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This paper reviews the nature of two quasiparticles, the Majorana fermion and vison, emergent in the Kitaev model, mainly from the theoretical point of view. We demonstrate how the fractionalization of a quantum spin into these two quasiparticles occurs and clarify their properties in the presence and absence of magnetic fields. In addition to discussions on the itinerant nature inherent to Majorana fermions, the quantum dynamics of visons induced by an applied magnetic field is revealed. Fractional quasiparticles manifest themselves in temperature evolutions of thermodynamic quantities, excitation spectra, and transport properties. The formulations for them and calculation results are shown in detail. Based on the results, we present how the signatures of fractional quasiparticles appear in physical quantities. The paper also mentions the recent developments of the experimental and theoretical works of Kitaev-related systems and presents outlooks of studies on these systems. [ABSTRACT FROM AUTHOR]

Dam is an essential structure in hydraulic engineering, and its surface cracks pose significant threats to its integrity, impermeability, and durability. Automated crack detection methods based on computer vision offer substantial advantages over manual approaches with regard to efficiency, objectivity and precision. However, current methods face challenges such as misidentification, discontinuity, and loss of details when analyzing real-world dam crack images. These images often exhibit characteristics such as low contrast, complex backgrounds, and diverse crack morphologies. To address the above challenges, this paper presents a pure Vision Transformer (ViT)-based dam crack segmentation network (DCST-net). The DCST-net utilizes an improved Swin Transformer (SwinT) block as the fundamental block for enhancing the long-range dependencies within a SegNet-like encoder–decoder structure. Additionally, we employ a weighted attention block to facilitate side fusion between the symmetric pair of encoder and decoder in each stage to sharpen the edge of crack. To demonstrate the superior performance of our proposed method, six semantic segmentation models have been trained and tested on both a self-built dam crack dataset and two publicly available datasets. Comparison results indicate that our proposed model outperforms the mainstream methods in terms of visualization and most evaluation metrics, highlighting its potential for practical application in dam safety inspection and maintenance. [ABSTRACT FROM AUTHOR]

The focus of this paper is on investigating the use of visual communication between two humanoid robots, in order to enhance the coordination of tasks between them. The problem continues to be an interesting and fruitful area of research from the days of using multiple robot manipulator arms for manufacturing as well as space robotics to current research in medical robotics. The approach here is to employ several off-the-shelf algorithms, software and hardware such as the NAO robot and support software, including Choregraphe, OpenCV to capture and process images, the SVM to classify objects in images, and the Python programming environment. Five robotic actions were studied and three modes. The experiments used one robot as the "viewer" and the second robot as the "subject" being analyzed. Results show that the visual communication system has an accuracy of 90% in correctly identifying the five movements. This research has shown an original solution, as a model that can enable robots to run in the complex service tasks consisting of multiple connected actions in a dynamic environment. This methodology can also let the intelligent operation of the robots serve in different scenes according to their actual requirements. This research focuses on enhancing the prototype robot vision function and development of additional value for consolidation manageable platform that increases service robots in the home environment of intelligent control capability. [ABSTRACT FROM AUTHOR]

The spread of SARS-CoV-2 to animals has the potential to evolve independently. In this study, we distinguished several sentinel animal species and genera for monitoring the re-emergence of COVID-19 or the new outbreak of COVID-19-like disease. We analyzed SARS-CoV-2 genomic data from human and nonhuman mammals in the taxonomic hierarchies of species, genus, family and order of their host. We find that SARS-CoV-2 carried by domestic dog (Canis lupus familiaris), domestic cat (Felis catus), mink (Neovison vison), and white-tailed deer (Odocoileus virginianus) cluster closely to human-origin viruses and show no differences in the majority of amino acids, but have the most positively selected sites and should be monitored to prevent the re-emergence of COVID-19 caused by novel variants of SARS-CoV-2. Viruses from the genera Panthera (especially lion (Panthera leo)), Manis and Rhinolophus differ significantly from human-origin viruses, and long-term surveillance should be undertaken to prevent the future COVID-19-like outbreaks. Investigation of the variation dynamics of sites 142, 501, 655, 681 and 950 within the S protein may be necessary to predict the novel animal SARS-CoV-2 variants. [ABSTRACT FROM AUTHOR]

