Miracle-dz/UniFAR-FTUs huggingface dataset:
Advancing Pan-cancer Gene Expression Survial Analysis by Inclusion of Non-coding RNA

ABSTRACT Non-coding RNAs occupy a significant fraction of the human genome. Their biological significance is backed up by a plethora of emerging evidence. One of the most robust approaches to demonstrate non-coding RNA’s biological relevance is through their prognostic value. Using the rich gene expression data from The Cancer Genome Altas (TCGA), we designed Advanced Expression Survival Analysis (AESA), a web tool which provides several novel survival analysis approaches not offered by previous tools. In addition to the common single-gene approach, AESA computes the gene expression composite score of a set of genes for survival analysis and utilizes permutation test or cross-validation to assess the significance of log-rank statistic and the degree of over-fitting. AESA offers survival feature selection with post-selection inference and utilizes expanded TCGA clinical data including overall, disease-specific, disease-free, and progression-free survival information. Users can analyse either protein-coding or non-coding regions of the transcriptome. We demonstrated the effectiveness of AESA using several empirical examples. Our analyses showed that non-coding RNAs perform as well as messenger RNAs in predicting survival of cancer patients. These results reinforce the potential prognostic value of non-coding RNAs. AESA is developed as a module in the freely accessible analysis suite MutEx. Abbreviation: ACC: Adrenocortical Carcinoma (n = 92); BLCA: Bladder Urothelial Carcinoma (n = 412); BRCA: Breast Invasive Carcinoma (n = 1098); CESC: Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (n = 307); CHOL: Cholangiocarcinoma (n = 51); COAD: Colon Adenocarcinoma (n = 461); DLBC: Lymphoid Neoplasm Diffuse Large B-cell Lymphoma (n = 58); ESCA: Oesophageal Carcinoma (n = 185); GBM: Glioblastoma Multiforme (n = 617); HNSC: Head and Neck Squamous Cell Carcinoma (n = 528); KICH: Kidney Chromophobe (n = 113); KIRC: Kidney Renal Clear Cell Carcinoma (n = 537); KIRP: Kidney Renal Papillary Cell Carcinoma (n = 291); LAML: Acute Myeloid Leukaemia (n = 200); LGG: Brain Lower Grade Glioma (n = 516); LIHC: Liver Hepatocellular Carcinoma (n = 377); LUAD: Lung Adenocarcinoma (n = 585); LUSC: Lung Squamous Cell Carcinoma (n = 504); MESO: Mesothelioma (n = 87); OV: Ovarian Serous Cystadenocarcinoma (n = 608) PAAD: Pancreatic Adenocarcinoma (n = 185); PCPG: Pheochromocytoma and Paraganglioma (n = 179); PRAD: Prostate Adenocarcinoma (n = 500); READ: Rectum Adenocarcinoma (n = 172); SARC: Sarcoma (n = 261); SKCM: Skin Cutaneous Melanoma (n = 470); STAD: Stomach Adenocarcinoma (n = 443); TGCT: Testicular Germ Cell Tumours (n = 150); THCA: Thyroid Carcinoma (n = 507) THYM: Thymoma (n = 124); UCEC: Uterine Corpus Endometrial Carcinoma (n = 560); UCS: Uterine Carcinosarcoma (n = 57); UVM: Uveal Melanoma (n = 80)
Synaptic mitochondria regulate hair-cell synapse size and function

Sensory hair cells in the ear utilize specialized ribbon synapses. These synapses are defined by electron-dense presynaptic structures called ribbons, composed primarily of the structural protein Ribeye. Previous work has shown that voltage-gated influx of Ca2+ through CaV1.3 channels is critical for hair-cell synapse function and can impede ribbon formation. We show that in mature zebrafish hair cells, evoked presynaptic-Ca2+ influx through CaV1.3 channels initiates mitochondrial-Ca2+ (mito-Ca2+) uptake adjacent to ribbons. Block of mito-Ca2+ uptake in mature cells depresses presynaptic-Ca2+ influx and impacts synapse integrity. In developing zebrafish hair cells, mito-Ca2+ uptake coincides with spontaneous rises in presynaptic-Ca2+ influx. Spontaneous mito-Ca2+ loading lowers cellular NAD+/NADH redox and downregulates ribbon size. Direct application of NAD+ or NADH increases or decreases ribbon size respectively, possibly acting through the NAD(H)-binding domain on Ribeye. Our results present a mechanism where presynaptic- and mito-Ca2+ couple to confer proper presynaptic function and formation.
Critical appraisal of guidelines for coronary artery disease on dual antiplatelet therapy: More consensus than controversies

