Miracle-dz/UniFAR-FTUs huggingface dataset:
An optical/NIR survey of globular clusters in early-type galaxies III. On the colour bimodality of GC systems

Context. The interpretation that bimodal colour distributions of globular clusters (GCs) reﬂect bimodal metallicity distributions has been challenged. Non-linearities in the colour to metallicity conversions caused for example by the horizontal branch (HB) stars may be responsible for transforming a unimodal metallicity distribution into a bimodal (optical) colour distribution. Aims. We study optical/near-infrared (NIR) colour distributions of the GC systems in 14 E/S0 galaxies. Methods. We test whether the bimodal feature, generally present in optical colour distributions, remains in the opti-cal/NIR ones. The latter colour combination is a better metallicity proxy than the former. We use KMM and GMM tests to quantify the probability that diﬀerent colour distributions are better described by a bimodal, as opposed to a unimodal distribution. Results. We ﬁnd that double-peaked colour distributions are more commonly seen in optical than in optical/NIR colours. For some of the galaxies where the optical ( g − z ) distribution is clearly bimodal, a bimodal distribution is not preferred over a unimodal one at a statistically signiﬁcant level for the ( g − K ) and ( z − K ) distributions. The two most cluster-rich galaxies in our sample, NGC 4486 and NGC 4649, show some interesting diﬀerences. The ( g − K ) distribution of NGC 4649 is better described by a bimodal distribution, while this is true for the ( g − K ) distribution of NGC 4486 GCs only if restricted to a brighter sub-sample with small K-band errors ( < 0.05 mag). Formally, the K-band photometric errors cannot be responsible for blurring bimodal metallicity distributions to unimodal ( g − K ) colour distributions. However, simulations including the extra scatter in the colour-colour diagrams (not fully accounted for in the photomet- ric errors) show that such scatter may contribute to the disappearance of bimodality in ( g − K ) for the full NGC 4486 sample. For the less cluster-rich galaxies results are inconclusive due to poorer statistics. Conclusions. A bimodal optical colour distribution is not necessarily an indication of an underlying bimodal metallicity distribution. Horizontal branch morphology may play an important role in shaping some of the optical GC colour distributions. However, we ﬁnd tentative evidence that the ( g − K ) colour distributions remain bimodal in the two cluster-rich galaxies in our sample (NGC 4486 and NGC 4649) when restricted to clusters with small K-band photo- metric errors. This bimodality becomes less pronounced when including objects with larger errors, or for the ( z − K ) colour distributions. Deeper observations of large numbers of GCs will be required to reach more secure conclusions.
Theoretical spectroscopic scan of the sensitivity of asymmetric slab waveguide sensors

An extensive theoretical analysis is carried out to investigate the variation of the sensitivity of optical slab waveguide sensors with the wavelength of the guided wave. We consider a three-layer waveguide as an optical sensor. The sensitivity for both polarizations of light: s-polarized light (TE) and p-polarized light (TM), is derived using the characteristic equation of the structure. The dispersion of the materials is taken into account to study the sensitivity spectroscopic scan over the near IR-range from 1.2 –2 μm. It is found that an optimum wavelength exists for each guiding layer thickness and this optimum value increases linearly with the thickness of the guiding layer.
When to stop computing and start investing

PurposeThe purpose of the study is to analyze when — while predicting the future price of a financial instrument — we should stop computations and start using this information for the actual investment.Design/methodology/approachWe derive the explicit formulas explaining how the resulting gain depends on the duration of computations.FindingsWe provide an algorithm that enables us to decide the computation time that leads to the largest possible gain.Originality/valueTo the best of our knowledge, this is the first solution to the problem. Following our recommendations will allow investors to select the computation time for which the resulting gain is the largest possible.
A survey of low-luminosity compact sources and its implication for the evolution of radio-loud active galactic nuclei – I. Radio data

