Miracle-dz/UniFAR-FTUs huggingface dataset:
Variability investigation of quasars 4C 38.41 and 3C 345 at 92 cm: additional 14 observations

This paper provides additional evidence for the variability of the quasar 4C 38.41 based on 14 short observations at 92 cm using the Westerbork Synthesis Radio Telescope (WSRT). A fractional variability of 11.6 per cent was observed during the periods of 1989 May and from 1992 December to 1993 May. A brightness temperature of T B ∼ 2.6 or 5.2 X 10 1 8 δ - 3 K in 4C 38.41 can be estimated in the comoving frame, far in excess of the inverse Compton limit 10 1 2 K. A Doppler factor of δ ≥ 138 would be required by invoking the relativistic bulk motion. Combining the published six Westerbork North Sky Survey (WENSS) mosaic data at 92 cm, we conclude that 4C 38.41 has significant variability, which is unlikely to be caused by propagation effects. No variability was found for the quasar 3C 345.
Adaptive Control/Identification for Hybrid Systems Part I: with Bounded Discrete Regressor

In this and the companion paper [1], we propose a direct-adaptive-control framework for hybrid dynamical systems with unknown parameters. The approach addresses both the tracking-control and the parameter-estimation problems and relies on Lyapunov theory for hybrid systems. In this paper, we address these problems for systems with bounded discrete regressor. This assumption may appear restrictive at first sight, but its interest lies in that it yields a fairly simple static discrete adaptation law. Furthermore, parameter-estimation convergence is guaranteed under an original property of persistency of excitation tailored for hybrid systems, which is introduced here. The main results rely on Lyapunov theory for hybrid systems and establish uniform global asymptotic stability for the resulting closed-loop hybrid system. In the companion paper [1] the boundedness assumption on the regressor is relaxed and a high-order discrete adaptation law is proposed.
New Perspectives on Chronic Obstructive Pulmonary Disease

Abstract Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality worldwide; many recent advances have been made in many aspects of the disease. The aim of this article is to illustrate and discuss some of these advances in the management of different types of patients. Large-scale trials have confirmed that long-acting bronchodilator therapy, particularly using the combination of LABA/LAMA, remains the mainstay of COPD treatment, with special attention being paid to careful selection of inhaler devices. The initial choice of pharmacological therapy is based on the GOLD ABCD grouping of patients. It is very important to stress that there is a need to implement a management cycle because COPD is a chronic disease with varying clinical course and a high number of potential comorbidities that may affect morbidity and mortality. Therefore, regular reevaluation of the patient is mandatory. This allows identification of characteristics aimed at maximizing the benefits for a specific patient or a subset of patients. Within this context, the role of the blood eosinophil count as a marker of inhaled corticosteroids response to prevent future exacerbations in patients who, despite appropriate bronchodilator therapy, still suffer from them has been proven to be a useful simple biomarker in medication selection. These advances support the concept of precision medicine, with the goal that patients get the right medicine at the right time for the right reason. Finally, recent studies have shown that early life events may be of critical relevance for the development of COPD. With this as a background, concepts to identify individuals at risk and early identification of cases have become an important objective of current research with the hope of maximizing the effects of therapy and the possibility of impacting disease progression.
A Democratically Anonymous and Trusted Architecture for CTI Sharing using Blockchain

Cyber Threat Intelligence (CTI) sharing has become a significant issue with the increasing number of cyberattacks. In CTI sharing, one entity (e.g., an organisation or a user) intends to share specific threat information to another entity that might otherwise be unavailable to another entity. However, this process needs to address many challenges, including privacy, trust, and accountability. In this paper, we propose a novel blockchain-based architecture that facilitates the secure dissemination of CTI data. The motivation for this study is to provide a solution that can efficiently address privacy, trust, and accountability when sharing CTI among organisations as well as maintaining an intelligence-based informed decisions. We discuss the current problems within the domain of CTI sharing using blockchain, and our proposal leverages the salient properties of the blockchain, e.g., decentralised, cryptographic keys, immutability, etc., to address those issues. We discuss the detailed design of the proposed architecture. We demonstrate that our approach offers a more effective and efficient way of CTI sharing that has the potential to overcome the trust barriers, data privacy, and accountability issues inherent in this domain.
The Impact Of Covid-19 On Digital Sharia Banking In Padangsidimpuan City

