Miracle-dz/UniFAR-FTUs huggingface dataset:
Complications of the endovascular management of acute ischemic stroke

: Acute ischemic stroke is a significant source of morbidity and mortality across the globe. Currently, the only US Food and Drug Administration approved medical treatment of acute ischemic stroke is intravascular (IV) alteplase. While IV thrombolysis has been shown to decrease morbidity and mortality from acute ischemic stroke, it is limited in both its efficacy in certain types of stroke, as well as in its generalizability. It has been shown that time to revascularization is one of the most important predictors of outcomes in acute ischemic stroke, and thus clinicians have turned to endovascular options in efforts to improve outcomes from stroke. Direct intra-arterial thrombolysis was one of the first of such efforts to improve efficacy rates and increase the timeline for thrombolytic therapy. More recently, investigators and clinicians have turned to newer endovascular options in attempts to further improve recanalization rates. Many different endovascular techniques have been employed and are growing exponentially in use. Examples include stenting, as well as mechanical thrombectomy with both older-generation devices and newer stent retrieval technology. While the majority of the literature focuses on the effectiveness of different techniques, such as recanalization rates and major overall outcomes such as death and disability, there is very little literature on the complications of the different techniques. The purpose of this article is to review the different forms of endovascular treatment of acute ischemic stroke and their associated complications.
STATEMENT OF RESEARCH INTERESTS

My research is in the area of algebraic combinatorics, with an emphasis on problems from commutative algebra and algebraic geometry. The connection between algebra and combinatorics has had many implications in both fields. In combinatorics the highlights include Stanley’s proofs of the upper bound conjecture [21] and the g-theorem [22] using the theory of Cohen-Macaulay rings and toric varieties. In algebraic geometry the theory of toric varieties provides an important class of examples, with connections to still more areas, such as integer programming [4], [25], and mirror symmetry in mathematical physics [3], [6]. A less obvious connection between the areas is through the theory of Hilbert schemes. This connection is most spectacularly illustrated in Mark Haiman’s recent (2000) proof of the n! -conjecture of algebraic combinatorics [10] using the Hilbert scheme of n points in the affine plane. Both in my thesis, and in more recent work, I have been studying similar interactions with Hilbert schemes. I use computers extensively in my research, both to develop conjectures and to produce examples. This involves both using computational algebra packages such as Macaulay 2 [9] and Maple, and writing code in C. The theory of Gröbner bases also plays an important in my work. A unifying theme in my research is the study of toric ideals and their initial ideals. The Baues problem in geometric combinatorics also plays an important role. One version of the Baues problem concerns polyhedral subdivisions of the convex hull of a point configuration. Of interest is the homotopy type of the poset of all subdivisions, and whether the set of all triangulations (the finest possible subdivisions) is connected by operations known as bistellar flips. Part of the Baues graph of a configuration of six point in the plane is shown in Figure 1. Variants of such flips are of interest in computational geometry, and in low dimensional topology, where they are known as Pachner moves. An excellent survey is [18]. My work concerns algebraic analogues of this question.
NVESTIGATION OF TECTONICS BY GRAVITY DETAILING

Mapping of fault patterns is an important part of geophysical exploration. A computerized digital template analysis method is described which tests gravity maps for the effects of faults by comparing measured gravity data with calculated master curves. The interpreted gravity data are incorporated in a tectonic map using geological symbols and units, for ready use by the geologists. Tectonics can be investigated by gravity detailing if the smallest undulations on the Bouguer map are taken into consideration. Up to now, residual and derivative gravity maps have explained gravity effects by assuming spherical bodies which are almost unknown in geology. The method discussed here uses tectonic elements, such as fault-blocks and dikes as a basis of interpretation instead of the spherical bodies of the conventional interpretation methods. Gravity data can be easily and relatively cheaply obtained in the early phases of exploration by area wide spot coverage following lines of easy access such as roads, etc. Seismic studies, by contrast, have the disadvantage of being executed along predetermined profile lines. Only after sufficient detailing do seismic profiles permit-if at all -an areal mapping of faults. Thus a tectonic map is obtained only at the end of a geophysical survey instead of being available prior to the planning of costly seismic profiles. The use of gravimetric data and their interpretation by the suggested method provides tectonic detail maps in the early phases of geophysical studies. In addition, this article discusses a general geophysical interpretation method, using the investigation of faults by gravity as an example. Applications of this method for different gravity and magnetics problems as well as for combined interpretations are outlined. Detailed case histories will be published in later articles.
Paleoecological Significance of the Banded Iron-Formation

