Miracle-dz/UniFAR-FTUs huggingface dataset:
Deadlock freeness supervisor for marked graph

Abstract This note presents a control synthesis approach for discrete event systems modeled by marked graphs with uncontrollable transitions. It solves forbidden state problems characterized by a set of general mutual exclusion constraints. We prove that the closed loop control can reach a deadlock situation. Using the structural proprieties of marked graph we defined causes of the deadlock situation, and we defined a formal method to avoid it.
Equivalent Lumped-Element Circuit of Aperture and Mutually Coupled Cylindrical Dielectric Resonator Antenna Array

This paper presents an electrical model of aperture and mutually coupled three-elements cylindrical dielectric resonator antenna (CDRA) array designed for 802.11a system applications. In electrical model, each antenna component is represented by its equivalent RLC circuit. The advanced design system (ADS) software is used to build the electrical model and predict the behavior of return loss, while the antenna structure is simulated using CST microwave studio before fabrication. The flrst and last radiating elements of the proposed array are excited through the aperture slots while the middle element is excited through the mutual coupling of its neighboring elements. The slot length and inter-slot distance efiects on bandwidth are comprehensively analyzed and presented. The maximum gain of the proposed array for 5.0GHz band is about 10.8dBi, and the achieved simulated (CST, ADS) and measured impedance bandwidths are 1.076GHz, 1.0GHz, and 1.2GHz respectively. The proposed CDRA array antenna exhibits an enhancement of the gain (7.4%) and bandwidth (93.3%) as compared to a literature work with aperture slots. In this study, it is also observed that by using the mutual coupling instead of third slot to excite the middle CDRA, side lobe levels are also reduced signiflcantly over the entire 5.0GHz band.
INTERPOLATION BY SERIES OF EXPONENTIALS IN H ( D ) WITH REAL NODES

In the space of holomorphic functions in a convex domain, we study a problem on interpolation by sums of the series of exponentials converging uniformly on compact subsets of the domain. The discrete set of multiple interpolation nodes is located on the real axis in the domain and has the unique finite accumulation point. We obtain a solvability criterion in terms of distribution of limit directions at infinity for the exponents of exponentials.
Non-Parametric Policy Learning for High-Dimensional State Representations

Learning complex control policies from high-dimensional sensory input is a challenge for reinforcement learning algorithms. Non-parametric methods can help to address this problem, but many current approaches rely on unstable greedy maximization. In this paper, we develop a kernel-based reinforcement learning algorithm that performs robust policy updates. We show that our method outperforms related approaches, and is able to learn an underpowered swing-up task task directly from high-dimensional image data.
Jupiter's Great Red Spot and Other Vortices

Probably the question most frequently asked about the Great Red Spot (GRS) is "What is it? ," as if a single powerful word or phrase-soliton, Taylor column, Rossby wave, hurricane-could neatly explain its 300 years of observation (Hook 1665, Cassini 1666) and modeling. The GRS is a nearly 2-dimensional vortex not attached to any topographic feature. Such vortices abound in Nature, but the peculiarities of the GRS, such as its huge size, persistent survival amid turbulence, and (most vexing from our point of view) why there is no terrestrial analog, are due to Jupiter's rapid rotation, nearly dissipationless atmosphere (no boundary layers), and strongly shearing east-west winds. This review argues that these three ingredients are essential for the formation and maintenance of the GRS, and that any flow having all three traits such as those found on Saturn, Neptune, and most other locations on Jupiter also have long-lived vortices. We present a tutorial in vortex dynamics to explain theoretically the GRS as the self-organization of vorticity in turbulence. We avoid pre­ senting models with enough free parameters to obtain a solution that reproduces exactly the GRS velocity and the motion of every cloud. The quality of the observations does not warrant it, and a misinterpretation of them can lead to incorrect conclusions. In the next section we list a number of properties of the GRS and the other Jovian vortices that are unambiguous from the data. The remainder of this paper develops the simplest possible model that explains these properties one at a time rather
ADOPTING BLENDED LEARNING INSTRUCTION TO PROMOTE LEARNERS' ORAL COMPETENCE