The high level of direct transactions at Islamic banks during the Covid-19 pandemic is a common sight in Padangsidimpuan City. In fact, in the current 4.0 era, Islamic banks have provided various digital-based services to make it easier for customers to transact without having to come to Islamic banks, especially during the pandemic. This study aims to see the impact of the Covid-19 pandemic on the use of Digital Syariah Banking in Padangsidimpuan City. This study uses descriptive qualitative data analysis techniques with 400 samples. This study resulted that Covid-19 had no impact on the use of Digital Syariah Banking in Padangsidimpuan City. This is due to three factors, namely the public's view of Covid-19, security, and the location of Islamic banks.
Binary Black Widow Optimization Approach for Feature Selection

Feature selection is a process of reduction of irrelevant, negligible, noisy features from data sets so as to obtain better performance measurements with fewer features. Throughout the literature, various methods are presented that use different approaches to get through this difficult problem, prevalently. In this study, a binary variant of the Black Widow Optimization (BWO) is proposed in a wrapper mode for the purpose of feature selection. The BWO algorithm has early convergence ability on continuous problems and that characteristic is also effective for finding an optimum solution in feature selection problem. The proposed approach compared with state-of-the-art and widely used approaches such as Binary Particle Swarm Optimization (BPSO and VPSO), Binary Grey Wolf Optimization (BGWO1 and BGWO2). The performance of these algorithms is assessed over 20 benchmark data sets from the UCI repository. The results show that the proposed binary method can be utilized effectively in discrete problems such as feature selection.
Sequential decomposition of Stochastic Stackelberg games

In this paper, we consider a discrete-time stochastic Stackelberg game where there is a defender (also called leader) who has to defend a target and an attacker (also called follower). The attacker has a private type that evolves as a controlled Markov process. The objective is to compute the stochastic Stackelberg equilibrium of the game where defender commits to a strategy. The attacker’s strategy is the best response to the defender strategy and defender’s strategy is optimum given the attacker plays the best response. In general, computing such equilibrium involves solving a fixed-point equation for the whole game. In this paper, we present an algorithm that computes such strategies by solving lower dimensional fixed-point equations for each time t. Based on this algorithm, we compute the Stackelberg equilibrium of a security example.
Characterization of shear transformation zone volume during Orthogonal micro turning of Zr-based Bulk metallic glass

Bulk metallic glasses (BMGs) have unique superior properties as compared to their crystalline counterparts because of the disordered structure at the atomic scale. This study presents the experimental work on Zr-based BMGs during orthogonal micro-turning. The shear transformation zone (STZ) volume of the strained surface generated during machining was characterized by nanoindentaion technique. The STZ volume was found to be lower for the machined region than the unmachined region for all the cases of cutting speeds and feed values which suggest the densification of the atoms at the machined surface due to combined influence of machining and nanoindentation. The densification of atoms suggests the work hardening (strain hardening) phenomenon which is generally not visible for amorphous metallic alloys.
Citrus Sinensis Peel Pectin: A Novel Binder in Erythromycin Tablet Formulation

