Search Results (23)

Lilium holds significant horticultural and ecological importance. Understanding the morpho-anatomical diversity of the stems can provide insights into taxonomy and breeding strategies. This study comprehensively examined the stem morpho-anatomy of 71 Lilium taxa to elucidate taxonomic and structural differences. For the first time, four distinct jigsaw-puzzle-shaped shapes of epidermal cells (Ep) in monocot stems, novel I-shaped and Co-xylem (O-, X-, W-, Q-shaped) vascular bundles (Vb) in Lilium stems, and quantitative characteristics (Vb density, xylem/phloem area ratio, etc.) were systematically discovered and analyzed. Asiatic (A) and Longiflorum × A (LA) hybrids displayed epidermal appendages, while Oritenal × Trumpet (OT) hybrids featured thicker sclerenchymatous rings (Sr). Collateral Vb in hybrids visually displayed bicollateral with degraded bundle sheaths (Bs), contrasting with intact circular Bs in wild species. Ward.D clustering categorized Lilium taxa into group A (Oritenal and OT hybrids) and B (A, LA, Trumpet, Longiflorum × Oriental hybrids and wild species), with Mantel’s test identified height, Ep shape, Ep length/width ratio, cortex/Sr thickness ratio and Bs integrity as key discriminators. Bending stems exhibited a higher Vb area. These findings establish a comprehensive pheno-anatomical framework for Lilium, which can guide future breeding programs and ecological studies. Full article

We propose an enhanced privacy-preserving method for image classification using ConvMixer, which is an extremely simple model that is similar in spirit to the Vision Transformer (ViT). Most privacy-preserving methods using encrypted images cause the performance of models to degrade due to the influence of encryption, but a state-of-the-art method was demonstrated to have the same classification accuracy as that of models without any encryption under the use of ViT. However, the method, in which a common secret key is assigned to each patch, is not robust enough against ciphertext-only attacks (COAs) including jigsaw puzzle solver attacks if compressible encrypted images are used. In addition, ConvMixer is less robust than ViT because there is no position embedding. To overcome this issue, we propose a novel block-wise encryption method that allows us to assign an independent key to each patch to enhance robustness against attacks. In experiments, the effectiveness of the method is verified in terms of image classification accuracy and robustness, and it is compared with conventional privacy-preserving methods using image encryption. Full article

Agate veins and nodules occur in the Lece Volcanic Complex (Oligocene-Miocene) situated in the south of Serbia and occupying an area of 700 km². This volcanic complex is composed predominantly of andesites, with sporadic occurrences of andesite-basalts, dacites and latites, and features agate formations that have been very little investigated. This study focuses on five selected agate occurrences within the Lece Volcanic Complex, employing optical microscopy, scanning electron microscopy (SEM), X-ray powder diffraction analysis, inductively coupled plasma mass spectrometry (ICP-MS), and Fourier transform infrared spectroscopy (FTIR). In three localities (Rasovača, Mehane, and Ždraljevići), agate mineralization is directly related to distinct fault zones with strong local brecciation. In the other two localities (Vlasovo and Sokolov Vis), the agate is found in nodular form and does not show any connection with fracture zones. The silica phases of the Lece volcanic agates consist of cristobalite and tridymite, length-fast chalcedony, quartzine (length-slow chalcedony), and macrocrystalline quartz. Vein agates show a frequent alternation between length-fast chalcedony and quartz bands. Nodular agates consist primarily of length-fast chalcedony, occasionally containing notable quantities of opal-CT, absent in vein agates. Microtextures present in vein agates include crustiform, colloform, comb, mosaic, flamboyant, and pseudo-bladed. Jigsaw puzzle quartz microtexture supports the recrystallization of previously deposited silica in the form of opal or chalcedony from hydrothermal fluids. Growth lines in euhedral quartz (Bambauer quartz) point to agate formations in varying physicochemical conditions. These features indicate epithermal conditions during the formation of hydrothermal vein agates. Due to intense hydrothermal activity, vein agate host rocks are intensively silicified. Vein agates are also enriched with typical ore metallic elements (especially Pb, Co, As, Sb, and W), indicating genetic relation with the formation of polymetallic ore deposits of the Lece Volcanic Complex. In contrast, nodular agates have a higher content of major elements of host rocks (Al₂O₃, MgO, CaO, Na₂O, and K₂O), most probably mobilized from volcanic host rocks. Organic matter, present in both vein and nodular agate with filamentous forms found only in nodular agate, suggests formation in near-surface conditions. Full article