Dual antiplatelet therapy (DAPT) in the form of aspirin plus a P2Y12 inhibitor, when indicated, is one of the key treatments in coronary artery disease (CAD). Many recommendations on DAPT in patients with CAD based on current guidelines are largely inconsistent. In our current study, we aimed at systematically reviewing DAPT‐relevant clinical practice guidelines, and highlighting their commonalities and differences for better informed decision‐making.
Evolution & Development

Correspondence Kathryn Kavanagh, Department of Biology, University of Massachusetts Dartmouth, North Dartmouth 02747, MA. Email: kkavanagh@umassd.edu Abstract The relation of developmental plasticity to evolutionary diversification is a key component of evolutionary theory involving developmental bias, but the basis of the relationship varies among traits and among taxa. Here I review some scenarios of how structural integration during early organogenesis could influence this relationship. When condensations are highly integrated and dependent on each other during early organogenesis, both plasticity and evolution are restricted, for example size proportions in molar tooth rows and phalanges within a digit. When similar condensations develop and remain separate (in tracheal cartilages and feather buds), they show high levels of variation and diversity in number but not in shape and size, at least at early stages. When non‐similar structures form separately and then integrate while still undergoing patterning, high levels of plasticity (in number, size, shape; in rib uncinate processes) or new dimensions of ecologically‐significant variation (cusp offset, in mammal teeth) are seen. Although each of these structural integration scenarios is unique, the modulation of evolvability is detectable and informative. Parsing the influence of structural integration at these developmental levels, rather than later‐stage structural correlations or only through genetic covariation, may be necessary to advance understanding of evolvability of the phenotype.
XINA: Explainable Instance Alignment Using Dominance Relationship

Over the past few years, knowledge bases (KBs) like DBPedia, Freebase, and YAGO have accumulated a massive amount of knowledge from web data. Despite their seemingly large size, however, individual KBs often lack comprehensive information on any given domain. For example, over 70 percent of people on Freebase lack information on place of birth. For this reason, the complementary nature across different KBs motivates their integration through a process of aligning instances. Meanwhile, since application-level machine systems, such as medical diagnosis, have heavily relied on KBs, it is necessary to provide users with trustworthy reasons why the alignment decisions are made. To address this problem, we propose a new paradigm, explainable instance alignment (XINA), which provides user-understandable explanations for alignment decisions. Specifically, given an alignment candidate, XINA replaces existing scalar representation of an aggregated score, by decision- and explanation-vector spaces for machine decision and user understanding, respectively. To validate XINA, we perform extensive experiments on real-world KBs and show that XINA achieves comparable performance with state-of-the-arts, even with far less human effort.
Information management in interactive and non-interactive suspenseful storytelling

Suspense is one key feature in modern storytelling. One of the mechanisms to deliver a suspenseful experience to an audience is by means of controlling the information provided. The media, however, has a very strong impact on what kind of information can be delivered and how. Moreover, modern storytelling is usually conveyed interactively, in such a way that the audience is also part of the story. In this paper, we experiment and analyse the different impact of information management in interactive and non-interactive storytelling. We report on an experiment measuring the reported perceived amusement in interactive and non-interactive versions of a potentially suspenseful story, and we provide evidence that a passive, non-interactive audience usually prefers less information than an active interactive audience. The study provides informed insight on how these results could be used in real scenarios to deliver appropriate levels of information to enhance the perception of suspense.
Linear Kernel Tests via Empirical Likelihood for High-Dimensional Data

We propose a framework for analyzing and comparing distributions without imposing any parametric assumptions via empirical likelihood methods. Our framework is used to study two fundamental statistical test problems: the two-sample test and the goodness-of-fit test. For the two-sample test, we need to determine whether two groups of samples are from different distributions; for the goodness-of-fit test, we examine how likely it is that a set of samples is generated from a known target distribution. Specifically, we propose empirical likelihood ratio (ELR) statistics for the two-sample test and the goodness-of-fit test, both of which are of linear time complexity and show higher power (i.e., the probability of correctly rejecting the null hypothesis) than the existing linear statistics for high-dimensional data. We prove the nonparametric Wilks’ theorems for the ELR statistics, which illustrate that the limiting distributions of the proposed ELR statistics are chi-square distributions. With these limiting distributions, we can avoid bootstraps or simulations to determine the threshold for rejecting the null hypothesis, which makes the ELR statistics more efficient than the recently proposed linear statistic, finite set Stein discrepancy (FSSD). We also prove the consistency of the ELR statistics, which guarantees that the test power goes to 1 as the number of samples goes to infinity. In addition, we experimentally demonstrate and theoretically analyze that FSSD has poor performance or even fails to test for high-dimensional data. Finally, we conduct a series of experiments to evaluate the performance of our ELR statistics as compared to state-of-the-art linear statistics.
The use of student-copresented virtual guest speakers in entrepreneurial education

