findings will inspire researches seeking feasible and promising topological systems, which may lead to new practical applications such as solitronics.11Yscopu

Symmetry analysis of the Chiral Solitons in the extended Su-Schrieffer-Heeger model : Particle-Antiparticle Duality and Fractionalization

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Particle-antiparticle duality and re-fractionalization of chiral solitons in the extended Su-Schrieffer-Heeger model

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Developing a Diagnostic Decision Support System for Benign Paroxysmal Positional Vertigo Using a Deep-Learning Model

Background: Diagnosis of benign paroxysmal positional vertigo (BPPV) depends on the accurate interpretation of nystagmus induced by positional tests. However, difficulties in interpreting eye-movement often can arise in primary care practice or emergency room. We hypothesized that the use of machine learning would be helpful for the interpretation. Methods: From our clinical data warehouse, 91,778 nystagmus videos from 3467 patients with dizziness were obtained, in which the three-dimensional movement of nystagmus was annotated by four otologic experts. From each labeled video, 30 features changed into 255 grid images fed into the input layer of the neural network for the training dataset. For the model validation, video dataset of 3566 horizontal, 2068 vertical, and 720 torsional movements from 1005 patients with BPPV were collected. Results: The model had a sensitivity and specificity of 0.910 ± 0.036 and 0.919 ± 0.032 for horizontal nystagmus; of 0.879 ± 0.029 and 0.894 ± 0.025 for vertical nystagmus; and of 0.783 ± 0.040 and 0.799 ± 0.038 for torsional nystagmus, respectively. The affected canal was predicted with a sensitivity of 0.806 ± 0.010 and a specificity of 0.971 ± 0.003. Conclusions: As our deep-learning model had high sensitivity and specificity for the classification of nystagmus and localization of affected canal in patients with BPPV, it may have wide clinical applicability

Bed-mounted laparoscopic surgical robot system with novel positioning arm mechanism

Background Commercialised laparoscopic surgical robotic systems require a large operating room and can only be used in large hospitals. If the robotic system is to be used in a small- or medium-sized hospital, the occupied volume must be reduced further. Methods In this paper, we propose a bed-mounted system that can be installed in a general operating room. Furthermore, we proposed a novel positioning arm suitable for a bed-mounted surgical robot system. Results The surgical possibility of the proposed bed-mounted system has been verified. Furthermore, the surgical possibility of the proposed system was confirmed using in vivo animal experiments. Conclusions A bed-mounted laparoscopic robotic system and a novel positioning arm was proposed. The study's ultimate goal is to enable robotic surgery in small and medium-sized hospitals by introducing the proposed bed-mounted laparoscopic robot system, allowing many people to receive high-quality medical services.FALS

Leukodystrophy in children: a pictorial review of MR imaging features

Dysmyelinating diseases, or leukodystrophies, encompass a wide spectrum of inherited neurodegenerative disorders affecting the integrity of myelin in the brain and peripheral nerves. Most of these disorders fall into one of three categories-lysosomal storage diseases, peroxisomal disorders, and diseases caused by mitochondrial dysfunction-and each leukodystrophy has distinctive clinical, biochemical, pathologic, and radiologic features. Magnetic resonance (MR) imaging has become the primary imaging modality in patients with leukodystrophy and plays an important role in the identification, localization, and characterization of underlying white matter abnormalities in affected patients. MR imaging has also been extensively used to monitor the natural progression of various white matter disorders and the response to therapy. Although the MR imaging features of leukodystrophy are often nonspecific, systematic analysis of the finer details of disease involvement may permit a narrower differential diagnosis, which the clinician can then further refine with knowledge of patient history, clinical testing, and metabolic analysis