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The redescription of Malerisaurus robinsonae (Archosauromorpha: Allokotosauria) from the Upper Triassic lower Maleri Formation, Pranhita-Godavari Basin, India
No full textAllokotosauria, a clade of non-archosauriform archosauromorphs with a broad diversity of body plans, plays a crucial role in better understanding the evolutionary history of early diverging stem-archosaurs. Here we provide a detailed redescription of Malerisaurus robinsonae, a malerisaurine allokotosaur from the middle Carnian—lowermost Norian lower Maleri Formation, Pranhita-Godavari Basin, India. The new anatomical information available from recently discovered and well-preserved skeletons of various allokotosaurs, such as Azendohsaurus madagaskarensis, Shringasaurus indicus, Puercosuchus traverorum, and Malerisaurus-like taxa, and their comparison with Malerisaurus robinsonae enriches our understanding of the anatomy of this species. To reassess the phylogenetic relationships of Malerisaurus robinsonae, we revised its scorings and included eight additional allokotosaurian species to the already most comprehensive phylogenetic dataset focused on Permo-Triassic archosauromorphs. We modified 70 scorings for Malerisaurus robinsonae and the new analysis recovered this species at the base of Malerisaurinae and this group as the earliest branch of Azendohsauridae. Pamelaria dolichotrachela is found as the earliest diverging non-malerisaurine azendohsaurid and sister taxon to the Shringasaurus indicus + Azendohsaurus spp. clade. Trilophosaurid interrelationships are well resolved, with Teraterpeton hrynewichorum, Coelodontognathus ricovi, and Rutiotomodon tytthos as their successive earliest-branching species. The position of Anisodontosaurus greeri as a sister taxon to Variodens inopinatus bolsters long ghost lineages in the Late Triassic trilophosaurid record. A disparity analysis of tooth crown morphology shows that Allokotosauria is the most disparate Permo-Triassic archosauromorph clade, exploring the almost complete range of basic crown morphologies. Trilophosaurids occupy an area of the dental morphospace unique among archosauromorphs
The ties that bind us: Social networks and productivity in the factory
No full textWe use high frequency worker level productivity data from garment manufacturing units in India to study the effects of caste-based social networks on individual and group productivity when workers are complements in the production function. Using plausibly exogenous variation in the production lines\u27 caste composition for almost 35,000 worker-days, we find that a 1 percentage point (pp) increase in the share of own caste workers in the line increases daily individual productivity by at least 0.09 pp. The least efficient worker\u27s productivity, however, rises by almost 0.17 pp when the caste composition of the line becomes more homogeneous by 1 pp. These results are robust to unobservable heterogeneity in worker ability and line level trends. Production externalities, that induce greater effort through within-network peer effects, can potentially explain our findings
The undecidable charge gap and the oil drop experiment
No full textDecision problems in physics have been an active field of research for quite a few decades resulting in some interesting findings in recent years. However, such research investigations are based on a priori knowledge of theoretical computer science and the technical jargon of set theory. Here, I discuss a particular, but a significant, instance of how decision problems in physics can be realised without such specific prerequisites. I expose a hitherto unnoticed contradiction, that can be posed as as decision problem, concerning the oil drop experiment, thereby resolve it by refining the notion of ‘existence’ in physics. This consequently leads to the undecidability of the charge spectral gap through the notion of ‘undecidable charges’ which is in tandem with the completeness condition of a theory as was stated by Einstein, Podolsky and Rosen in their seminal work. Decision problems can now be realised in connection with basic physics, in general, rather than quantum physics, in particular, as per some recent claims
Therapeutic Role of Probiotics in Gut-Brain Axis Under Microgravity
No full textMicrogravity is a state of free fall which one experiences in space. Human-crewed missions are becoming more sophisticated in the ongoing times. The altered gravitational conditions exert several physiological changes in the astronauts. Among many, one of the significantly affected systems and least discussed so far is the neurological system. Earlier studies have shown that exposure to space condition leads to structural changes in the brain, including distorted neurons and apoptotic astrocytes. Recent studies show the velocity of the action potential is reduced. Hippocampal activity is disrupted leading to cognitive impairment. Neuro ocular change occurs in some astronauts. Probiotics like Bacillus coagulans and Lactobacillus sp. connect gut-brain axis. Several probiotics are effective in treating neurological structural disorders. To sum up, in orbital exploration, astronauts face challenges of cosmic radiation and microgravity, impacting neuronal morphology. Chronic low-dose X-ray exposure delays neurite outgrowth and induces apoptosis. Simulated microgravity intensifies these effects, causing a significant increase in late apoptotic neurons. Astrocytes exposed to microgravity undergo apoptosis, but surviving cells adapt. Microgravity induces cellular senescence in rat cells, mimicking aging. NASA Twin Study reveals cognitive declines post-microgravity. Probiotics show therapeutic potential in neurological disorders, influencing gene expression and apoptotic proteins. They alleviate neurodegeneration and delay senescence, emphasizing their role in neurological well-being. In this review we discuss baseline data in this area since few laboratories has started working on the effect of nanoparticles on probiotics under microgravity. This review would help us and others interested in this field worldwide to work cohesively in future. Graphical Abstract: (Figure presented.