Banded iron-formation (BIF) is rare in rocks younger than about 2 aeons (years X 10 9 ). It records a major episode of chemical iron sedimentation, however, at about 2 to 2.1 aeons, just before the deposition of the oldest oxidized terrestrial sediments. The great iron-formations of this age reflect dramatic events. Ferrous iron residual in stagnant oceans beneath an anoxygenous atmosphere may then have moved into the photic zone on a vast scale because of overturning instigated by climatic change. A previously limited, photosynthetic, procaryotic microbiota, dependent on ferrous iron to maintain ambient oxygen at tolerable levels, then expanded and diversified, converting the iron to insoluble ferric oxides.In the absence of biological silica secretion, the contemporaneous hydrosphere was saturated with H 4 SiO 4 , whose continuing precipitation was favored by near neutral pH. Ferric oxides were intermittently added. The episodicity of the iron-rich bands suggests cyclical changes in procaryotic populations, or rates of supply of ferrous iron, or both. Mechanical differences between geochemically similar contemporaneous BIFs imply variations in turbulence and depth of water. Geochemically varying facies of the same age suggest variations in availability of O 2 . With advanced biological oxygen mediation, continuing segregation of metabolic carbon, and increasing supplies of oxygen, the oceans were depleted of iron to become saturated with O 2 , which thereafter evaded to the atmosphere, giving rise to continental red beds. Rare Paleozoic BIF seems to be related to local euxinic conditions and volcanic sources of iron, reminiscent of Archean deposits. The apparently late Proterozoic deposits of the Rapitan (north-western Canada) and Jacadigo (southwestern Brazil) beds remain enigmas.
Efficient Adaptation of Large Vision Transformer via Adapter Re-Composing

The advent of high-capacity pre-trained models has revolutionized problem-solving in computer vision, shifting the focus from training task-specific models to adapting pre-trained models. Consequently, effectively adapting large pre-trained models to downstream tasks in an efficient manner has become a prominent research area. Existing solutions primarily concentrate on designing lightweight adapters and their interaction with pre-trained models, with the goal of minimizing the number of parameters requiring updates. In this study, we propose a novel Adapter Re-Composing (ARC) strategy that addresses efficient pre-trained model adaptation from a fresh perspective. Our approach considers the reusability of adaptation parameters and introduces a parameter-sharing scheme. Specifically, we leverage symmetric down-/up-projections to construct bottleneck operations, which are shared across layers. By learning low-dimensional re-scaling coefficients, we can effectively re-compose layer-adaptive adapters. This parameter-sharing strategy in adapter design allows us to significantly reduce the number of new parameters while maintaining satisfactory performance, thereby offering a promising approach to compress the adaptation cost. We conduct experiments on 24 downstream image classification tasks using various Vision Transformer variants to evaluate our method. The results demonstrate that our approach achieves compelling transfer learning performance with a reduced parameter count. Our code is available at \href{https://github.com/DavidYanAnDe/ARC}{https://github.com/DavidYanAnDe/ARC}.
Pleiotropy informed adaptive association test of multiple traits using genome‐wide association study summary data