This study aims to investigate the effect of Blended Learning on learners’ oral competence and determine students and teachers’ attitudes towards Blended Learning (BL). This study was instigated from reviewing of interrelated literatures and resources taken from different references, journals and previous studies. These resources defined BL as a combination of face-to-face and online learning. The study was carried out on a sample of 40 participants: 19 teachers and twenty-one students at Taif University, KSA. Two questionnaires were adopted to measure how BL can help to promote learner’s oral competence and enhance fluency in terms of speaking English as foreign language. Teachers and students' questionnaires revolve round the attitudes, Application of Blended Learning and Developing Oral Competence. The two questionnaires were investigating the adoption of Blended Learning as an effective approach for promoting learners’ oral competence in English EFL departments. The preliminary data were collected from various resources and previous studies. However, the core data were gathered and retrieved from collected from respondents (19 teachers and 21 students) whom were selected to adopt the BL in “ situational English” course within the duration of 4 months. During this period Blended Learning and modern learning environments as well as the appropriate online materials were used to promote learning English as a foreign language and spoken English skills in particular. The study followed the descriptive and analytical approach of research design to assess and examine the integration and application of Blended Learning in situational English for English fluency purposes. The overall findings of the study showed no significant different attitudes between teachers and students attitudes towards BL and its application to develop oral competence. Finally, the study recommends intensive application of BL in English language oral courses to promote oral performance and competence.
Do Private Inspection Programs Affect Trade Facilitation?

Private inspection of international shipments has been used over the last half-century for a variety of purposes. These include prevention of capital flight and improvement of import duty collection, among others. The existing literature has failed to find much impact of these inspection programs on collected tariff revenue or corruption at the border. This paper explores the"facilitation"effect of private inspection programs on trade. The results indicate that private inspection has a positive and significant trade-facilitation effect. These programs raise import volumes for countries using them by approximately 2 to 10 percent. The findings here also suggest that the benefit of private inspection of imports may be associated with reforms and best practices applied by private inspection firms. Private firms'inspection of cargo may promote faster clearance times and process reliability, rather than improved tax collection.
IN VITRO HEPATOCYTE-ACTIVITY ENHANCEMENT VIA A LOBULE- MIMETIC ENGINEERED LIVER TISSUE LAB CHIP

A liver labchip integrating the DEP-based cell patterning technique and the microfluidic system for reconstructing the engineered liver tissue with the feature of liver function enhancement is demonstrated and reported in this paper. DEP forces are utilized as the cell-patterning mechanism to manipulate heterogeneous cells for mimicking the inherent hepatic morphology and increasing the cell-cell interaction. An ethoxyresorufin-O-dealkylase assay was performed to study the liver function enhancement of the engineered liver tissues. Experiment results show that the P450-1A1 enzyme activity of engineered liver tissues are 68.41% enhanced comparing with non-patterned liver cells.
Information Technology Aspects of Integrated Cardiac Rhythm Disease Management

Since several decades pacemakers and implantable cardioverter defibrillators (ICDs) are a common therapy for patients with cardiac rhythm abnormalities. More recently developed devices like implantable cardiac resynchronization therapy devices (CRTs) (Anand et al. 2009) or implantable loop recorders (ILRs) (Boersma et al. 2003) are implanted with increasing frequency and provide promising results. Selection and implantation of devices are only first steps in cardiac rhythm disease management. Continuous adaptation of device settings to patient’s needs, monitoring of device’s battery status, revision of devices and several other issues need to be considered. Additionally, the functionality of devices is closely related to other therapeutic aspects, such as medication or the patient’s health parameters – assessed either by general practitioners or by the patient him/ herself (e.g. blood pressure). In many cases a given patient needs more than one therapy: e.g. pacemaker therapy is closely related to medication monitoring; or an increasing number of remotely monitored congestive heart failure patients also have an implanted CRT device. Therefore, a system is needed which is able to handle data from various sources (from implanted devices, from patient’s home, from general practitioners, from hospitals, etc.) and provide the physician with all information necessary for an optimal therapy. While from the patient’s view it is primarily essential that all data from various sources are combined in one single system, from the physician’s view it is also important to have one single system for all the patients she/ he is responsible for. There are several manufacturers for each of the therapeutic tools used in cardiac rhythm disease management. Each of those provides the physician with its own proprietary data interface. And, of course, one physician’s patients are not all equipped with devices of one and the same manufacturer. Therefore, it is not only necessary to combine devices supporting different therapies (pacemakers, remote monitoring, etc.), but also to combine systems from different manufacturers within one single platform. Additionally, eHealth infrastructures with electronic health records are currently envisaged, conceived or already established in many environments (single healthcare institutions, health management organisations, whole healthcare systems, or even nation-wide) (Pfeiffer
Quantile Regression Reinforcement Learning with State Aligned Vector Rewards