Abstract Students wishing to be entrepreneurs have a great need for role models to serve as inspiration and help them envision their future organization. Universities often use guest speakers for this purpose. The author introduces a methodology of using a library of audio tapes as a virtual guest speaker series, larger and more diversified than even the most well-connected university could attract. Students copresent with the executives by pairing the taped messages with student-created presentation visuals.
TRIZ AND HYBRIDIZATION ALGORITHMS FOR STUDENT CREATIVITY IMPROVEMENT

The ability to generate design ideas is vital for university students to learn. Many learning approaches to inculcate the sense of design creativity have been introduced by researchers. This paper discusses the use of TRIZ and hybridization algorithms in Product Design and Development course to stimulate students in formulating new design ideas. TRIZ concepts, including the Trend of Engineering System Evolution (TESE), S-Curved Main Parameter Value (MPV) and forty inventive principles were introduced to students in addition to hybridization algorithms. Upon the completion of the course, students were then enquired to come up with ideas for new product concept and present them in the form of poster as well as oral presentation. A reflective evaluation was then carried out in order to get the brief depiction about the effectiveness of the approach. It was observed that students felt more equipped and were able to propose many ideas and initiatives.
On Reproducible AI Towards reproducible research, open science, and digital scholarship in AI publications

Background: Artificial intelligence, like any science, must rely on reproducible experiments to validate results. Objective: To give practical and pragmatic recommendations for how to document AI research so that results are reproducible. Method: Our analysis of the literature shows that AI publications currently fall short of providing enough documentation to facilitate reproducibility. Our suggested best practices are based on a framework for reproducibility and recommendations for best practices given by scientific organizations, scholars, and publishers. Results: We have made a reproducibility checklist based on our investigation and described how every item in the checklist can be documented by authors and examined by reviewers. Conclusion: We encourage authors and reviewers to use the suggested best practices and author checklist when considering submissions for AAAI publications and conferences.
Reading Comprehension Application (RCA) On Smartphone Usage In Classroom

The primary objectives of this study were (1) to find out learners’ reading comprehension achievement after learning English using Reading Comprehension Application (RCA) on smart phone, (2) to find out if there is any significant effect of RCA on Smartphone usage in learning English. The findings revealed that learners gain higher achievement on their post-test (67.81) score rather than on the pre-test score (62.65). Furthermore, there was significant difference of pre-test and post-test mean score (Sig. level 0.001 < 0.05). The results constituted that there was improvement on learner’s reading comprehension achievement based on the pre-test and post-test findings presentation after learning English using Reading Comprehension Application (RCA) on smart phone. Keywords—Reading comprehension; Reading Comprehension Application (RCA); Smart phone
Tuning Feedback-Based Traffic Signal Controls

A growing problem in many cities is that the traffic demand fluctuates heavily during the day and that it grows larger as the years go by. This calls for, and the technology to easier measure traffic enables, more efficient traffic light controls that can handle a greater traffic demand but also be adaptive. Centralised control of traffic light might, even though it can be both adaptive and efficient, be costly to install and expand due to the required communication between junctions. Decentralised control however, might be cheaper to install and maintain while still being adaptive and efficient. This thesis explores the Proportional Allocation controller with regards to its tuning parameter under conditions imposed by e.g., network size and topology, and queue sensor length. Two aspects of its performance were measured: optimality and fairness. In addition to the original controller two modifications are proposed and evaluated. It was found that when simulating, smaller networks could be used to approximate bigger ones, and that the queue sensor length is of critical importance not to be too small. The proposed modifications were found to perform similarly to the original one even though it in principal should not. The results herein should give a good starting point of the optimal value of the tuning parameter in a real-world implementation. (Less)
A Survey on Network Intrusion Detection

Network security is any activity designed to protect the usability and integrity of your network and data. It includes both hardware and software technologies. Effective network security manages access to the network. It targets a variety of threats and stops them from entering or spreading on your network. Network security combines multiple layers of defenses at the edge and in the network. Each network security layer implements policies and controls. Authorized users gain access to network resources, but malicious actors is blocked from carrying out exploits and threats. Two types of network includes wired and wireless network. The common vulnerability that exists in both wired and wireless networks is an “unauthorized access” to a network. An attacker can connect his device to a network though unsecure hub/switch port. In this regard, wireless network are considered less secure than wired network, because wireless network can be easily accessed without any physical connection. Network security is a big topic and is growing into a high profile Information Technology (IT) specialty area. Security-related websites are tremendously popular with savvy Internet users. The popularity of security-related certifications has expanded. Esoteric security measures like biometric identification and authentication have become commonplace in corporate America. Many organizations still implement security measures in an almost haphazard way, with no well-thought out plan for making all the parts fit together. Computer security involves many aspects, from protection of the physical equipment to protection of electronic bits and bytes that make up the information that resides on the network.
Extraction of Structural and Semantic Data from 2D Floor Plans for Interactive and Immersive VR Real Estate Exploration