Genetic variants associated with disease outcomes can be used to develop personalized treatment. To reach this precision medicine goal, hundreds of large‐scale genome‐wide association studies (GWAS) have been conducted in the past decade to search for promising genetic variants associated with various traits. They have successfully identified tens of thousands of disease‐related variants. However, in total these identified variants explain only part of the variation for most complex traits. There remain many genetic variants with small effect sizes to be discovered, which calls for the development of (a) GWAS with more samples and more comprehensively genotyped variants, for example, the NHLBI Trans‐Omics for Precision Medicine (TOPMed) Program is planning to conduct whole genome sequencing on over 100 000 individuals; and (b) novel and more powerful statistical analysis methods. The current dominating GWAS analysis approach is the “single trait” association test, despite the fact that many GWAS are conducted in deeply phenotyped cohorts including many correlated and well‐characterized outcomes, which can help improve the power to detect novel variants if properly analyzed, as suggested by increasing evidence that pleiotropy, where a genetic variant affects multiple traits, is the norm in genome‐phenome associations. We aim to develop pleiotropy informed powerful association test methods across multiple traits for GWAS. Since it is generally very hard to access individual‐level GWAS phenotype and genotype data for those existing GWAS, due to privacy concerns and various logistical considerations, we develop rigorous statistical methods for pleiotropy informed adaptive multitrait association test methods that need only summary association statistics publicly available from most GWAS. We first develop a pleiotropy test, which has powerful performance for truly pleiotropic variants but is sensitive to the pleiotropy assumption. We then develop a pleiotropy informed adaptive test that has robust and powerful performance under various genetic models. We develop accurate and efficient numerical algorithms to compute the analytical P‐value for the proposed adaptive test without the need of resampling or permutation. We illustrate the performance of proposed methods through application to joint association test of GWAS meta‐analysis summary data for several glycemic traits. Our proposed adaptive test identified several novel loci missed by individual trait based GWAS meta‐analysis. All the proposed methods are implemented in a publicly available R package.
COVID-19 Diagnosis: ULGFBP-ResNet51 approach on the CT and the Chest X-ray Images Classification

The contagious and pandemic COVID-19 disease is currently considered as the main health concern and posed widespread panic across human-beings. It affects the human respiratory tract and lungs intensely. So that it has imposed significant threats for premature death. Although, its early diagnosis can play a vital role in revival phase, the radiography tests with the manual intervention are a time-consuming process. Time is also limited for such manual inspecting of numerous patients in the hospitals. Thus, the necessity of automatic diagnosis on the chest X-ray or the CT images with a high efficient performance is urgent. Toward this end, we propose a novel method, named as the ULGFBP-ResNet51 to tackle with the COVID-19 diagnosis in the images. In fact, this method includes Uniform Local Binary Pattern (ULBP), Gabor Filter (GF), and ResNet51. According to our results, this method could offer superior performance in comparison with the other methods, and attain maximum accuracy.
CrowdLink: Crowdsourcing for Large-Scale Linked Data Management

Crowd sourcing is an emerging paradigm to exploit the notion of human-computation for solving various computational problems, which cannot be accurately solved solely by the machine-based solutions. We use crowd sourcing for large-scale link management in the Semantic Web. More specifically, we develop Crowd Link, which utilizes crowd workers for verification and creation of triples in Linking Open Data (LOD). LOD incorporates the core data sets in the Semantic Web, yet is not in full conformance with the guidelines for publishing high quality linked data on the Web. Our approach can help in enriching and improving quality of mission-critical links in LOD. Scalable LOD link management requires a hybrid approach, where human intelligent and machine intelligent tasks interleave in a workflow execution. Likewise, many other crowd sourcing applications require a sophisticated workflow specification not only on human intelligent tasks, but also machine intelligent tasks to handle data and control-flow, which is strictly deficient in the existing crowd sourcing platforms. Hence, we are strongly motivated to investigate the interplay of crowd sourcing, and semantically enriched workflows for better human-machine cooperation in task completion. We demonstrate usefulness of our approach through various link creation and verification tasks, and workflows using Amazon Mechanical Turk. Experimental evaluation demonstrates promising results in terms of accuracy of the links created, and verified by the crowd workers.
Cardiovascular networks: systems-based approaches to cardiovascular disease.