We present a new sample of compact steep spectrum (CSS) sources with radio luminosity below 10 26 W Hz − 1 at 1.4 GHz; these are called low-luminosity compact (LLC) objects. The sources have been selected from the Faint Images of the Radio Sky at Twenty-cm (FIRST) survey and observed with the multi-element radio linked interferometer network (MERLIN) at the L and C bands. The main criterion used for selection was the luminosity of the objects, and approximately one-third of the CSS sources from the new sample have a value of radio luminosity comparable to Fanaroff–Riley type 1 sources (FR Is). About 80 per cent of the sources have been resolved and about 30 per cent have weak extended emission and disturbed structures when compared with the observations of higher-luminosity CSS sources. We have studied the correlation between radio power and linear size, and the redshift with a larger sample that also included published samples of compact objects and large-scale FR IIs and FR Is. In the radio power versus linear size diagram, the LLC objects occupy the space below the main evolutionary path of radio objects. We suggest that many of these might be short-lived objects, and their radio emission may be disrupted several times before they become FR IIs. We conclude that
A Lagrangian Mean Theory of Wave, Mean-Flow Interaction With Applications to Nonacceleration and Its Breakdown (Paper 9R1575)

A review is given of a new Lagrangian mean theory of wave transport. Attention is focused on the so-called ‘nonacceleration’ theorem, and it is shown that such a theorem arises naturally in the Lagrangian mean framework. Also discussed is a simple example of the Stokes drift, a concept which is central to nonacceleration. The Lagrangian mean theory substantially simplifies and unifies our understanding of wave driving in cases where nonacceleration is violated because of wave transience and dissipation. Moreover, the theory has given new insights in one particular case, that of Rossby gravity wave, meanflow interaction. These insights have successfully explained some hitherto unresolved paradoxes in the theory of the quasi-biennial oscillation of zonal wind in the equatorial stratosphere. Some brief remarks are also made concerning some of the outstanding difficulties of the theory in need of future investigation.
Neptune: An Automated System for Dark Ship Detection, Targeting, and Prioritization

The ability to detect dark ships at open-ocean scale requires enhanced space-based intelligence, surveillance, and reconnaissance capabilities. With the boom of commercial space-based sensing, the nation needs an automated process to meet the growing volume and velocity of data. Multimodal data from the variety of existing and proposed space-based sensor networks can be aggregated and fused to produce target-quality tracks on ships. These sensor modalities include synthetic aperture radar (SAR), electro-optical/infrared (EO/IR), and Automatic Identification System (AIS). In this article, we demonstrate the work of a Johns Hopkins University Applied Physics Laboratory (APL) team to automate recognition of target surface vessels from these modalities on a next-generation spaceflight processor to simulate on-orbit detection. These detections can be fused to form quality tracks that can then be used to detect dark ship anomalies via pattern-of-life analysis. Tracks formed over a continental or global scale motivate the need for further automated analysis since a significant amount of human effort would be needed to analyze thousands or tens of thousands of tracks in detail and in real time. To address this challenge, the APL team developed a suite of pattern-of-life tools that extract features from tracks and flag tracks that deviate too far from some learned definition of normality. national security challenge is finding ways to quickly and reliably locate and identify these ships anywhere in the world. The Automatic Identification System (AIS), a radio frequency (RF) system for identifying and locating
Re-examining the Planning Basis of Goal-driven Autonomy Problems

The study of goal-reasoning agents capable of integrated ac- tion and execution has received a great deal of attention in recent years. While practical implementations and theoretical insights of such agents have provided a wealth of flexible behavior in a variety of task environments, they tend to focus on complex environments that are far from classical planning assumptions. This paper formalizes classical planning prob- lems where an agent can change its goal(s) during execution. We identify the minimal changes to classical planning and formalize a model that supports “classical goal reasoning. ”
1 Model order reduction: basic concepts and notation