The sample efficiency of deep reinforcement learning (DRL) algorithms is limited by the weak scalar training signal. We propose to use state aligned vector rewards to capitalize on the spatiotemporal nature of reaching problems and show that a state change distribution can be learned given an action distribution. Our agent, trained with a new DRL method inspired by quantile regression, is able to learn multiple times faster in high dimensional state spaces than a classical DRL algorithm.
Effect of hesperidin dietary supplementation on growth performance, carcass traits and meat quality of rabbits

An experiment was conducted to examine the dose effects of hesperidin dietary supplementation on fattening rabbits’ growth performance, as well as carcass and meat quality characteristics. Forty-eight Hyla hybrid male weaned (35 d old) rabbits were purchased and randomly assigned to 3 dietary groups of 16 rabbits each and fed diets supplemented with the antioxidant hesperidin at 0, 1 and 2 g/kg feed. At 80 d of age, the rabbits were slaughtered and samples of Longissimus lumborum (LL) muscle were used to estimate meat quality traits. No significant differences were observed in body weight at the age of 80 d, feed conversion rate (35 to 80 d), or organ weights among the 3 groups. The pH, colour, percentage of released water, shear force values and intramuscular fat content of LL muscle were not significantly influenced by the dietary treatment. Hesperidin dietary supplementation at both levels reduced the polyunsaturated fatty acids (PUFAs), mainly arachidonic (C20:4n-6), docosapentaenoic (C22:5n-3) and eicosapentaenoic (C20:5n-3) (only at 2 g/kg), and PUFA/SFA ratio (P<0.01). Based on the malondialdehyde (MDA) values, hesperidin inclusion did not influence meat antioxidant status during the 9-d refrigerated storage at 4°C. Thus, we may conclude that dietary supplementation with hesperidin at the selected concentration levels did not generally influence growth performance, carcass traits, meat quality or antioxidant capacity in fattening rabbits, although meat values for PUFAs appeared to be decreased.
Comparison Between Real-Time Polymerase Chain Reaction and DNA-Microarray in Detection and Identification of Mycobacterium Species

Low-cost and low-density (LCD) DNA arrays offer an easy way to detect resistance as minimal laboratory instrumentation is needed. Nucleic acid-based amplification tests allow the rapid detection of Mycobacterium tuberculosis. Recently, a real-time PCR assay for M. tuberculosis complex was introduced. Real-Time PCR and DNA-microarray techniques were compared with the classical methods of Ziehl-Neelsen (ZN) staining and culturing. Regarding to the standard culture method, 80 positive individuals were identified out of 140 urine samples. RT- PCR showed 96.3% sensitivity and 96.7% specificity with Mycobacterial tuberculosis complex (MTB) (n=10) and nontuberculous mycobacteria (NTM) (n=70). The DNA-microarray analysis exhibited 100% sensitivity and specificity. One species belonging to (MTB) was identified as M. tuberculosis and positively represented by 12.5% (n=10). Five species belonging to nontuberculous mycobacteria (NTM) were identified and represented as M. kansasii 37.5% (n=30), M. celatum 21.25% (n=17), M. gordonae 11.25% (n=9), M. chelonae 10% (n=8), and M. phlei 7.5% (n=6). The results recommend the use of our simple and rapid PCR technique for early diagnosis of mycobacteria’s. Also, the fast LCD-microarray protocol is very useful for species identification and differentiation between MTB and NTM
Construction of Incoherent Dictionaries via Direct Babel Function Minimization

Highly incoherent dictionaries have broad applications in machine learning. Minimizing the mutual coherence is a common intuition to construct incoherent dictionaries in the previous methods. However, as pointed out by Tropp (2004), mutual coherence does not oﬀer a very subtle description and Babel function, as a generalization of mutual coherence, is a more attractive alternative. However, it is much more challenging to optimize. In this work, we minimize the Babel function directly to construct incoherent dictionaries. As far as we know, this is the ﬁrst work to optimize the Babel function. We propose an augmented Lagrange multiplier based algorithm to solve this nonconvex and nonsmooth problem with the convergence guarantee that every accumulation point is a KKT point. We deﬁne a new norm (cid:107) X (cid:107) ∞ ,max p and propose an eﬃcient method to compute its proximal operation with O ( n 2 log n ) complexity, which dominates the running time of our algorithm, where max p means the sum of the largest p elements and n is the number of the atoms. Numerical experiments testify to the advantage of our method.
Reading Proficiency Across Economies: Measuring the Quality of Education and its Effect on Economic Growth

