Interpretable CNN for ischemic stroke subtype classification with active model adaptation

Background TOAST subtype classification is important for diagnosis and research of ischemic stroke. Limited by experience of neurologist and time-consuming manual adjudication, it is a big challenge to finish TOAST classification effectively. We propose a novel active deep learning architecture to classify TOAST. Methods To simulate the diagnosis process of neurologists, we drop the valueless features by XGB algorithm and rank the remaining ones. Utilizing active learning framework, we propose a novel causal CNN, in which it combines with a mixed active selection criterion to optimize the uncertainty of samples adaptively. Meanwhile, KL-focal loss derived from the enhancement of Focal loss by KL regularization is introduced to accelerate the iterative fine-tuning of the model. Results To evaluate the proposed method, we construct a dataset which consists of totally 2310 patients. In a series of sequential experiments, we verify the effectiveness of each contribution by different evaluation metrics. Experimental results show that the proposed method achieves competitive results on each evaluation metric. In this task, the improvement of AUC is the most obvious, reaching 77.4. Conclusions We construct a backbone causal CNN to simulate the neurologist process of that could enhance the internal interpretability. The research on clinical data also indicates the potential application value of this model in stroke medicine. Future work we would consider various data types and more comprehensive patient types to achieve fully automated subtype classification.

Modal Analysis of Conceptual Microsatellite Design Employing Perforated Structural Components for Mass Reduction

Mass reduction is a primary design goal pursued in satellite structural design, since the launch cost is proportional to their total mass. The most common mass reduction method currently employed is to introduce honeycomb structures, with space qualified composite materials as facing materials, into the structural design, especially for satellites with larger masses. However, efficient implementation of these materials requires significant expertise in their design, analysis, and fabrication processes; moreover, the material procurement costs are high, therefore increasing the overall program costs. Thus, the current work proposes a low-cost alternative approach through the design and implementation of geometrically-shaped, parametrically-defined metal perforation patterns, fabricated by standard processes. These patterns included four geometric shapes (diamonds, hexagons, squares, and triangles) implemented onto several components of a structural design for a conceptual satellite, with a parametric design space defined by two scale factors and also two aspect ratio variations. The change in the structure’s fundamental natural frequency, as a result of implementing each pattern shape and parameter variation, was the selection criterion, due to its importance during the launcher selection process. The best pattern from among the four alternatives was then selected, after having validated the computational methodology through implementing experimental modal analysis on a scaled down physical model of a primary load-bearing component of the structural design. From the findings, a significant mass reduction percentage of 23.15%, utilizing the proposed perforation concept, was achieved in the final parametric design iteration relative to the baseline unperforated case while maintaining the same fundamental frequency. Dynamic loading analysis was also conducted, utilizing both the baseline unperforated and the finalized perforated designs, to check its capability to withstand realistic launch loads through applying quasi-static loads. The findings show that the final perforated design outperformed the baseline unperforated design with respect to the maximum displacements, maximum Von Mises stresses, and also the computed margin of safety. With these encouraging outcomes, the perforated design concept proved that it could provide an opportunity to develop low-cost satellite structural designs with reduced mass.

Impact of Covid-19 on Stock Market in Sub-Saharan Africa

Corona virus disease (COVID-19) which was declared by the World Health Organization as a global pandemic caused serious economic problem to all the countries including Sub-Saharan Africa. Given the negative impact of COVID19 on the world economy, this paper examined the impact of COVID19 related cases and death on stock exchange markets volatility in Sub-Saharan African countries. The study used the number of reported cases and death from four Sub-Saharan African countries viz Nigeria, South Africa, Kenya, and Botswana, reported cases and death from China and U.S. and all share index as a proxy of stock markets in four countries from 28 February 2020 to 21 December 2020. The study estimated GARCH 11, TGARCH 11, and EGARCH 11 since the variables are heteroskadestic in nature which makes the application of ARCH lausible; the selection criterion was based on Akaike, Schwarz, and Hannan info Criteria. The result shows that COVID19 confirmed cases and death do not affect the operation of the stock markets in Sub-Saharan African countries, but the volatility of the markets has increased within the period of analysis. Furthermore, Botswana and Kenya stock markets were affected by external cases from China. We therefore recommended that stock markets stakeholders in Sub-Saharan Africa should be more concern about health safety measures and be ready for any future pandemic that might affect the markets.

Linear-Time Temporal Answer Set Programming

In this survey, we present an overview on (Modal) Temporal Logic Programming in view of its application to Knowledge Representation and Declarative Problem Solving. The syntax of this extension of logic programs is the result of combining usual rules with temporal modal operators, as in Linear-time Temporal Logic (LTL). In the paper, we focus on the main recent results of the non-monotonic formalism called Temporal Equilibrium Logic (TEL) that is defined for the full syntax of LTL but involves a model selection criterion based on Equilibrium Logic, a well known logical characterization of Answer Set Programming (ASP). As a result, we obtain a proper extension of the stable models semantics for the general case of temporal formulas in the syntax of LTL. We recall the basic definitions for TEL and its monotonic basis, the temporal logic of Here-and-There (THT), and study the differences between finite and infinite trace length. We also provide further useful results, such as the translation into other formalisms like Quantified Equilibrium Logic and Second-order LTL, and some techniques for computing temporal stable models based on automata constructions. In the remainder of the paper, we focus on practical aspects, defining a syntactic fragment called (modal) temporal logic programs closer to ASP, and explaining how this has been exploited in the construction of the solver telingo, a temporal extension of the well-known ASP solver clingo that uses its incremental solving capabilities.