: This is the first chapter of a three-volume series dedicated to theory and application of Model Order Reduction (MOR). We motivate and introduce the basic concepts and notation, with reference to the two main cultural approaches to MOR: the system-theoretic approach employing state-space models and transfer function concepts (Volume 1), and the numerical analysis approach as applied to partial differential operators (Volume 2), for which projection and approximation in suitable function spaces provide a rich set of tools for MOR. These two approaches are complementary but share the main objective of simplifying numerical computations while retaining accuracy. Despite the sometimes different adopted language and notation, they also share the main ideas and key concepts, which are briefly summarized in this chapter. The material is presented so that all chapters in this three-volume series are put into context, by highlighting the specific problems that they address. An overview of all MOR applications in Volume 3 is also provided.
SKI Activates Wnt/ (cid:1) -Catenin Signaling in Human Melanoma 1

Overexpression of the oncoprotein SKI correlates with the progression of human melanoma in vivo . SKI is known to curtail the growth inhibitory activity of tumor growth factor (cid:1) through the formation of repressive transcriptional complexes with Smad2 and Smad3 at the p21 Waf-1 promoter. Here, we show that SKI also stimulates growth by activating the Wnt signaling pathway. From a yeast two-hybrid screen and immunoprecipitation studies, we identified the protein FHL2/DRAL as a novel SKI binding partner. FHL2, a LIM-only protein, binds (cid:1) -catenin and can function as either a transcriptional repressor or activator of the Wnt signaling pathway. SKI enhanced the activation of FHL2 and/or (cid:1) -cate-nin- regulated gene promoters in melanoma cells. Among the SKI targets were microphthalmia-associated transcription factor and Nr-CAM, two proteins associated with melanoma cell survival, growth, motility, and transformation. Transient overexpression of SKI and FHL2 in ski (cid:2) / (cid:2) melanocytes synergistically enhanced cell growth, and stable overexpression of SKI in a poorly clonogenic human melanoma cell line was suffi- cient to stimulate rapid proliferation, decreasing the number of cells in the G 1 phase of the cell cycle, and dramatically increasing clonogenicity, colony size and motility. Taken together, these results suggest that by targeting members of the tumor growth factor (cid:1) and (cid:1) -catenin pathways, SKI regulates crucial events required for melanoma growth, survival, and invasion.
Survey on Computational Humour

Humor is an important aspect of human civil-isation as it governs our daily lives. A large part of humor we see comes in form of text. Natural Language Processing is a fantastic tool to understand and replicate this phenomenon. Being able to understand humour in text can help machines separate the true meaning from the implied meaning. Humour also has the potential to make machines more human-like. In this work we work attempt to teach machines to detect and generate humor. We build a system to rate the humor quotient in Stand up comedy. Our model is able to predict the funniness on a scale of 0 to 4 with great accuracy (0.84 on Quadratic Weighted Kappa). Creating data sets for automatic measurement of humour quotient is difficult due to multiple possible interpretations of the content. As part of this project we release first tri-modal non-binary data set us-ing English Stand-up comedy. This a valuable resource for the Natural Language Processing and Machine Learning community for multi-modal humour and sentiment analysis. We also build a system that can make any sentence hyperbolic and further use that to generate hu-mour. Our first work got accepted to EMNLP 2021 main conference and the second work is getting submitted to EMNLP 2022.
Reproducibility Report for ACM SIGMOD 2021 Paper: “REDS: Rule Extraction for Discovering Scenarios”

The code and data provided allow to reproduce all results and plots from the original paper [1]. The code is relatively easy to run on a Windows machine, but more difficult to run on a different platform due to a few scripts and the limited availability of some tools (e.g., RTools , which provides a convenient tool-chain for building the exact R packages that the authors used, but that is only available on Windows platforms). As the scripts used to generate the plots include tens of thousands of individual experiments, running all the scripts can take more than one week on a modest machine.
Consensus Data Mining (CDM) Protein Secondary Structure Consensus Data Mining (CDM) Protein Secondary Structure Prediction Server: Combining GOR V and Fragment Database Prediction Server: Combining GOR V and Fragment Database Mining (FDM) Mining (FDM)

