GraphMineSuite: Enabling High-Performance and Programmable Graph Mining Algorithms with Set Algebra

We propose GraphMineSuite (GMS): the first benchmarking suite for graph mining that facilitates evaluating and constructing high-performance graph mining algorithms. First, GMS comes with a benchmark specification based on extensive literature review, prescribing representative problems, algorithms, and datasets. Second, GMS offers a carefully designed software platform for seamless testing of different fine-grained elements of graph mining algorithms, such as graph representations or algorithm subroutines. The platform includes parallel implementations of more than 40 considered baselines, and it facilitates developing complex and fast mining algorithms. High modularity is possible by harnessing set algebra operations such as set intersection and difference, which enables breaking complex graph mining algorithms into simple building blocks that can be separately experimented with. GMS is supported with a broad concurrency analysis for portability in performance insights, and a novel performance metric to assess the throughput of graph mining algorithms, enabling more insightful evaluation. As use cases, we harness GMS to rapidly redesign and accelerate state-of-the-art baselines of core graph mining problems: degeneracy reordering (by up to >2x), maximal clique listing (by up to >9x), k-clique listing (by 1.1x), and subgraph isomorphism (by up to 2.5x), also obtaining better theoretical performance bounds

Iterative Approximation of Common Fixed Points of Two Nonself Asymptotically Nonexpansive Mappings

Suppose that K is nonempty closed convex subset of a uniformly convex and smooth Banach space E with P as a sunny nonexpansive retraction and F:=F(T1)∩F(T2)={x∈K:T1x=T2x=x}≠∅. Let T1,T2:K→E be two weakly inward nonself asymptotically nonexpansive mappings with respect to P with two sequences {kn(i)}⊂[1,∞) satisfying ∑n=1∞(kn(i)-1)<∞(i=1,2), respectively. For any given x1∈K, suppose that {xn} is a sequence generated iteratively by xn+1=(1-αn)(PT1)nyn+αn(PT2)nyn, yn=(1-βn)xn+βn(PT1)nxn, n∈N, where {αn} and {βn} are sequences in [a,1-a] for some a∈(0,1). Under some suitable conditions, the strong and weak convergence theorems of {xn} to a common fixed point of T1 and T2 are obtained

Interactive Radial Volume Histogram Stacks for Visualization of Kidneys from CT and MRI

Optical parameter assignment via Transfer Functions (TF) is the sole interactive part in medical visualization via volume rendering. Being an interactive element of the rendering pipeline, TF specification has very important effects on the quality of volume-rendered medical images. However, TF specification should be supported by informative search spaces, interactive data exploration tools and intuitive user interfaces. Due to the trade-off between user control and TF domain complexity, integrating different features into the TF without losing user interaction is a challenging task since both are needed to fulfill the expectations of a physician. By addressing this problem, we introduce a semi-automatic method for initial generation of TFs. The proposed method extends the concept of recently introduced Volume Histogram Stack (VHS), which is a new domain constructed by aligning the histograms of the image slices of a CT and/or MR series. In this study, the VHS concept is extended by allowing the user to define an alignment axis using orthogonal multi planar reconstructions via simple, yet effective, interaction mechanisms. The construction of VHS according to the slices generated specifically for user defined search space allows the more informative integration of local intensity distribution, and better spatial positioning of the organ of interest into the TF. For testing, the proposed strategy is applied to kidney visualization from CT and MRI series. The performance of extended VHS domain is evaluated via intensity based TF design. Volumetric histogram based manual TF specifications are quantitatively compared to VHS based manual tweaking of original slices, and to extended-VHS based automatic TF design. The results show both quantitatively and qualitatively enhanced rendering quality for kidney visualization

Influence of Distance Transform on Classification Based Segmentation of Abdominal Organs from MRI

Segmentation of abdominal organs from MR images can be performed using two- or three- dimensional (2D or 3D) methods. 2D methods are less sensitive to volumetric anisotropy than 3D methods. Also they have the advantage of direct integration to the clinical scheme based on manual delination. One of the most important factors that affects the performance of 2D methods is the extraction and usage of similatiries between adjacent image slices. In this paper, the effects of the use of distance transform as adjacent slice similarity indicatir on performance is discussed. Considering classification based segmentation of abdominal organs, images modified by distance transform are used to extract features. Application of the same classification strategy to modified and original images show the advantage of the usage of the distance transform on performance

A Comparative Study on Minimizing False-Positive Error for Abdominal Organ Segmentation from MRI

