Miracle-dz/UniFAR-FTUs huggingface dataset:
Therapeutic options for Covid – 19 : Pandemic – A Review

Covid-19 is an outbreak of a severe acute respiratory disorder which emerged in December 2019 in Wuhan, China. Since then the virus has spread to many countries and has become and pandemic. The mortality rate of the disease is very high but it varies from country to country depending on the medical facilities and the observance of isolation among the population. As the disease is very contagious many different treatment modalities have been tried. The therapeutic methods which are used are Ayurvedic and homeopathic along with that some Allopathic drugs are also used. Ayurvedic and homeopathy were found to be useful in asymptomatic patients rather than symptomatic patients. The drug which is used for treatment is antiviral drugs, protease inhibitors, antimalarial drugs, and neuraminidase inhibitors. But most promising results were obtained by using hydroxychloroquine, thus many countries are using this drug for treatment. Research related to vaccine development is still in progress. but there is still an absence of data regarding the effectiveness of these methods. Clinical trials need to be performed to prove the drug or the measure effective. While the search for a vaccine is still underway, preventive measures should be taken to curb the chain of infection. This includes the use of face mask, washing hands frequently, at least 1meter distance while in public places. This Literature review summarizes all the measures that have been used for the treatment of COVID 19 pandemic all around the world.
A Pore‐Scale Upscaling Approach for Laminated Sandstones using Minkowski Maps and Hydraulic Attributes

Digital core analysis offers unprecedented insight into fluid transport mechanisms at the pore scale, yet the integration of this knowledge into standard workflows requires the consideration of larger sample volumes. For hierarchical materials, this can be achieved by appropriate classification schemes and associated upscaling of pore‐scale transport properties to continuum measures. This work introduces a robust upscaling approach based on regional Minkowski measures or Minkowski maps with or without an additional hydraulic attribute. Data clustering of this feature vector field is achieved with a Gaussian mixture model leading to spatially compact rock types capturing the layering of the analyzed laminated sandstone. Other regional attribute fields like pore size, throat size, and volume/surface ratio are analyzed using these partitions. This is followed by a characterization of their transport properties, namely, electrical conductivity and permeability, for which an efficient sampling scheme utilizing spectral methods is introduced. We compare the upscaled transport properties on the basis of homogenization to full‐scale direct pore‐scale simulations for a thinly laminated sandstone and demonstrate very good agreement and large computational speed‐up.
Ageing Workforces, Ill‐health and Multi‐state Labour Market Transitions*

We provide novel evidence on the effects of ill-health on the dynamics of labour state transitions by considering retirement as mobility between full-time work, part-time work, self-employment and inactivity. We employ a dynamic multi-state model which accounts for state dependence and different types of unobservables. Our model allows for both individual heterogeneity and labour-state gravity as well as correlations between labour market states. We estimate this model on rich longitudinal data from the Household, Income and Labour Dynamics in Australia Survey. We find that both ill-health and health shocks greatly increase the probability of leaving full-time employment and moving into inactivity. Simulated dynamic trajectories suggest larger impacts of long-term health conditions than those of a one-off health shock and some evidence of health-driven retirement pathways via part-time work and self-employment. Our findings also indicate that the effects of health changes could be underestimated and the magnitude of true labour market state dependence overestimated if individual effects or labour dynamic transitions are not accounted for in the model.
WHITE OPPOSITION TO NATIVE NATION SOVEREIGNTY

Abstract Since first contact with Europeans, Native American nations have strived to maintain and strengthen their sovereignty. Yet, non-Native individuals and groups, as well as federal, state, and local governments, continue to challenge this sovereignty. Despite the critical importance of sovereignty, the only academic study focused on U.S. public attitudes toward Native nation sovereignty predated the rise of Native nation gaming and relied on samples from three universities. In our study, we surveyed over 2000 White Americans from across the United States to examine attitudes toward Native nation sovereignty. Of the many factors that may influence these attitudes, we focused on three: belief in “the casino Indian” stereotype, the perception that Native American interests conflict with the interests of Whites, and the presence of Native nation gaming in participants’ states. We find two significant models predicting attitudes towards Native nation sovereignty. First, greater endorsement of the casino Indian stereotype is associated with more negative attitudes toward Native nation sovereignty. This relationship is explained, at least in part, by the perception that Native American interests conflict with the interests of Whites. That is, the more White participants endorsed the casino Indian sterereotype, the more apt they were to believe that their interests conflict with Native Americans, which in turn is related to more negative attitudes towards Native nation sovereignty. The second model revealed that the presence of Native nation gaming in the participant’s state has important indirect implications for attitudes towards Native nation sovereignty. Specifically, White participants living in states with Native nation gaming are more likely to endorse the casino Indian stereotype, which is related to greater perceived conflict of interest with Native Americans, and, ultimately perceived conflict of interest is associated with more negative attitudes toward Native nation sovereignty. We situate our findings relative to group position theory and discuss practical implications for Native nation sovereignty.
Spatiotemporal Diversification of Tree Squirrels: Is the South American Invasion and Speciation Really That Recent and Fast?