Virtual reality (VR) enables the development of virtual training frameworks suitable for various domains, especially when real-world conditions may be hazardous or impossible to replicate because of unique additional resources (e.g., equipment, infrastructure, people, locations). Although VR technology has significantly advanced in recent years, methods for evaluating immersion (i.e., the extent to which the user is engaged with the sensory information from the virtual environment or is invested in the intended task) continue to rely on self-reported questionnaires, which are often administered after using the virtual scenario. Having an objective method to measure immersion is particularly important when using VR for training, education, and applications that promote the development, fine-tuning, or maintenance of skills. The level of immersion may impact performance and the translation of knowledge and skills to the real-world. This is particularly important in tasks where motor skills are combined with complex decision making, such as surgical procedures. Efforts to better measure immersion have included the use of physiological measurements including heart rate and skin response, but so far they do not offer robust metrics that provide the sensitivity to discriminate different states (idle, easy, and hard), which is critical when using VR for training to determine how successful the training is in engaging the user’s senses and challenging their cognitive capabilities. In this study, electroencephalography (EEG) data were collected from 14 participants who completed VR jigsaw puzzles with two different levels of task difficulty. Machine learning was able to accurately classify the EEG data collected during three different states, obtaining accuracy rates of 86% and 97% for differentiating easy versus hard difficulty states and baseline vs. VR states. Building on these results may enable the identification of robust biomarkers of immersion in VR, enabling real-time recognition of the level of immersion that can be used to design more effective and translative VR-based training. This method has the potential to adjust aspects of VR related to task difficulty to ensure that participants are immersed in VR. Full article

Effective features play an important role in synthetic aperture radar (SAR) image interpretation. However, since SAR images contain a variety of terrain types, it is not easy to extract effective features of different terrains from SAR images. Deep learning methods require a large amount of labeled data, but the difficulty of SAR image annotation limits the performance of deep learning models. SAR images have inevitable geometric distortion and coherence speckle noise, which makes it difficult to extract effective features from SAR images. If effective semantic context features cannot be learned for SAR images, the extracted features struggle to distinguish different terrain categories. Some existing terrain classification methods are very limited and can only be applied to some specified SAR images. To solve these problems, a jigsaw puzzle self-supervised learning (JPSSL) framework is proposed. The framework comprises a jigsaw puzzle pretext task and a terrain classification downstream task. In the pretext task, the information in the SAR image is learned by completing the SAR image jigsaw puzzle to extract effective features. The terrain classification downstream task is trained using only a small number of labeled data. Finally, fully connected conditional random field processing is performed to eliminate noise points and obtain a high-quality terrain classification result. Experimental results on three large-scene high-resolution SAR images confirm the effectiveness and generalization of our method. Compared with the supervised methods, the features learned in JPSSL are highly discriminative, and the JPSSL achieves good classification accuracy when using only a small amount of labeled data. Full article

Is it possible to experience healing and growth when you grieve? How and where do you find meaning again? During the COVID-19 pandemic, many people were looking for answers to these questions. This autoethnography explores how I experienced personal transformation through the method of Music and Imagery (MI) therapy in the midst of the pandemic and huge personal loss. This transformation also impacted my faith in Christ. Through documenting my journey using music listening, artwork, journaling, memories, and peers’ feedback, I realized just how possible it was to grow and find healing in trying times. I pieced all the information together like a jigsaw puzzle until I could see the complete picture. Full article