The aim of this study was to do comparative evaluation of citrus sinensis peel pectin as a pharmaceutical excipients (binder) in erythromycin tablet formulation. The orange peel pectin was extracted from the peel of citrus sinesis, dried, milled and the phytochemicals determined. The granules formulated were evaluated for micromeritic properties. The granules were compressed to tablets at the compression pressure of 30N/m 2 and later evaluated for hardness, friability, disintegration time, dissolution studies and release kinetics. The extracted orange peel pectin was found to contain flavonoids, carbohydrates and reducing sugar. However, alkaloid, anthraquinone, saponin, cardiac glycoside, terpenoid and tannin were found to be absent. The different batches of formulated erythromycin granules were free flowing with angle of repose between 20.07 3.74 to 20. 82 1.51. , bulk density (0.43 0.03 to 0.53 0.02); tapped density (0.51 0.05 to 0.61 0.03); compressibility index (8.12 3.57 to 13.93 6.20); Hausner’s ratio (1.14 0.07 to 1.25 0.19) and flow rate (0.55 0.11 to 0.94 0.13). All formulated erythromycin tablets were uniform in weight. Their hardness were satisfactory (4.5 0.02 to 6.7 0.05 kg/cm 2 ); friability (0.40 0.12 to 0.91 0.10%). Most of the tablets disintegrated within 15 minutes, except those formulated with 10% of the binders with Acacia 10% (20.1 .02 minutes), corn starch mucilage (CSM) 10% (21.4 0.03) and orange peel pection (OPP) 10% (25.4 0.05 minutes) respectively. Increase in the binder concentration resulted in a corresponding increase in hardness and disintegration time, but decrease in percentage friability. The dissolution of all batches of erythromycin tablets fitted into the Higuchi model release kinetics. Orange peel pectin exhibited good binding property comparable to those of the standard Acacia and Corn starch mucilage.
Gaps on the flow of the simplified path-preference cellular automaton model

The path-preference model is a cellular-automaton model to describe the dynamics of RNA polymerase II in transcription. The main difference from the standard traffic flow model is that it contains another preferential paths at some sites. In this paper, we propose an exact analysis for the simplest version of this model which consists on the minimal structure and removes stochastic factors. We find that the number of particles is dominant to the dynamics of this version and observed that there are not only expected phase shift but also several non-continuous gaps as the number of particles increases. By considering the behavior of limit cycles, we also determine the point where such gaps in the flow appear and the exact value of the flow.
EFFICIENT GLOBAL LOCALIZATION BY SEARCHING A BIT-ENCODED GRAPH

Abstract Global localization is the problem of finding a totally unknown robot pose given a known map and a set of observations relative to the robot. This is the combinatorial correspondence problem between map landmarks and observations, and its complete solution is an NP-hard problem that makes it computationally intractable when the size of the map increases. We propose the use of bit encoded graphs that take advantage of bit parallelism when solving instances of the deeply studied in graph theory Maximum Clique Problem (MCP). We have implemented and compared our solution with standard branch and bound heuristic search over the space of possible associations. Although the computational complexity of our algorithm is still exponential because it is complete, our results prove an impressive reduction of two orders of magnitude in required processing time thanks to the efficient underlying model, making it possible to deal with previously computationally intractable scenarios. Moreover, it is the first time (up to our knowledge) that this kind of technique is used in the robotics domain and it could possibly be applied to other problems such as path planning.
Dual active contour models for image feature extraction

Active contours are now a very popular technique for shape extraction, achieved by minimising a suitably formulated energy functional. Conventional active contour formulations suffer difficulty in appropriate choice of an initial contour and values of parameters. Recent approaches have aimed to resolve these problems, but can compromise other performance aspects. To relieve the problem in initialisation, an evolutionary dual active contour has been developed, which is combined with a local shape model to improve the parameterisation. One contour expands from inside the target feature, the other contracts from the outside. The two contours are inter-linked to provide a balanced technique with an ability to reject weak’local energy minima. Additionally a dual active contour configuration using dynamic programming has been developed to locate a global energy minimum and complements recent approaches via simulated annealing and genetic algorithms. These differ from conventional evolutionary approaches, where energy minimisation may not converge to extract the target shape, in contrast with the guaranteed convergence of a global approach. The new techniques are demonstrated to extract successfully target shapes in synthetic and real images, with superior performance to previous approaches. The new technique employing dynamic programming is deployed to extract the inner face boundary, along with a conventional normal-driven contour to extract the outer face boundary. Application to a database of 75 subjects showed that the outer contour was extracted successfully for 96% of the subjects and the inner contour was successful for 82%. This application highlights the advantages new dual active contour approaches for automatic shape extraction can confer.
Development of active laser reflector for alignment and monitoring of large-scale scientific devices