While camera traps can effectively detect semi-aquatic mammal species, they are also often temporally and monetarily inefficient and have a difficult time detecting smaller bodied, elusive mammals. Recent studies have shown that extracting DNA from environmental samples can be a non-invasive, alternative method of detecting elusive species. Environmental DNA (eDNA) has not yet been used to survey American mink (Neogale vison), a cryptic and understudied North American mustelid. To help determine best survey practices for the species, we compared the effectiveness and efficiency of eDNA and camera traps in surveys for American mink. We used both methods to monitor the shoreline of seven bodies of water in northeastern Indiana from March to May 2021. We extracted DNA from filtered environmental water samples and used quantitative real-time PCR to determine the presence of mink at each site. We used Akaike's Information Criterion to rank probability of detection models with and without survey method as a covariate. We detected mink at four of the seven sites and seven of the 21 total survey weeks using camera traps (probability of detection (ρ) = 0.36). We detected mink at five sites and during five survey weeks using eDNA (ρ = 0.25). However, the highest probability of detection was obtained when both methods were combined, and data were pooled (ρ = 0.47). Survey method did not influence model fit, suggesting no difference in detectability between camera traps and eDNA. Environmental DNA was twice as expensive, but only required a little over half (58%) of the time when compared to camera trapping. We recommend ways in which an improved eDNA methodology may be more cost effective for future studies. For this study, a combination of both methods yielded the highest probability for detecting mink presence. [ABSTRACT FROM AUTHOR]

Quantum loop and dimer models are prototypical correlated systems with local constraints, which are not only intimately connected to lattice gauge theories and topological orders but are also widely applicable to the broad research areas of quantum materials and quantum simulation. Employing our sweeping cluster quantum Monte Carlo algorithm, we reveal the complete phase diagram of the triangular-lattice fully packed quantum loop model. Apart from the known lattice nematic (LN) solid and the even Z 2 quantum spin liquid (QSL) phases, we discover a hidden vison plaquette (VP) phase, which had been overlooked and misinterpreted as a QSL for more than a decade. Moreover, the VP-to-QSL continuous transition belongs to the (2 + 1)D cubic* universality class, which offers a lattice realization of the (fractionalized) cubic fixed point that had long been considered as irrelevant towards the O(3) symmetry until corrected recently by conformal bootstrap calculations. Our results are therefore of relevance to recent developments in both experiments and theory, and facilitate further investigations of hidden phases and transitions. By using the sweeping cluster quantum Monte Carlo algorithm, the authors reveal the complete ground-state phase diagram of the triangular-lattice fully packed quantum loop model. They discover a hidden vison plaquette phase between the known lattice nematic solid and the even Z 2 quantum spin liquid (QSL) phase, which had been previously misinterpreted as the QSL, and explain how to detect it experimentally. [ABSTRACT FROM AUTHOR]

Effective long-term management of invasive non-native species (INNS) in South America is a pressing yet complex task. Critically, the environmental, historical, cultural, and economic idiosyncrasies of the region call for the inclusion of a plurality of views from those sectors of society receiving the negative and positive impacts of INNS. This is a multifaceted, and often daunting, task that can be aided by an early identification of stakeholders – those affected by or with an interest in INNS and their management – accompanied by targeted stakeholder engagement. Here, we report the procedures and results of a stakeholder mapping activity aimed at identifying stakeholders and designing engagement strategies. Using expert knowledge procedures, we compiled comprehensive lists of stakeholders for six case-studies in South America: (i) invasive grasses (Urochloa spp.) in Brazil; (ii) glossy privet (Ligustrum lucidum) in Argentina; (iii) lodgepole and Monterey pines (Pinus contorta and P. radiata) in Argentina; (iv) American mink (Neogale vison) in Argentina and Chile; (v) lodgepole and Monterey pines in Chile; and (vi) German yellow-jacket (Vespula germanica) in Chile. Overall, we identified 250 stakeholders, which, based on their interest and influence, were classified into "context settlers" (2%), "key players" (47%), "crowd" (5%), and "subjects" (49%). We outlined strategies to engage with each of these four groups and for each of our six case-studies. Across case studies, communication with stakeholders was the most common engagement strategy proposed (27%; 19 of 70 strategies), followed by active involvement of stakeholders in INNS research and management (23%). Our results highlight the importance of considering power imbalances, as those stakeholders more likely to benefit from INNS were assessed to have more influence over INNS management relative to local and indigenous communities. Our work illustrates how to identify stakeholders in a rigorous and rapid manner, which should be complemented with the involvement of the stakeholders themselves. [ABSTRACT FROM AUTHOR]