An enumeration of spatial autocorrelation’s (SA’s) polyvalent forms occurred nearly three decades ago. Attempts to conceive and disseminate a clearer explanation of it employ metaphors seeking to better relate SA to a student’s or spatial scientist’s personal knowledge databank. However, not one of these uses the jigsaw puzzle metaphor appearing in this paper, which exploits an analogy between concrete visual content organization and abstract map patterns of attributes. It not only makes SA easier to understand, which furnishes a useful pedagogic tool for teaching novices and others about it, but also discloses that many georeferenced data should contain a positive–negative SA mixture. Empirical examples corroborate this mixture’s existence, as well as the tendency for marked positive SA to characterize remotely sensed and moderate (net) positive SA to characterize socio-economic/demographic, georeferenced data. Full article

This study proposed two algorithms for reconstructing jigsaw puzzles by using a color compatibility feature. Two realistic application cases were examined: one involved using the original image, while the other did not. We also calculated the transformation matrix to obtain the real positions of each puzzle piece and transmitted the positional information to the robotic arm, which then put each puzzle piece in its correct position. The algorithms were tested on 35-piece and 70-piece puzzles, achieving an average success rate of 87.1%. Compared with the human visual system, the proposed methods demonstrated enhanced accuracy when handling more complex textural images. Full article

In this paper, we propose a novel attack on image encryption for privacy-preserving deep neural networks (DNNs). Although several encryption schemes have been proposed for privacy-preserving DNNs, existing cipher-text-only attacks (COAs) have succeeded in restoring visual information from encrypted images. Image encryption using the Vision Transformer (ViT) is known to be robust against existing COAs due to the operations of block scrambling and pixel shuffling, which permute divided blocks and pixels in an encrypted image. However, the correlation between blocks in the encrypted image can still be exploited for reconstruction. Therefore, in this paper, a novel jigsaw puzzle solver-based attack that utilizes block correlation is proposed to restore visual information from encrypted images. In the experiments, we evaluated the security of image encryption for privacy-preserving deep neural networks using both conventional and proposed COAs. The experimental results demonstrate that the proposed attack is able to restore almost all visual information from images encrypted for being applied to ViTs. Full article

For manipulating heat flow according to human desire, thermal metamaterial structures (meta-structures) have attracted growing interest. Based on the transformation thermotics and the effective medium approximation theory, we designed and fabricated a convertible thermal meta-structural device to demonstrate that multiple different heat-flow manipulations could be conducted using a single thermal meta-structural device. The convertible meta-structures were designed by discretizing a two-dimensional plane and separating multiple square unit modules with stripe-shaped dissimilar materials of the Polydimethylsiloxane (PDMS) and solid resin with surface metallized copper (Cu). The convertible thermal meta-structure device with a relatively high geometric accuracy was fabricated via a proposed hybrid manufacturing path of “Stereolithography Apparatus (SLA) 3D printing—electroless plating—electroplating—thermally insulated packaging”. The thermal manipulation features were numerically simulated and preliminarily verified by experimental testing. Using multiple dispersed square unit modules to replace an annular region of the thermal meta-structure exhibited different thermal flow functions, including thermal cloak, thermal concentration, thermal rotation, and thermal dispersion, through the unique geometric design of the heat-flow transfer direction within each module. By rotating each square unit module at a specific angle and arranging the modules, similar to a “jigsaw puzzle”, the convertibility among different thermal manipulation functions was achieved. This path is anticipated to provide a new strategy for multifunctional meta-structures in thermo-physics and its potential engineering applications. Full article

As in a jigsaw puzzle, the pieces put together place before us the drama of the proliferation of new conflicts. Such are the times of today when people try to justify war on the grounds of belonging to different and incompatible cultures. Hence, there is an urgent need for a revival of intercultural dialogue and adequate education to foster it. Aware of the current challenge to peace, the two authors, who come from different geographical areas and cultures, seek through their research to highlight the educational value of Chiara Lubich’s charism, her work and that of the Focolare Movement she founded. To this end, they make use of the hermeneutic method of “text” analysis, understood as everything the person said, did and wrote. For this, they focus on what, with respect to the epistemology of education, consists in the real innovation, namely: the Lubich synoran, the Golden Rule as the axiological foundation of intercultural dialogue education, the Art of Loving as a method and the Cube of Peace as a teaching tool. Full article