As large-scale scientific devices like particle accelerators and tokamaks become bigger and more complex, efficient measurements are needed for these devices. At present, when laser trackers are used to measure these devices, manually rotating reflectors is needed in many circumstances, but it's inefficient and it's inappropriate to be used in the areas where human can't approach. To solve the problem, we designed an active laser reflector, which can rotate to a target angle position controlled by a host computer software. We designed a fixture to embed and clamp a spherically mounted retro-reflector (SMR). And two custom-designed motors are used to drive the SMR to rotate horizontally and vertically respectively. The shaft of the motor has a flange to match another flange on the load, which can reduce the coaxiality error between them. The motor control system consists of two motor controllers and a host computer software, and they communicate through WIFI. We made a prototype of the active laser reflector based on the design scheme and measured the offset of the SMR center, which is around ±0.23 mm. The active laser reflector we designed can increase the measuring and monitoring efficiency for large-scale scientific devices.
Accounting for Proportion Congruency Effects in the Stroop Task in a Confounded Setup: Retrieval of Stimulus-Response Episodes Explains it All

Proportion congruency (PC) effects on the strength of distractor interference were investigated in a high-powered (n = 109), pre-registered experiment in which participants had to identify the ink color of color words. Replicating the standard PC effect, Stroop interference was larger in blocks comprising mostly congruent word-color combinations, compared to blocks comprising mostly incongruent trials. These block-level differences in the strength of the Stroop effect were eliminated after controlling for (a) the congruency of the most recent episode in which the current word had been presented (“episodic retrieval of control states”), and also after controlling for (b) the response relation of this episode and the current trial (“episodic response retrieval”). Controlling for the congruency in trial n-1 (congruency sequence effect, CSE), irrespective of word relation did not eliminate the PC effect, nor did controlling for immediate exact and partial repetitions. When predicting PC effects simultaneously by both types of episodic retrieval processes, only episodic response retrieval explained the effect. Our findings attest to the importance of episodic response retrieval processes in explaining the PC effect in Stroop-like tasks in a confounded setup where different processes compete with each, and they speak against explanations in terms of a global adjustment of cognitive control settings or contingency learning under these conditions. The results further support the assumption that the most recent episode in which a stimulus had occurred is crucial for responding in the current trial (the “law of recency”; Giesen et al., 2020).
Item-Position Binding Capacity Limits and Word Limits in Working Memory: A Reanalysis of Oberauer ()

Oberauer (2019) suggested that the working memory capacity in word lists only limits the binding of words to serial positions, with no limit for the words themselves. I advocate a word item limit as a broad kind of binding of each word to the current trial. I propose that the word capacity limit can be observed in Oberauer’s data when binding of a word to the trial is crucial (Experiment 2, words drawn from a small pool and often repeated across trials), though probably much less so when this kind of binding is unimportant (Experiment 1, words drawn from a large pool and rarely repeated across trials). In Oberauer’s recognition procedure for lists of 2, 4, 6, or 8 words, the number of words in the response set was varied, including both words from the list (1, 2, 4, 6, or 8 of them) and words that were not from the list (0, 1, 2, or 4 of them). There was also a serial recall procedure. In a re-analysis of the data from Experiment 2, an overlooked item capacity limit was found that affected the distribution of erroneous responses. Specifically, when the correct answer was unknown to the participant (which happened more at longer list lengths), proportionally fewer words from the list were selected as responses; selection of non-list words increased. It is an important theoretical refinement of Oberauer’s position to include evidence of a word item capacity limit when the item-to-trial binding is crucial, as in his Experiment 2.
Core Structures in Random Graphs and Hypergraphs