Evolving Access to Educational Materials

The purpose of this paper is to interrogate the ways in which the selection of educational materials results in implications that impact access to these materials. This is necessary considering the evolving nature of educational materials offered by traditional publishers, and the increase in the availability of online learning materials, among those, open educational resources. I begin by reviewing the existing literature on emerging problems and barriers to learners’ access to educational materials including textbooks, online learning resources, and open educational resources. The findings from the literature review confirm that learners are now engaging with an increasingly complex ecosystem of educational materials, both print and digital, in a multitude of differing forms and formats, with various terms of use and durations of sustained access. Educators have a variety of choices to make when considering the educational materials to be used in their courses, and while fitness for purpose still dominates as the most important selection criterion, ease and persistence of access are becoming important considerations. A model which encapsulates the findings considering the variety of educational materials is presented alongside a discussion about the specific considerations for each.

Karen Ever After: The Career & Legal Consequences of being the Racist White Lady in an Internet Meme

With the coupled crises of the COVID-19 pandemic and racial protest movements in 2020, the “Karen” meme gained national attention as more incidents were posted online. These incidents have shown to be destructive to all parties involved as victims often experience negative health effects while “Karens” experience doxing. This study investigated the defaming career and legal consequences following the release of video content on social media in which a white woman dubbed as a “Karen” displays racist behaviors. Utilizing a directed qualitative content analysis, the sourcing of incident content came from a study by Been Verified that evaluated 150 incidents. A 2-part data-collection was implemented utilizing Advanced Google Search Engine and Chan McNamarah’s research on racialized police communication. Incidents were subsequently processing using a selection criterion to be considered for consequence assessment. Out of 56 qualified incidents, 27% had discovered career consequences and 27% had discovered legal consequences. This research contributes to a largely undiscussed field in academia by providing an in-depth assessment on defaming Internet trends. It has implications for HR specialists and policymakers in making appropriate decisions to ensure accountability is taken in online matters. It also holds significance for Internet-users in understanding how one’s digital footprint can be perceived online.

A minimum transmitted load control method for shock isolation mounts with magnetorheological energy absorbers

This paper proposed a minimum transmitted load (MTL) control method for drop-induced shock isolation mounts (SIM) with magnetorheological energy absorbers (MREAs). MTL control method consists of two parts of maximum damping force (MDF) control and one part of constant acceleration (CA) control, which can make the payload stop after fully utilize MREA stroke (soft landing) with minimum transmitted load. The control algorithm of MTL control method is derived in a single-degree-of-freedom (SDOF) system. The relationship between the controllable velocity range of MTL control method and parameters of shock isolation mounts is also derived. An optimal control method selection criterion between Bingham number (BN) control method and MTL control method is developed. The performance of MTL control method and selection criterion are shown by applying to the SIM system with variable drop velocities and system parameters. Results shows that MTL control method has the minimum transmitted load and the selection criterion is feasible.

Gap-com: General model selection criterion for sparse undirected gene networks with non-trivial community structure

We introduce a new model selection criterion for sparse complex gene network modeling where gene co-expression relationships are estimated from data. This is a novel formulation of the gap statistic and it can be used for the optimal choice of a regularization parameter in graphical models. Our criterion favors gene network structure which differs from a trivial gene interaction structure obtained totally at random. We call the criterion the gap-com statistic (gap community statistic). The idea of the gap-com statistic is to examine the difference between the observed and the expected counts of communities (clusters) where the expected counts are evaluated using either data permutations or reference graph (the Erdős-Rényi graph) resampling. The latter represents a trivial gene network structure determined by chance. We put emphasis on complex network inference because the structure of gene networks is usually non-trivial. For example, some of the genes can be clustered together or some genes can be hub genes. We evaluate the performance of the gap-com statistic in graphical model selection and compare its performance to some existing methods using simulated and real biological data example.

An Inferential Aptness of a Weibull Generated Distribution and Application

In this article an attempt has been made to develop a flexible single parameter continuous distribution using Weibull distribution. The Weibull distribution is most widely used lifetime distributions in both medical and engineering sectors. The exponential and Rayleigh distribution is particular case of Weibull distribution. Here in this study we use these two distributions for developing a new distribution. Important statistical properties of the proposed distribution is discussed such as moments, moment generating and characteristic function. Various entropy measures like Rényi, Shannon and cumulative entropy are also derived. The kthkt⁢h order statistics of pdf and cdf also obtained. The properties of hazard function and their limiting behavior is discussed. The maximum likelihood estimate of the parameter is obtained that is not in closed form, thus iteration procedure is used to obtain the estimate. Simulation study has been done for different sample size and MLE, MSE, Bias for the parameter λλ has been observed. Some real data sets are used to check the suitability of model over some other competent distributions for some data sets from medical and engineering science. In the tail area, the proposed model works better. Various model selection criterion such as -2LL, AIC, AICc, BIC, K-S and A-D test suggests that the proposed distribution perform better than other competent distributions and thus considered this as an alternative distribution. The proposed single parameter distribution is found more flexible as compare to some other two parameter complicated distributions for the data sets considered in the present study.