Tree squirrels (Sciurinae, Sciurini) represent a diverse radiation that successfully colonized Europe, Asia and the Americas during the Miocene-Pliocene, but information on their evolutionary history remains unclear. In the Neotropics, they have been shown to exhibit the highest rate of diversification amongst all arboreal squirrels, with strikingly high species accumulation rates in the past 3 Mya. In this study, we investigated the tempo and mode of diversification of tree squirrels using a mitogenome dataset that includes 43 Sciurini species. Our results corroborate the date of origin of the tribe Sciurini around 14 Mya (13.4–15.5) but suggest that their ancestral area was most likely in North America. This is in contrast to previous findings that suggested that the ancestors of this tribe occupied Eurasia. We estimated that cladogenetic events leading to the Eurasian lineages occurred twice at 10.5 and 9.7 Mya. Current North American genera originated in a temporal window from 6.2–2.3 Mya, and the origin of the Neotropical radiation was estimated to have occurred around 6 Mya in northwestern South America, in the Pacific dominion. Remarkably, our results indicate that tree squirrels entered South America at an earlier date than previously estimated. This could have happened either through a land corridor connecting the Caribbean islands or through the Panamanian land bridge. Most cladogenetic events in Eurasia and North America appear to have occurred either late in the Miocene or in the Pleistocene, while the majority of Neotropical cladogenetic events occurred along the Pliocene—right after the South American invasion. We found a fairly constant speciation rate for tree squirrels (averaging 0.29), which contrasts with the peak of lineage accumulation observed in the Pliocene. The absence of fluctuations in the diversification rate may be the result of several extinction events that were responsible for equalizing the number of lineages maintained over time. Finally, we conclude that the South American invasion was not as recent as previously inferred, but the diversification there was indeed very fast.
ML-descent: An optimization algorithm for full-waveform inversion using machine learning

Full-waveform inversion (FWI) is a nonlinear optimization problem, and a typical optimization algorithm such as the nonlinear conjugate gradient or limited-memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) would iteratively update the model mainly along the gradient-descent direction of the misfit function or a slight modification of it. Based on the concept of meta-learning, rather than using a hand-designed optimization algorithm, we have trained the machine (represented by a neural network) to learn an optimization algorithm, entitled the “ML-descent,” and apply it in FWI. Using a recurrent neural network (RNN), we use the gradient of the misfit function as the input, and the hidden states in the RNN incorporate the history information of the gradient similar to an LBFGS algorithm. However, unlike the fixed form of the LBFGS algorithm, the machine-learning (ML) version evolves in response to the gradient. The loss function for training is formulated as a weighted summation of the L2 norm of the data residuals in the original inverse problem. As with any well-defined nonlinear inverse problem, the optimization can be locally approximated by a linear convex problem; thus, to accelerate the training, we train the neural network by minimizing randomly generated quadratic functions instead of performing time-consuming FWIs. To further improve the accuracy and robustness, we use a variational autoencoder that projects and represents the model in latent space. We use the Marmousi and the overthrust examples to demonstrate that the ML-descent method shows faster convergence and outperforms conventional optimization algorithms. The energy in the deeper part of the models can be recovered by the ML-descent even when the pseudoinverse of the Hessian is not incorporated in the FWI update.
Reliable Patterning, Transfer Printing and Post‐Assembly of Multiscale Adhesion‐Free Metallic Structures for Nanogap Device Applications

Patterning of metallic nanogaps with ultrasmall gap size on arbitrary substrates is of great importance for various applications in nanoelectronics, nanoplasmonics, and flexible optoelectronics. Common lithographic approaches suffer from limited resolution in defining ultrasmall nanogaps and restrictive available substrates for flexible and stretchable devices. In this work, a process portfolio to overcome the above limitations is proposed, enabling the fabrication of multiscale metallic nanogaps with reduced gap size on specific substrates for functional devices. The portfolio combines the recently developed sketch and peel lithography strategy, nanotransfer printing, and post‐mechanical assembly. Among the portfolio, the sketch and peel lithography strategy provides the unique capability to rapidly and reliably define multiscale adhesion‐free metallic nanostructures and nanogaps, which significantly facilitates the subsequent transfer printing process. Nanoplasmonic and nanoelectronic devices with ultrasmall nanogaps that are inaccessible with existing patterning approaches are fabricated to demonstrate the applicability of this fabrication strategy. The portfolio could also have potential for a variety of other applications in flexible and stretchable optics, electronics, and optoelectronics.
Coordination to Reduce Maternal and Infant Mortality in Tasikmalaya District