The k-core of a graph is its maximal subgraph with minimum degree at least k. The study of k-cores in random graphs was initiated by Bollobas in 1984 in connection to k-connected subgraphs of random graphs. Subsequently, k-cores and their properties have been extensively investigated in random graphs and hypergraphs, with the determination of the threshold for the emergence of a giant k-core, due to Pittel, Spencer and Wormald, as one of the most prominent results. In this thesis, we obtain an asymptotic formula for the number of 2-connected graphs, as well as 2-edge-connected graphs, with given number of vertices and edges in the sparse range by exploiting properties of random 2-cores. Our results essentially cover the whole range for which asymptotic formulae were not described before. This is joint work with G. Kemkes and N. Wormald. By defining and analysing a core-type structure for uniform hypergraphs, we obtain an asymptotic formula for the number of connected 3-uniform hypergraphs with given number of vertices and edges in a sparse range. This is joint work with N. Wormald. We also examine robustness aspects of k-cores of random graphs. More specifically, we investigate the effect that the deletion of a random edge has in the k-core as follows: we delete a random edge from the k-core, obtain the k-core of the resulting graph, and compare its order with the original k-core. For this investigation we obtain results for the giant k-core for Erdős–Renyi random graphs as well as for random graphs with minimum degree at least k and given number of vertices and edges.
The Structure of Super Cloud Clusters Observed in 1-20 June 1986 and their Relationship to Easterly Waves

The structural features of the eastward-propagating super cloud clusters and their westwardpropagating internal structures observed over the Pacific Ocean are described based on the GMS IR fundamental histogram data and the Global Objective Analysis (GANAL) Data. The analysis period is 1*20 June 1986 during which four organized groups of cloud clusters (super cloud clusters) with a longitudinal scale of about 3000 km successively propagated eastward over the equatorial western Pacific Ocean. The main results are as follows. (1) The hierarchical structure of the super cloud clusters observed in 1*20 June 1986 was associated with the equatorial eastward-propagating Kelvin wave-type mode and several degrees off equatorial westward-propagating "easterly waves" . (2) The equatorial eastwardpropagating mode was dominant between 10*N and 10*S, mainly in the zonal wind component. The phase relation between the wind and the height anomaly showed this mode had a Kelvin wave-type structure, although the propagation speed was as slow as 10*12*/day. The vertical structure indicated the downward energy propagation. The conversion from the convectively constructed potential energy to kinetic energy was not distinct, while the energy flux input from the southern hemisphere was indicated in the upper troposphere. (3) The structure of the westward mode associated with the westward-traveling cloud clusters corresponded to the "easterly waves" . To the rear of the lower convergence of the eastward mode (in SCC region), the upper level structure of the "easterly waves" was more firmly formed with the enhanced cloud activity producing the energy conversion from the available potential to the kinetic energy of the "easterly waves". Its amplitude in the lower troposphere was not significantly influenced by the eastward mode.
Compression of Convolutional Neural Networks With Divergent Representation of Filters

Convolutional neural networks (CNNs) have made remarkable achievements in many tasks. However, most of them are hardly applied to embedded systems directly because of the requirement of huge memory space and computing power. In this article, we propose a pruning framework, namely, FiltDivNet, to accelerate and compress CNN models for their applicability to small or portable devices. The correlations among filters are taken into account and measured by the goodness of fit. On this basis, a hybrid-cluster pruning strategy is designed with dynamic pruning ratios for different clusters in CNN models. It aims at representing its filters in their diversity by removing redundant ones cluster by cluster. In addition, a new loss function with adaptive sparsity constraints is introduced for the retraining and fine-tuning in the FiltDivNet. Finally, some comparative experiments based on classical CNN models are carried out to demonstrate its effectiveness in compression performance and its adaptability with different CNN architectures.