Abstract One of the challenges in protein secondary structure prediction is to overcome the cross-validated 80% prediction accuracy barrier. Here, we propose a novel approach to surpass this barrier. Instead of using a single algorithm that relies on a limited data set for training, we combine two complementary methods having different strengths: Fragment Database Mining (FDM) and GOR V. FDM harnesses the availability of the known protein structures in the Protein Data Bank and provides highly accurate secondary structure predictions when sequentially similar structural fragments are identified. In contrast, the GOR V algorithm is based on information theory, Bayesian statistics, and PSI-BLAST multiple sequence alignments to predict the secondary structure of residues inside a sliding window along a protein chain. A combination of these two different methods benefits from the large number of structures in the PDB and significantly improves the secondary structure prediction accuracy, resulting in Q3 ranging from 67.5 to 93.2%, depending on the availability of highly similar fragments in the Protein Data Bank.
Machine-Learning Analysis of Single-Cell RNA-Seq Biomarkers in Gastric Cancer Caused By Helicobacter Pylori

Gastric cancer is one of the most prevalent and deadly cancers in the world. One of the biggest factors for this disease is Helicobacter pylori (H. pylori), infecting roughly half of the world’s population. However, there is a limited understanding of the H. pylori infection at single-cell level. In this study, single-cell RNA-Seq datasets from intestinal metaplasia samples were analyzed. Using bioinformatics methods, the cells were clustered and cell types were identified with cell type specific marker genes. For each cell type, H. pylori infected cells were compared with control cells using statistical analysis in order to find significant genes and pathways. Then, machine-learning (ML) approaches were used to build models to distinguish H. pylori positive and negative cells, and the severity of infection. It is found that H. pylori infection is linked to an increase in enterocytes and a decrease in pit mucous cells (PMCs). These changes may promote disease progression from gastritis to gastric cancer. Significantly differentially expressed genes and several pathways such as the MHC class II antigen presentation pathway and the PD-1 pathway were identified. The random forest-based models achieved an accuracy of higher than 97% for detecting positivity and severity. We identified the specific type of the host cells along with signaling pathways related to H. pylori infection and signaling pathways leading to gastric cancer. We demonstrated that ML methods are useful in detection of the affected by H. pylori PMC cells.
A Legacy Insurance Core Application Migration Example

—In microservice architectures, data is often hold re-dundantly to create an overall resilient system. Although the synchronization of this data proposes a signiﬁcant challenge, not much research has been done on this topic yet. This paper shows four general approaches for assuring consistency among services and demonstrates how to identify the best solution for a given architecture. For this, a microservice architecture, which implements the functionality of a mainframe-based legacy system from the insurance industry, serves as an example.
Indication of Traditional Chinese Spinal Orthopedic Manipulation

This paper deals with the definition of the traditional Chinese spinal orthopedic medicine and Traditional Chinese Spinal Orthopedic Manipulation (TCSOM), the function of the TCSOM, with a special focus on how to make a preliminary diagnosis of one or several spinal segments disorders, and the indications of traditional Chinese spinal orthopedic manipulation in different spinal segments. C4 and C5 ( C4,5 ): Shoulder joint pain and function limited, deltoid weakness, shoulder sensory disturbance. Indication of the traditional Chinese spinal orthopedic manipulation between C5 and C6 ( C5,6 ): Pain in anterolateral arm, anterolateral forearm and the thumb, biceps brachia weakness, thumb sensory disturbance. Indication of the traditional Chinese spinal orthopedic manipulation between C6 and C7 ( C6,7 ): Pain in neck, posterior shoulder, back, lateral arm, lateral forearm, index finger, middle finger, triceps brachia weakness, index finger and middle finger sensory disturbance.
BEHAVIORAL INTENTIONS TO ADOPT MOBILE BANKING: EMPIRICAL EXAMINATION ON Z GENERATION

