Molecular Responses to Thermal and Osmotic Stress in Arctic Intertidal Mussels (Mytilus edulis): The Limits of Resilience

Increases in Arctic temperatures have accelerated melting of the Greenland icesheet, exposing intertidal organisms, such as the blue mussel Mytilus edulis, to high air temperatures and low salinities in summer. However, the interaction of these combined stressors is poorly described at the transcriptional level. Comparing expression profiles of M. edulis from experimentally warmed (30 °C and 33 °C) animals kept at control (23‰) and low salinities (15‰) revealed a significant lack of enrichment for Gene Ontology terms (GO), indicating that similar processes were active under all conditions. However, there was a progressive increase in the abundance of upregulated genes as each stressor was applied, with synergistic increases at 33 °C and 15‰, suggesting combined stressors push the animal towards their tolerance thresholds. Further analyses comparing the effects of salinity alone (23‰, 15‰ and 5‰) showed high expression of stress and osmoregulatory marker genes at the lowest salinity, implying that the cell is carrying out intracellular osmoregulation to maintain the cytosol as hyperosmotic. Identification of aquaporins and vacuolar-type ATPase transcripts suggested the cell may use fluid-filled cavities to excrete excess intracellular water, as previously identified in embryonic freshwater mussels. These results indicate that M. edulis has considerable resilience to heat stress and highly efficient mechanisms to acclimatise to lowered salinity in a changing world.

Using blockchain technology to extend the vendor managed inventory for sustainability

Nowadays, Information Technology (IT) is changing the way traditional enterprise management concepts work. One of the most dominant IT achievements is the Blockchain Technology. This technology enables the distributed collaboration of stakeholders for their interactions while fulfilling the security and consensus rules among them. This paper has focused on the application of Blockchain technology to enhance one of traditional inventory management models. The Vendor Managed Inventory (VMI) has been considered one of the most efficient mechanisms for vendor inventory planning by the suppliers. While VMI has brought competitive advantages for many industries, however its centralized mechanism limits the collaboration of a pool of suppliers and vendors simultaneously. This paper has studied the recent research for VMI application in industries and also has investigated the applications of Blockchain technology for decentralized collaboration of stakeholders. Focusing on sustainability issue for total supply chain consisting suppliers and vendors, it has proposed a Blockchain based VMI conceptual model. The different capabilities of this model for enabling the collaboration of stakeholders while maintaining the competitive advantages and sustainability issues have been discussed.

Innate Receptors Expression by Lung Nociceptors: Impact on COVID-19 and Aging

The lungs are constantly exposed to non-sterile air which carries harmful threats, such as particles and pathogens. Nonetheless, this organ is equipped with fast and efficient mechanisms to eliminate these threats from the airways as well as prevent pathogen invasion. The respiratory tract is densely innervated by sensory neurons, also known as nociceptors, which are responsible for the detection of external stimuli and initiation of physiological and immunological responses. Furthermore, expression of functional innate receptors by nociceptors have been reported; however, the influence of these receptors to the lung function and local immune response is poorly described. The COVID-19 pandemic has shown the importance of coordinated and competent pulmonary immunity for the prevention of pathogen spread as well as prevention of excessive tissue injury. New findings suggest that lung nociceptors can be a target of SARS-CoV-2 infection; what remains unclear is whether innate receptor trigger sensory neuron activation during SARS-CoV-2 infection and what is the relevance for the outcomes. Moreover, elderly individuals often present with respiratory, neurological and immunological dysfunction. Whether aging in the context of sensory nerve function and innate receptors contributes to the disorders of these systems is currently unknown. Here we discuss the expression of innate receptors by nociceptors, particularly in the lungs, and the possible impact of their activation on pulmonary immunity. We then demonstrate recent evidence that suggests lung sensory neurons as reservoirs for SARS-CoV-2 and possible viral recognition via innate receptors. Lastly, we explore the mechanisms by which lung nociceptors might contribute to disturbance in respiratory and immunological responses during the aging process.

On the Meta-Analysis Review Towards efficient mechanisms for resource, energy, and data management in the fog computing

Fog computing is an architecture that uses collaborative end-user edge devices to carry out a large amount of storage, transmission, configuration, and module function. In this computingenvironment, management issue is the process of managing, monitoring and optimizing the correlated components for improving the performance, availability, security and any fundamental operational requirement. The management strategies have a great impact on the fog computing, but, as far as we know, there is not a comprehensive and systematic study in this field. Hence, this paper classifies the management strategies into three main categories, including resource, energy and data management. In addition, it defines the new challenges in each of these categories. Finally, the differences between the reviewed strategies are investigated in terms of scalability,reliability, time, and queries attributes along with providing the main directions for future research.