This research explains coordination to reduce maternal and infant mortality rates in Tasikmalaya District. The background of this study is the phenomenon of high maternal and infant mortality rates in West Java including in Tasikmalaya District. The method used in this research is descriptive with a qualitative approach carried out through interviews and observations of the parties involved in the expanding maternal and infant survival in Tasikmalaya District, reinforced by secondary data studies from the results of previous research, as well as data from related institutions. In order for the system in coordination to be effective it is necessary to improve in several aspects related to the system in coordination, in which there are three main dimensions in coordination, the dimensions of the mandate, systems and behaviors.
H Gene-based Molecular Characterization of Field Isolates of Canine Distemper Virus from Cases of Canine Gastroenteritis

Background: Canine distemper virus (CDV) is one of the important causes for canine gastroenteritis. Its genome codes for six structural proteins N, P, M, F, H and L, of which H is important for viral pathogenesis. Availability of CDV molecular epidemiological data is sparse. Our study reports for the first time, isolation of enteric CDV from India and its molecular epidemiology. Methods: We isolated the circulating wild type CDV from cases of canine gastroenteritis recorded during 2019 in India. Partial H gene of the isolates was amplified and phylogeny was reconstructed with other isolates from the NCBI database using MUSCLE from MEGA7. Results: The multiple sequence alignment of the partial H gene of circulating CDV with reference isolates revealed 88-95% nucleotide identity, and 83-91% amino acid identity along with the presence of Nde1 restriction site at position 1571-1576 that is typical of wild type CDV isolates. Interestingly, phylogenetic analysis revealed that the circulating CDV were grouped with three different lineages i.e., South America-2, Asia-4, and Asia-5/India-1 and distantly related with the vaccine strains. Our study strengthens the need for the development of a relevant vaccine comprising of circulating viral strains for effective vaccination strategies.
A CNN CADx System for Multimodal Classification of Colorectal Polyps Combining WL, BLI, and LCI Modalities

Colorectal polyps are critical indicators of colorectal cancer (CRC). Blue Laser Imaging and Linked Color Imaging are two modalities that allow improved visualization of the colon. In conjunction with the Blue Laser Imaging (BLI) Adenoma Serrated International Classification (BASIC) classification, endoscopists are capable of distinguishing benign and pre-malignant polyps. Despite these advancements, this classification still prevails a high misclassification rate for pre-malignant colorectal polyps. This work proposes a computer aided diagnosis (CADx) system that exploits the additional information contained in two novel imaging modalities, enabling more informative decision-making during colonoscopy. We train and benchmark six commonly used CNN architectures and compare the results with 19 endoscopists that employed the standard clinical classification model (BASIC). The proposed CADx system for classifying colorectal polyps achieves an area under the curve (AUC) of 0.97. Furthermore, we incorporate visual explanatory information together with a probability score, jointly computed from White Light, Blue Laser Imaging, and Linked Color Imaging. Our CADx system for automatic polyp malignancy classification facilitates future advances towards patient safety and may reduce time-consuming and costly histology assessment.
Speech Dereverberation Based on Improved Wasserstein Generative Adversarial Networks

In reality, the sound we hear is not only disturbed by noise, but also the reverberant, whose effects are rarely taken into account. Recently, deep learning has shown great advantages in speech signal processing. But among the existing dereverberation approaches, very few methods apply deep learning at the waveform level. In addition, in the case of sever reverberation, the conventional speech dereverberation methods perform poorly, such as MCLP (multi-channel linear prediction). We proposed a new speech dereverberation method in this paper, which is based on improved WGAN (Wasserstein Generative Adversarial Networks), called WGAN-GP, whose generator uses strided-convolutional networks and the discriminator is structured on DNNs. Due to the addition of the gradient penalty item, WGAN-GP improves the stability of training and the generalization of the model. In the case of severe reverberation, according to the experimental results, the proposed system can perform better than MCLP. As the proposed method based on WAGN-GP can improve speech quality, speech signal processing systems may be able to apply it to pre-processing stage.
Effects of Buoyancy and Wind Forcing on Southern Ocean Climate Change

Observations show that since the 1950s, the Southern Ocean has stored a large amount of anthropogenic heat and has freshened at the surface. These patterns can be attributed to two components of surface forcing: poleward-intensified westerly winds and increased buoyancy flux from freshwater and heat. Here we separate the effects of these two forcing components by using a novel partial-coupling technique. We show that buoyancy forcing dominates the overall response in the temperature and salinity structure of the Southern Ocean. Wind stress change results in changes in subsurface temperature and salinity that are closely related to intensified residual meridional overturning circulation. As an important result, we show that buoyancy and wind forcing result in opposing changes in salinity: the wind-induced surface salinity increase due to upwelling of saltier subsurface water offsets surface freshening due to amplification of the global hydrological cycle. Buoyancy and wind forcing further lead to different vertical structures of Antarctic Circumpolar Current (ACC) transport change; buoyancy forcing causes an ACC transport increase (3.1 ± 1.6 Sv; 1 Sv ≡ 106m3s−1) by increasing the meridional density gradient across the ACC in the upper 2000 m, while the wind-induced response is more barotropic, with the whole column transport increased by 8.7 ± 2.3 Sv. While previous research focused on the wind effect on ACC intensity, we show that surface horizontal current acceleration within the ACC is dominated by buoyancy forcing. These results shed light on how the Southern Ocean might change under global warming, contributing to more reliable future projections.
New novel food regulation and collaboration for innovation