Thermal signature of a helical molecule: Beyond nearest-neighbor electron hopping
No full textWe investigate, for the first time, the thermal signature of a single-stranded helical molecule that is described beyond usual nearest-neighbor electron hopping, by analyzing electronic specific heat. Depending on the hopping of electrons, two different kinds of helical systems are considered. In one case the hopping is confined within a few neighboring lattice sites which is referred to as short-range hopping helix, while in the other case, electrons can hop in all possible sites making the system a long-range hopping one. These two helices accurately emulate the structures of single-stranded DNA and protein molecules, respectively. Each helix geometry is exposed to a transverse electric field applied perpendicular to the helix axis. Due to this field, the system transforms into a correlated disordered one, resembling the well-known Aubry-André-Harper (AAH) model. The interplay among the helicity, higher-order hopping, and the electric field has significant impact on thermal response. Our comprehensive theoretical analysis reveals that, under low-temperature conditions, the short-range hopping helix exhibits greater sensitivity to temperature compared to the long-range hopping helix system. Conversely, the scenario reverses in the high-temperature limit. The thermal response of the helices can be modified selectively by means of the electric field, and the difference between the specific heats of the two helices gradually decreases with increasing the field strength. The molecular handedness, whether left-handed or right-handed, on the other hand does not have any appreciable effect on the thermal signature. In addition, we also explore a significant application of electronic specific heat (ESH). If the helix contains a point defect, then by comparing the results of perfect and defective helices, one can estimate the location of the defect, which might be useful in diagnosing bad cells and different diseases. Finally, we discuss the results of ESH by considering the spin degree of freedom and in the context of real biological helical systems
TIC: text-guided image colorization using conditional generative model
No full textImage colorization is a well-known problem in computer vision. However, due to the ill-posed nature of the task, image colorization is inherently challenging. Though several attempts have been made by researchers to make the colorization pipeline automatic, these processes often produce unrealistic results due to a lack of conditioning. In this work, we attempt to integrate textual descriptions as an auxiliary condition, along with the grayscale image that is to be colorized, to improve the fidelity of the colorization process. To the best of our knowledge, this is one of the first attempts to incorporate textual conditioning in the colorization pipeline. To do so, a novel deep network has been proposed that takes two inputs (the grayscale image and the respective encoded text description) and tries to predict the relevant color gamut. As the respective textual descriptions contain color information of the objects present in the scene, the text encoding helps to improve the overall quality of the predicted colors. The proposed model has been evaluated using different metrics like SSIM, PSNR, LPISPS and achieved scores of 0.917, 23.27,0.223, respectively. These quantitative metrics have shown that the proposed method outperforms the SOTA techniques in most of the cases
TTS: Hilbert Transform-Based Generative Adversarial Network for Tattoo and Scene Text Spotting
No full text—Text spotting in natural scenes is of increasing interest and significance due to its critical role in several applications, such as visual question answering, named entity recognition and event rumor detection on social media. One of the newly emerging challenging problems is Tattoo Text Spotting (TTS) in images for assisting forensic teams and for person identification. Unlike the generally simpler scene text addressed by current state-of-the-art methods, tattoo text is typically characterized by the presence of decorative backgrounds, calligraphic handwriting and several distortions due to the deformable nature of the skin. This paper describes the first approach to address TTS in a real-world application context by designing an end-to-end text spotting method employing a Hilbert transform-based Generative Adversarial Network (GAN). To reduce the complexity of the TTS task, the proposed approach first detects fine details in the image using the Hilbert transform and the Optimum Phase Congruency (OPC). To overcome the challenges of only having a relatively small number of training samples, a GAN is then used for generating suitable text samples and descriptors for text spotting (i.e., both detection and recognition). The superior performance of the proposed TTS approach, for both tattoo and general scene text, over the state-of-the-art methods is demonstrated on a new TTS-specific dataset (publicly available) as well as on the existing benchmark natural scene text datasets: Total-Text, CTW1500 and ICDAR 2015