This study aims to analyze and obtain empirical evidence about the influence of the use of Mobile Banking by students of the accounting study program as generation z through interest. This research was conducted at the Majapahit Islamic University, Mayjen Sungkono University, and STIE Al-Anwar. The data used in this study used a questionnaire. The sampling method used convenience sampling. The number of samples collected was 90 students. The data analysis techniques used by the researchers were descriptive statistics and inferential statistics. To analyze the data, we use Partial Least Square (PLS). PLS-SEM analysis uses the outer model and the inner model. The results of the study prove that the benefit variable does not affect the attitude variable. The convenience variable and the attitude variable have a significant positive effect on interest. Attitude variables do not affect the decision process variables of Accounting study program students in using Mobile Banking. Attitude variables have a significant positive effect on the decision process variables of students in the Accounting study program in using Mobile Banking through the interest variable.
Lung Cancer Analysis by Quality Measures

: Lung cancer has been and is very sensitive topic in the field of biomedical engineering. Lot of work is carried out to detect lung cancer at initial stages and also even sometimes at later stages because lung cancer symptoms are very much similar to the other lung diseases such as Pneumonia, Emphysema, Interstitial lung diseases. Hence lung cancer detection becomes important. Although lot of work is carried out on lung cancer using image processing. This paper also deals with the same using quality measures. The quality measures used are normalized cross correlation, structural contents and normalized absolute error, which helps for lung cancer analysis. The quality measures are applied on both healthy and cancerous lung images and then compared to take decision.
An Ant Colony Algorithm for Improving Energy E ﬃ ciency of Road Vehicles

: The number and interdependency of vehicle CO 2 reduction technologies, which can be employed to reduce greenhouse emissions for regulatory compliance in the European Union and other countries, has increasingly grown in the recent years. This paper proposes a method to optimally combine these technologies on cars or other road vehicles to improve their energy e ﬃ ciency. The methodological di ﬃ culty is in the fact that these technologies have incompatibilities between them. Moreover, two conﬂicting objective functions are considered and have to be optimized to obtain Pareto optimal solutions: the CO 2 reduction versus costs. For this NP-complete combinatorial problem, a method based on a metaheuristic with Ant Colony Optimization (ACO) combined with a Local Search (LS) algorithm is proposed and generalized as the Technology Packaging Problem (TPP). It consists in ﬁnding, from a given set of technologies (each with a speciﬁc cost and CO 2 reduction potential), among all their possible combinations, the Pareto front composed by those conﬁgurations having the minimal total costs and maximum total CO 2 reduction. We compare the performance of the proposed method with a Genetic Algorithm (GA) showing the improvements achieved. Thanks to the increased computational e ﬃ ciency, this technique has been deployed to solve thousands of optimization instances generated by the availability of these technologies by year, type of powertrain, segment, drive cycle, cost type and scenario (i.e., more or less optimistic technology cost for projected data) and inclusion of o ﬀ -cycle technologies. The total combinations of all these parameters give rise to thousands of distinct instances to be solved and optimized. Computational tests are also presented to show the e ﬀ ectiveness of this new approach. The outputs have been used as basis to assess the costs of complying with di ﬀ erent levels of new vehicle CO 2 standards, from the perspective of di ﬀ erent manufacturer types as well as vehicle users in Europe.
Slope Dynamics and Implications on Livelihoods: A Case study of the Kom Highlands in the North West Region of Cameroon

This paper examines the changing nature of slopes and their implications on livelihood activities (faming and settlements), in the Kom highlands. To arrive at this objective, the topographic map of the study area was got from the national institute of cartography and analysed to identify areas of steep, moderate and gentle slopes. Furthermore, the digital elevation model of the study area was realised as well as land use maps. The implications of slope types on livelihoods were determined from field observations, structured questionnaires and interviews. The findings revealed that slope traits are hardly considered when farming or constructing houses. The result of which has been poor farm yields, environmental hazards such as landslides and soil erosion. Based on field findings, a land use suitability map for the study area was realised and it is hoped that if land uses occupy appropriate slope locations, environmental problems such as landslides, soil erosion will be greatly reduced and agricultural productivity will increase.