Purpose –The purpose of this paper was to study the novel food (NF) industry in Europe and how regulations have affected companies’ collaboration and openness towards other actors during new product development. The research question, therefore, was “How do the European NF regulations affect radical innovation in the food industry? ” Design/methodology/approach – A multiphase mixed-methods design was used to combine three sets of data: the NF applications and copies of these from 1997 to 2018; the applications in the first 18 months of the revised NF regulation period after 2018 and interviews Findings – Interactions with research and development (R&D) suppliers are common during development of NF products. Ownership and protection of knowledge are important for companies’ openness during innovation and collaboration. The decentralised NF regulations from 1997–2017, with reduced possibilities for data protection, prevented innovation. However, both old and new NF regulations facilitates an easy route for a second-to-market approach. Companies of all sizes apply for NF-approved products under the new NF regulations, which ensure data protection. Originality/value – The NF regulations and their effect on radical food innovation has not previously been studied according to innovation management theory. Understanding various forms of selective partnership and collaboration among actors in the food industry is valuable for future growth.
Constraining Central Himalayan (Nepal) Fault Geometry Through Integrated Thermochronology and Thermokinematic Modeling

Constraining the subsurface structural geometry of the central Himalaya continues to prove difficult, even after the 2015 Gorkha earthquake and the resulting insights into the trajectory of the Main Himalayan thrust (MHT). To this end, we apply a thermokinematic model to evaluate four possible balanced cross section geometries based on three estimates of the MHT in central Nepal. We compare the effect of different décollement and duplex geometries on predicted cooling ages and compare these to new and published ages. We find that the best‐fit geometry able to reproduce the cooling ages at the surface is a hinterland‐dipping duplex, which has been translated over a mid‐crustal ramp located ~110 km north of the Main Frontal thrust. We find that the temporal evolution of the duplex and MHT mid‐crustal ramp both play an integral role in producing the observed cooling ages, implying that the common assumption that the active décollement and ramp geometry solely control the distribution of cooling ages is incorrect. Furthermore, results indicate that the Ramgarh‐Munsiari thrust was emplaced between 17 and ~10 Ma, followed by the Trishuli thrust. Duplex growth occurs between 6.5 and 0.75 Ma, with its constituent thrust sheets moving at variable rates between 10 and 42 mm/yr. Young out‐of‐sequence thrusting (5 km of displacement) in the hinterland produces a slightly improved fit to the cooling ages. Finally, the resulting thermal field modeled from our best‐fit geometry suggests a possible basis for the nucleation and rupture characteristics of the Gorkha earthquake.
Application of an Improved Hough Transform and Image Correction Algorithm in ACC

Numerous studies have shown that ACC (Augmentative and Alternative Communication), as a tool in language and communication training for children with autism, has effectively improved and played a positive role. ACC’s Picture Exchange System (PECS) provides an important support for the correction and feature recognition of language and training teaching cards. When designing the picture exchange function of ACC, this paper proposes a modified Hough transform and image correction algorithm suitable for teaching cards to solve the problems of large data calculation, time-consuming calculation, large space occupation and false peaks caused by traditional Hough transform algorithm in detecting straight lines, which also optimizes the interactive experience of the teaching scene. Finally, we design two experiments to compare and analyse the classic Hough transform, random Hough transform and improved Hough transform. Experimental results show that the improved Hough transform algorithm has superior performance in terms of execution efficiency and accuracy of line detection.
Redesign of substrate selection in glycopeptide antibiotic biosynthesis enables effective formation of alternate peptide backbones.

Non-ribosomal peptide synthesis is capable of utilizing a wide range of amino acid residues due the selectivity of adenylation (A)-domains. Changing the selectivity of A-domains could lead to new bioactive non-ribosomal peptides, although remodeling efforts of A-domains are often unsuccessful. Here, we explored and successfully reengineered the specificity of the module 3 A-domain from glycopeptide antibiotic biosynthesis to change the incorporation of 3,5-dihydroxyphenylglycine into 4-hydroxyphenylglycine. These engineered A-domains remain selective in a functioning peptide assembly line even under substrate competition conditions, and indicating a possible application of these for the future redesign of GPA biosynthesis.