Segmentation of abdominal organs from magnetic resonance data sets is an essential task for several medical procedures and analysis. When this process is done manually, it requires an expert radiologist's time and experience. Classification of organs by using several features for segmentation is a known technique. In recent years, for different application fields it is shown that hierarchical classification systems are more successful than composite feature-single classifier systems. The success of hierarchical systems in medical image segmentation is directly related to the reduction of false positive error in every level of the hierachy. In this paper, 3 different algorithms of Adaboost (Adaptive Boosting) method: Real, gentle and modest are compared in terms of their false positive error performance. Performance metrics are obtained for each organ and the dependence of false positive error on the selected algorithm is examined

Effects of Ecballium elaterium on brain in a rat model of sepsis-associated encephalopathy

Despite recent advances in antibiotic therapy, sepsis remains a major clinical challenge in intensive care units. Here we examined the anti-inflammatory and antioxidant effects of Ecballium elaterium (EE) on brain, and explored its therapeutic potential in an animal model of sepsis-associated encephalopathy (SAE) [induced by cecal ligation and puncture (CLP)]. Thirty rats were divided into three groups of 10 each: control, sepsis, and treatment. Rats were subjected to CLP except for the control group, which underwent laparatomy only. The treatment group received 2.5 mg/kg EE while the sepsis group was administered by saline. Twenty-four hours after laparotomy, animals were sacrificied and the brains were removed. Brain homogenates were prepared to assess interleukin 1beta (IL-1β), interleukin 6 (IL-6), tumor necrosis factor alpha (TNF-α), total antioxidant capacity (TAC), and total oxidant status (TOS). Brain tissue sections were stained by hematoxylin and eosin (H&E) to semi-quantitatively examine the histopathologic changes such as neuron degeneration, pericellular/perivascular edema and inflammatory cell infiltration in the cerebral cortex. We found a statistically significant reduction in brain tissue homogenate levels of TNF-α 59.5 ± 8.4/50.2 ± 6.2 (p = 0.007) and TOS 99.3 ± 16.9/82.3 ± 7.8 (p = 0.01) in rats treated with EE; although interleukin 6 levels were increased in the treatment group compared to the sepsis group, this was not statistically significant. Neuronal damage (p = 0.00), pericellular/perivascular edema and inflammatory cell infiltration (p = 0.001) were also significantly lower in the treatment group compared to those in the sepsis group. These data suggest that Ecballium elaterium contains some components that exert protective effects against SAE in part by attenuating accumulation of proinflammatory cytokines, which may be important contributors to its anti-inflammatory effects during sepsis

Facial diplegia: etiology, clinical manifestations, and diagnostic evaluation

ABSTRACT Objective Facial diplegia (FD) is a rare neurological manifestation with diverse causes. This article aims to systematically evaluate the etiology, diagnostic evaluation and treatment of FD. Method The study was performed retrospectively and included 17 patients with a diagnosis of FD. Results Patients were diagnosed with Guillain-Barré syndrome (GBS) (11), Bickerstaff’s brainstem encephalitis (1), neurosarcoidosis (1), non-Hodgkin’s Lymphoma (1), tuberculous meningitis (1) herpes simplex reactivation (1) and idiopathic (1). In addition, two patients had developed FD during pregnancy. Conclusion Facial diplegia is an ominous symptom with widely varying causes that requires careful investigation

Global Impact of COVID-19 on Stroke Care and IV Thrombolysis

Objective To measure the global impact of COVID-19 pandemic on volumes of IV thrombolysis (IVT), IVT transfers, and stroke hospitalizations over 4 months at the height of the pandemic (March 1 to June 30, 2020) compared with 2 control 4-month periods. Methods. We conducted a cross-sectional, observational, retrospective study across 6 continents, 70 countries, and 457 stroke centers. Diagnoses were identified by their ICD-10 codes or classifications in stroke databases. Results. There were 91,373 stroke admissions in the 4 months immediately before compared to 80,894 admissions during the pandemic months, representing an 11.5% (95% confidence interval [CI] −11.7 to −11.3, p \u3c 0.0001) decline. There were 13,334 IVT therapies in the 4 months preceding compared to 11,570 procedures during the pandemic, representing a 13.2% (95% CI −13.8 to −12.7, p \u3c 0.0001) drop. Interfacility IVT transfers decreased from 1,337 to 1,178, or an 11.9% decrease (95% CI −13.7 to −10.3, p = 0.001). Recovery of stroke hospitalization volume (9.5%, 95% CI 9.2–9.8, p \u3c 0.0001) was noted over the 2 later (May, June) vs the 2 earlier (March, April) pandemic months. There was a 1.48% stroke rate across 119,967 COVID-19 hospitalizations. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection was noted in 3.3% (1,722/52,026) of all stroke admissions. Conclusions. The COVID-19 pandemic was associated with a global decline in the volume of stroke hospitalizations, IVT, and interfacility IVT transfers. Primary stroke centers and centers with higher COVID-19 inpatient volumes experienced steeper declines. Recovery of stroke hospitalization was noted in the later pandemic months