Interpersonal brain synchrony (IBS) during cooperation has not been systematically investigated. To address this research gap, this study assessed neural synchrony during a cooperative jigsaw puzzle solving task using functional near-infrared spectroscopy (fNIRS)-based hyperscanning. IBS was measured for successful and failed tasks in 31 dyads in which the partners were familiar or unknown to each other. No significant difference in IBS was observed between the different types of cooperative partnership; however, stronger IBS within regions of the pars triangularis Broca’s area, right frontopolar cortex, and right temporoparietal junction was observed during task success. These results highlight the effect of better task performance on cooperative IBS for the first time and further extend understanding of the neural basis of cooperation. Full article

Spatial orientation is essential for daily life, but it deteriorates with aging. The present study was aimed at investigating age changes across the adult lifespan in the self-reported use of navigation aids and everyday orientation experiences, as well as investigating to what extent these are related to visuospatial working memory (VSWM) and self-reported wayfinding inclinations. A sample of 456 people aged 25–84 years rated how much they use navigation aids (maps, GPS, verbal directions), how much they went out, and how much they reached or lost their way to unfamiliar destinations (in 2016). Then, they performed the jigsaw puzzle test (VSWM) and questionnaires on sense of direction, pleasure in exploring, and spatial anxiety. The results showed that increasing age is related to a lower tendency to go out, fewer experiences of finding one’s way and getting lost, a lower level of GPS use, and increased verbal directions use. After age changes were accounted for, VSWM was related to aid use and orientation experiences (except for losing one’s way), wayfinding inclinations (especially spatial anxiety) to using a map, and orientation experiences. Overall, other than age, VSWM and one’s wayfinding attitudes can play a role–albeit it a modest one–in spatial behaviors. Full article

Dystroglycanopathy is a collective term referring to muscular dystrophies with abnormal glycosylation of dystroglycan. At least 18 causative genes of dystroglycanopathy have been identified, and its clinical symptoms are diverse, ranging from severe congenital to adult-onset limb-girdle types. Moreover, some cases are associated with symptoms involving the central nervous system. In the 2010s, the structure of sugar chains involved in the onset of dystroglycanopathy and the functions of its causative gene products began to be identified as if they were filling the missing pieces of a jigsaw puzzle. In parallel with these discoveries, various dystroglycanopathy model mice had been created, which led to the elucidation of its pathological mechanisms. Then, treatment strategies based on the molecular basis of glycosylation began to be proposed after the latter half of the 2010s. This review briefly explains the sugar chain structure of dystroglycan and the functions of the causative gene products of dystroglycanopathy, followed by introducing the pathological mechanisms involved as revealed from analyses of dystroglycanopathy model mice. Finally, potential therapeutic approaches based on the pathological mechanisms involved are discussed. Full article

This paper investigated the effect of task complexity on time estimation in the virtual reality environment (VRE) using behavioral, subjective, and physiological measurements. Virtual reality (VR) is not a perfect copy of the real world, and individuals perceive time duration differently in the VRE than they do in reality. Though many researchers have found a connection between task complexity and time estimation under non-VR conditions, the influence of task complexity on time estimation in the VRE is yet unknown. In this study, twenty-nine participants performed a VR jigsaw puzzle task at two levels of task complexity. We observed that as task complexity increased, participants showed larger time estimation errors, reduced relative beta-band power at Fz and Pz, and higher NASA-Task Load Index scores. Our findings indicate the importance of controlling task complexity in the VRE and demonstrate the potential of using electroencephalography (EEG) as real-time indicators of complexity level. Full article