Diagnosis of Melanoma Lesion Using Neutrosophic and Deep Learning

Melanoma is a kind of skin cancer which occurs due to too much exposure of melanocyte cells to the dangerous UV radiations, that gets damaged and multiplies uncontrollably. This is popularly known as malignant melanoma and is comparatively less heard of than certain other types of skin cancers; however it can be more detrimental as it swiftly spreads if not detected and attended at a primary stage. The differentiation between benign and melanocytic lesions sometimes may be confusing, but the symptoms of the disease can reasonably be discriminated by a profound investigation of its histopathological and clinical characteristics. In the recent past, Deep Convolutional Neural Networks (DCNNs) have advanced in accomplishing far better results. The necessity of the present day is to have faster and computationally efficient mechanisms for diagnosis of the deadly disease. This paper makes an effort to showcase a deep learning-based ‘Keras’ algorithm, which is established on the implementation of DCNNs to investigate melanoma from dermoscopic and digital pictures and provide swifter and more accurate result as contrasted to standard CNNs. The main highlight of this paper, basically stands in its incorporation of certain ambitious notions like the segmentation performed by a culmination of a moving straight line with a sequence of points and the application of the concept of triangular neutrosophic number based on uncertain parameters. The experiment was done on a total of 40,676 images obtained from four commonly available datasets— International Symposium on Biomedical Imaging (ISBI) 2017, International Skin Imaging Collaboration (ISIC) 2018, ISIC 2019 and ISIC 2020 and the end result received was indeed motivating. It attained a Jac score of 86.81% on ISIC 2020 dataset and 95.98%, 95.66% and 94.42% on ISBI 2017, ISIC 2018 and ISIC 2019 datasets, respectively. The present research yielded phenomenal output in most instances in comparison to the pre-defined parameters with the similar types of works in this field.

Coded Aperture Hyperspectral Image Reconstruction

In this work, we study and analyze the reconstruction of hyperspectral images that are sampled with a CASSI device. The sensing procedure was modeled with the help of the CS theory, which enabled efficient mechanisms for the reconstruction of the hyperspectral images from their compressive measurements. In particular, we considered and compared four different type of estimation algorithms: OMP, GPSR, LASSO, and IST. Furthermore, the large dimensions of hyperspectral images required the implementation of a practical block CASSI model to reconstruct the images with an acceptable delay and affordable computational cost. In order to consider the particularities of the block model and the dispersive effects in the CASSI-like sensing procedure, the problem was reformulated, as well as the construction of the variables involved. For this practical CASSI setup, we evaluated the performance of the overall system by considering the aforementioned algorithms and the different factors that impacted the reconstruction procedure. Finally, the obtained results were analyzed and discussed from a practical perspective.

Highly Diverse Shrub Willows (Salix L.) Share Highly Similar Plastomes

Plastome phylogenomics is used in a broad range of studies where single markers do not bear enough information. Phylogenetic reconstruction in the genus Salix is difficult due to the lack of informative characters and reticulate evolution. Here, we use a genome skimming approach to reconstruct 41 complete plastomes of 32 Eurasian and North American Salix species representing different lineages, different ploidy levels, and separate geographic regions. We combined our plastomes with published data from Genbank to build a comprehensive phylogeny of 61 samples (50 species) using RAxML (Randomized Axelerated Maximum Likelihood). Additionally, haplotype networks for two observed subclades were calculated, and 72 genes were tested to be under selection. The results revealed a highly conserved structure of the observed plastomes. Within the genus, we observed a variation of 1.68%, most of which separated subg. Salix from the subgeneric Chamaetia/Vetrix clade. Our data generally confirm previous plastid phylogenies, however, within Chamaetia/Vetrix phylogenetic results represented neither taxonomical classifications nor geographical regions. Non-coding DNA regions were responsible for most of the observed variation within subclades and 5.6% of the analyzed genes showed signals of diversifying selection. A comparison of nuclear restriction site associated DNA (RAD) sequencing and plastome data on a subset of 10 species showed discrepancies in topology and resolution. We assume that a combination of (i) a very low mutation rate due to efficient mechanisms preventing mutagenesis, (ii) reticulate evolution, including ancient and ongoing hybridization, and (iii) homoplasy has shaped plastome evolution in willows.

Edema, Fainting, and Strokes

High blood pressure in humans is often associated with heart failure, edema, strokes, and episodes of fainting. Giraffes never show these. Edema, the abnormal collection of fluid in the lower legs, is prevented in giraffes by a combination of thick basement membranes of capillary blood vessels, which probably reduce their permeability to proteins, a very high tissue pressure that resists flow of fluid out of capillaries, and efficient mechanisms for returning blood to the heart. Fainting occurs when blood flow (and thus oxygen and glucose supply) to the brain is reduced. When a giraffe lifts its head after drinking water there is a sudden reduction of blood flow to the head, and fainting should result. Fainting is avoided because the blood flow that remains is diverted completely to the brain by a unique arrangement of blood vessels and nerves, and by structures that maintain the perfusion pressure of the blood flowing through the brain. Strokes can be caused by rupture of small blood vessels in the brain when they are exposed to high blood pressure of the kind reached in the head of a giraffe when it drinks surface water. Rupture of brain blood vessels is prevented in giraffes by mechanisms that reduce pressure. The posture adopted while drinking, baroreceptor-mediated reduction in cardiac output, the effects of the carotid rete, diversion of blood away from the brain, an increase in cerebrospinal fluid pressure, and passive and active constriction of blood vessels, all contribute.

Flip a coin or vote? An experiment on the implementation and efficiency of social choice mechanisms

Corporate boards, experts panels, parliaments, cabinets, and even nations all take important decisions as a group. Selecting an efficient decision rule to aggregate individual opinions is paramount to the decision quality of these groups. In our experiment we measure revealed preferences over and efficiency of several important decision rules. Our results show that: (1) the efficiency of the theoretically optimal rule is not as robust as simple majority voting, and efficiency rankings in the lab can differ from theory; (2) participation constraints often hinder implementation of more efficient mechanisms; (3) these constraints are relaxed if the less efficient mechanism is risky; (4) participation preferences appear to be driven by realized rather than theoretic payoffs of the decision rules. These findings highlight the difficulty of relying on theory alone to predict what mechanism is better and acceptable to the participants in practice.