“If there is any area in which a network thinking could trigger a revolution, I believe that biology is it. ” — Albert Laszlo Barabasi 1 Traditional biological and biochemical studies deal with relatively few components, allowing intuitive reasoning to guide hypotheses and experiments. For example, a popular experimental protocol in cardiovascular research is to examine gene functions through the use of transgenic or gene-targeted mice. Although clearly informative, it is becoming increasingly clear that such studies alone are not sufficient to explain complex processes such as arrhythmias, heart failure, and atherogenesis. Even a basic behavior, the action potential of a cardiomyocyte, requires the coordinated actions of >20 different ion transporters and channels.2 Perturbing proteins individually will help establish their functions, but it will not provide a full understanding of how they function together (quantitatively, temporally, and spatially). For this, a more global analysis, in which the activities of all of the relevant proteins are tracked over time and then integrated into a quantitative mathematical model, is required to provide a deeper level of understanding of cardiomyocyte dynamics. A new branch of biology, called systems biology, seeks to identify the components of complex systems and to model their dynamic interactions.3 The approach arose in large part as a result of new technical and analytical developments. The Human Genome Project provided a biological “parts list,” and technologies such as massively parallel DNA sequencing, expression microarrays, and tandem mass spectrometric analyses of proteins and metabolites have made high-throughput analysis of biological systems feasible. To deal with the data explosion, novel statistical and other mathematical modeling approaches are being developed. Basically, systems-based approaches involve 4 steps. The first is to define the system to be examined (eg, a cardiomyocyte). The second is to identify the components of the system (eg, the set …
Tests enhance the transfer of learning.

Numerous learning studies have shown that if the period of time devoted to studying information (e.g., casa-house) includes at least 1 test (casa-? ), performance on a final test is improved-a finding known as the testing effect. In most of these studies, however, the final test is identical to the initial test. If the final test requires a novel demonstration of learning (i.e., transfer), prior studies suggest that a greater degree of transfer reduces the size of the testing effect. The authors tested this conjecture. In 2 experiments, 4th- or 5th-grade students learned to assign regions or cities to map locations and returned 1 day later for 2 kinds of final tests. One final test required exactly the same task seen during the learning session, and the other final test consisted of novel, more challenging questions. In both experiments, testing effects were found for both kinds of final tests, and the testing effect was no smaller, and actually slightly larger, for the final test requiring transfer. (PsycINFO Database Record (c) 2009 APA, all rights reserved).
A Human Lin− CD123+ CD127low Population Endowed with ILC Features and Migratory Capabilities Contributes to Immunopathological Hallmarks of Psoriasis