Unambiguous discrimination of sequences of quantum states
No full textWe consider the problem of determining the state of an unknown quantum sequence without error. The elements of the given sequence are drawn with equal probability from a known set of linearly independent pure quantum states with the property that their mutual inner products are all real and equal. This problem can be posed as an instance of unambiguous state discrimination where the states correspond to that of all possible sequences having the same length as the given one. We calculate the optimum probability by solving the optimality conditions of a semidefinite program. The optimum value is achievable by measuring individual members of the sequence, and no collective measurement is necessary
Understanding contrast and assimilation: the two modes of human brightness perception and the conditions for their mutual transition through an experimental and modelling approach
No full textBrightness in a specific (target) region in the visual field is influenced by the brightness of its neighbouring regions. Depending on the nature of the adjacent regions, this brightness induction is often manifested as brightness contrast, wherein the contrast of the target region with the adjacent region is enhanced. However, a totally reverse effect may also be observed, known as brightness assimilation, wherein the brightness of the target region is averaged over the target and its neighbourhood. There are examples of visual illusions of both these types. For almost the last half a century, people tried to understand whether contrast and assimilation are the manifestation of a single phenomenon, i.e. whether both can be understood under the umbrella of a single unified model, or whether the two illusions are perceived through entirely different methods of computation by the human brain. Experiments have been performed in the past to examine intriguing transition from one of these two types of brightness induction to the other. However, whether it is a low or higher level visual experience is still not clear, though brightness perception is apparently a low-level vision phenomenon. Moreover, to the best of our knowledge, till date there exist neither a step-by-step quantitative systematic data on such transitional processes, nor a classical receptive field (the isotropic difference of Gaussian) based low-level visual modelling of such steps. The main purpose of the present paper is to meet this gap. We have studied with careful psychophysics experiment two such cases of transitions. In the first psychophysics experiment, we took a White illusion (WI) stimulus and converted it to a simultaneous brightness contrast illusion through different stages of semi-White illusion (SeWI) using twenty different comparator arrangements, and quantifying the illusory effect. In the second experiment, we used the shifted White illusion as the experimental stimuli and manipulated the aspect ratio (AR), of the target gray patch and found the transitional/threshold AR where the brightness assimilation illusion gets reversed to an brightness contrast illusion, while quantifying twelve different comparator arrangements. Finally, a linear centre surround receptive field model or, a difference of Gaussian (DoG) filter model is simulated to explain the variations of illusory effect produced under the different conditions of such stimuli. The isotropic DoG filter which is known to work well only for the brightness contrast based illusions, is interestingly found to fit well with brightness assimilation illusions as well, by suppression of the inhibitory surround of the classical DoG filter
A Comparative Analysis of Deep Learning Architectures for Segmentation in Lung
No full textThis study explores the application of deep learning techniques to segment lung computed tomography (CT) scans, with a focus on cases involving COVID-19 and lung tumors. Utilizing a diverse dataset encompassing a wide range of CT scans, we conduct an extensive evaluation of various state-of-the-art deep neural network architectures. Our experimental results demonstrate the high efficiency and accuracy of deep learning models in performing image segmentation tasks, achieving impressive dice scores of 95.12% and 82.89% on COVID-19 and lung tumor data, respectively. These findings highlight the signif-icant potential of deep learning in medical imaging applications. Furthermore, we conduct thorough ablation studies, meticulously analyzing the performance of each network architecture. These studies provide valuable insights into the specific strengths and limitations of different deep learning approaches, facilitating the identification of the most effective methods for lung CT scan segmentation. This research not only underscores the promising capabilities of deep learning in medical image analysis but also offers a detailed understanding of how various models can be optimized to enhance performance in clinical applications