Three-dimensional reconstructions of indoor environments are useful in various augmented and virtual scenarios. Creating a realistic virtual apartment in 3D manually does not only take time, but also needs skilled people for implementation. Analyzing a floor plan is a complicated task. Due to the lack of engineering standards in creating these drawings, they can have multiple different appearances for the same building. This paper proposes multiple models and heuristics which enable fully automated 3D reconstructions out of only a 2D floor plan. Our study focuses on floor plan analysis and definition of special requirements for a 3D building model used in a Virtual Reality (VR) setup. The proposed method automatically analyzes floor plans with a pattern recognition approach, thereby extracting accurate metric information about important components of the building. An algorithm for mesh generation and extracting semantic information such as apartment separation and room type estimation is presented. A novel method for VR interaction with interior design completes the framework. The result of the presented system is intended to be used for presenting a large number of apartments to customers. It can also be used as a base for purposes such as furnishing apartments, realistic occlusions for AR (Augmented Reality) applications such as indoor navigation or analyzing purposes. Finally, a technical evaluation and an interactive user study prove the advantages of the presented system.
New directions in applied general equilibrium model calibration

This thesis develops extensions to current techniques in applied general equilibrium (AGE) model calibration that improve existing practice and expand the use of AGE modelling to economic history applications. Chapter I introduces the thesis. Chapter 2 summarizes the origin and practice of calibration in economics, focussing on its role in AGE modelling. Chapter 3 proposes two related sensitivity analysis procedures for AGE models: calibrated parameter sensitivity analysis (CPSA) and extended sensitivity analysis. Existing sensitivity techniques are incomplete because they only capture the robustness of the model's results to uncertainty in a subset of the parameters, the elasticities. The remaining parameters determine the model's static structure, but are ignored in the sensitivity literature. CPSA fills this gap. When combined with an existing elasticity sensitivity technique in 'extended sensitivity analysis,' CPSA permits sensitivity analysis with respect to uncertainty in the values of all of a model's parameters. Chapter 4 examines the significance of the data adjustments required for calibration. It proposes that the measure of this importance should be the effect of the adjustment algorithm on the statistical properties of the model results. Simulations show that the performance of various algorithms differs significantly under such criteria, and illustrate fora specific policy experiment the link between algorithm performance and the relative magnitudes of the data. The experiments imply that the choice of data adjustment procedure is an important, if neglected, component of calibration. Chapter 5 shows how AGE techniques can be adapted to explore decompositional issues in economic history. By incorporating information about the combined effect of several shocks to an economy in calibration, AGE models can quantify the relative contributions to change of each shock. Furthermore, the effects ol shocks are non-additive, so that the marginal contribution of a shock is conditional on the presence or absence of other shocks. Chapter 6 concludes.
Structured peer-to-peer-based publication and sharing of ontologies to automatically process SPARQL query on a semantic sensor network

In recent years, semantic sensor networks are proposed, which apply ontologies to provide query capabilities and data access and allow users to express their needs at a conceptual level. In such sensor networks, a large amount of web ontologies are separately created by sensors to represent their own knowledge. These ontologies are distributed in different sensors and provide knowledge for semantic queries. It has become a very pressing issue to locate the desired ontologies for a given semantic query. To address this issue, we propose an approach based on structured peer-to-peer protocol to publish shareable ontologies on different sensors and automatically discover the ontologies useful for a given SPARQL query. Therefore, if a SPARQL query is given, our approach can locate ontologies desired and further send the query to them to find out solutions for the query. In addition, if solutions can be found out from a web ontology published, our approach makes sure to discover the ontology and get the solutions from it for the query. We conduct three experiments to evaluate the approach, the results of which demonstrate that our approach is effective and efficient.
An invariant based passive testing approach for protocol data parts

Conformance of implementations to protocol specifications is essential to assure interoperability between peers in network communications. Monitoring or passive testing techniques are used when no access to the communication interfaces is available or when the normal operation of the system cannot be interrupted. Most monitoring techniques only consider control portion of exchanged messages, usually ignoring the data part. However, as protocols become more complex and message exchange more data intensive, testing for data relations and constraints between exchanged messages becomes essential. In this paper we propose a novel approach for defining such relations as properties called invariants and show how they can be tested directly on traces using logic programming. Experimental results for SIP protocol traces are provided
Analog-to-digital conversion that allows to increase the dynamic range a standard ADC using the properties of electrical signals

A method is proposed to significantly increase the dynamic range of current and voltage meters in the traction networks of railway transport. The method is based on the low entropy of signals of this type and is based on the calculation of samples whose amplitude was distorted due to the output beyond the ADC dynamic range. The approach with the solution of system of linear equations is considered. An approach without solving a system of linear equations is presented. The accuracy of the method is discussed at the end of the article.