Innate lymphoid cells (ILC) are members of a heterogeneous family with a lymphoid origin that mimics the T helper (Th) cytokine profile. ILC are involved in early effector cytokine-mediated responses during infections in peripheral tissues. ILC also play an important role in chronic skin inflammatory diseases, including psoriasis. Although classical ILC express CD127, it has been recently reported that the presence of non-classical CD127− ILC populations and an early ILC precursor (EILP) CD127low. ILC development has predominately been investigated in mouse models. However, in humans, different transcription factors have been described for ILC identification. NFIL3 (nuclear factor, IL-3 regulated) is crucial for ILC development in response to IL-7. CD123 (IL-3Rα) is usually used to exclude basophils during ILC identification, however, it is unknown if in response to IL-3, NFIL3 could be relevant to induce ILC features in Lin− CD123+ populations in addition, is also unknown whether peripheral blood (PB) population with ILC features may have skin-homing potential to participate in skin inflammatory chronic diseases. Here, we report a Lin− CD123+ CD127low CD7+ CLA+ population that share some phenotypic properties with basophils, but expresses several transcription factors for ILC commitment such as inhibitor of DNA binding 2 (Id2), NFIL3, promyelocytic leukemia zinc finger (PLZF), thymocyte selection-associated high-mobility group box protein (TOX), and T cell factor-1 (TCF-1). In addition, this population expresses different ILC markers: CD132, CD90, CD161, α4 integrin, c-Kit, CRTH2, AhR, and IL-23R. IL-3 prevents apoptosis and increases their NFIL3, TOX, and PLZF expression. In PB, the CD123+ CD127low population is predominantly a conspicuous population that expresses T-bet and RORγt. The Lin− CD123+ CD127low population in PB has a limited Th type cytokine expression and highly expresses IL-8. The Lin− CD123+ CD127low population expresses skin-homing receptors (cutaneous lymphocyte antigen and CXCR4) and transmigrates through endothelial cells in response to SDF-1. An equivalent Lin− CD123low population was identified in control skin, which shows a broader phenotypic diversity and cytokine production, including IL-22 and IL-17. Remarkably, the CD123low population in the lesion and non-lesion skin of psoriasis patients expresses IL-17 and IL-22. Our findings suggest the identification of an alternative Lin− CD123+ CD127low population with ILC features endowed with migratory capabilities that might contribute to immunopathological hallmarks of psoriasis.
A formulation for fully resolved simulation (FRS) of particle-turbulence interactions in two-phase flows

A numerical formulation for fully resolved simulations of freely moving rigid particles in turbulent ows is presented. This work builds upon the ctitious-domain based approach for fast computation of uid-rigid par- ticle motion by Sharma & Patankar ((1) Ref. J. Compt. Phy. , (205), 2005). The approach avoids explicit calculation of distributed Lagrange multipliers to impose rigid body motion and reduces the computational overhead due to the particle-phase. Implementation of the numerical algorithm in co-located, nite-volume-base d, energy conserving fractional-step schemes on structured, Cartesian grids is presented. The numerical approach is rst validated for ow over a xed sphere at various Reynolds numbers and ow generated by a freely falling sphere under gravity. Grid and time-step convergence studies are per- formed to evaluate the accuracy of the approach. Finally, simulation of 125 cubical particles in a decaying isotropic turbulent ow is performed to study the feasibility of simulations of turbulent ows in the presence of freely moving, arbitrary-shaped rigid particles.
A Novel Approach to Reinstating Tolerance in Experimental Autoimmune Myasthenia Gravis Using a Targeted Fusion Protein, mCTA1–T146

Reinstating tissue-specific tolerance has attracted much attention as a means to treat autoimmune diseases. However, despite promising results in rodent models of autoimmune diseases, no established tolerogenic therapy is clinically available yet. In the experimental autoimmune myasthenia gravis (EAMG) model several protocols have been reported that induce tolerance against the prime disease-associated antigen, the acetylcholine receptor (AChR) at the neuromuscular junction. Using the whole AChR, the extracellular part or peptides derived from the receptor, investigators have reported variable success with their treatments, though, usually relatively large amounts of antigen has been required. Hence, there is a need for better formulations and strategies to improve on the efficacy of the tolerance-inducing therapies. Here, we report on a novel targeted fusion protein carrying the immunodominant peptide from AChR, mCTA1–T146, which given intranasally in repeated microgram doses strongly suppressed induction as well as ongoing EAMG disease in mice. The results corroborate our previous findings, using the same fusion protein approach, in the collagen-induced arthritis model showing dramatic suppressive effects on Th1 and Th17 autoaggressive CD4 T cells and upregulated regulatory T cell activities with enhanced IL10 production. A suppressive gene signature with upregulated expression of mRNA for TGFβ, IL10, IL27, and Foxp3 was clearly detectable in lymph node and spleen following intranasal treatment with mCTA1–T146. Amelioration of EAMG disease was accompanied by reduced loss of muscle AChR and lower levels of anti-AChR serum antibodies. We believe this targeted highly effective fusion protein mCTA1–T146 is a promising candidate for clinical evaluation in myasthenia gravis patients.