The paper considers the determinants of reading proficiency of the working population in an economy using data on the per capita circulation of newspapers for forty countries over some years. The results indicate that parents’ education and government expenditure on education during schooling are important in developing reading proficiency. Based on this analysis the paper develops a measure of the quality of education of the working population in terms of its impact on the per capita circulation of newspapers. By incorporating this measure in growth regressions it is observed that the quality of education may have a significant effect on the growth of nations.
Electrostatically defined few-electron double quantum dot in silicon

A few-electron double quantum dot was fabricated using metal-oxide-semiconductor-compatible technology and low-temperature transport measurements were performed to study the energy spectrum of the device. The double dot structure is electrically tunable, enabling the interdot coupling to be adjusted over a wide range, as observed in the charge stability diagram. Resonant single-electron tunneling through ground and excited states of the double dot was clearly observed in bias spectroscopy measurements.
The use of PCR-RFLP as an identification tool for two closely related species of bats of genus Platyrrhinus

The bat species Platyrrhinus lineatus and P. recifinus (Phyllostomidae: Stenodermatinae) are ecologically important because of their capacity for seed dispersal. P. recifinus is endemic to the Atlantic rain forest and is considered vulnerable by the IUCN. The lack of distinct morphological features makes identification of the two species a difficult task. This study was aimed at testing the hypothesis that these are actually two distinct species by using PCR-RFLP of the mitochondrial cytocrome b gene. The results showed no shared haplotypes, demonstrating that these are, in fact, two distinct species. No polymorphism was obtained for P. recifinus, which could be a sign of low genetic diversity in this threatened species.
Substance Use Disorder: Biological Mechanisms, Clinical Effects and Neuroadaptations

Substance use disorder is characterized by a psychological dependence on a substance or a drug that is beyond voluntary control and that can cause serious harm to the individual when used repetitively. The use of drugs, including alcohol, opiates and psychostimulants, is a wide spread behavior in human societies that pose massive public health costs. This paper aims at explaining the neurobiology of drug addiction and investigating the effects of substances such as psychostimulants, opioids, nicotine and alcohol on an individual’s health. Moreover, this paper gives an overview of the neurotransmitters and brains structures that are altered following the excessive use of drugs, and illustrates some of the neurobiological changes that occur during drug addiction. At the molecular level, drug abuse induces functional and morphological changes of specific brain structures, which generally lead to adverse consequences such as drug relapse. Although previous studies have significantly improved our understanding of the neurobiological mechanisms of substance use disorder in humans, more work need to be done to identify potential therapeutic targets and develop new treatment strategies.
Measuring Impact of Rumorous Messages in Social Media

As social media continues to grow, the connectivity between individuals and organisations becomes tighter, and the availability of data becomes more immediate, constant and abundant. Aside from conversational chat, people are using social media platforms to share relevant information and to report news. We must become aware of unbased rumours and protect ourselves against false information and its potential consequences if believed. As information credibility becomes an increasing concern, there rises an important question of rumour impact. This work is concerned with the study of rumour impact on social media itself. Information spread on social media has a high potential for impact, due to the real-time nature of these media. News organisations are losing their audiences to lies and unveriﬁed stories, costing them both money and reputation. Misinformation can also endanger life if adopted by individuals during times of crisis. This work measures the impact of a given rumour, impact that will be determined by analysing user engagement measures. Analysis is then conducted in an attempt to understand why some rumours make more impact than others. There are two main categories investigated - message-based feature analysis and author-based feature analysis . By measuring and analysing impact, this work strives to understand the dispersal potential of rumours. Questions are posed regarding the higher impact of some rumours compared to others, and message-and author-based features are investigated in a bid to answer such questions. This will indicate just how penetrable a given rumour could be, how many people could potentially be reached, how fast this dispersal can happen, and how composition features can inﬂuence success, highlighting the power of social media in the life of a rumour. This lends towards a useful tool for news agencies, social media networks, governments etc, in ﬂagging potentially impactful rumours.
Quality Model based on Object-oriented Metrics and Naive Bayes

Software quality engineering is a field in software engineering specializing on improving the approach to software quality on different software artifacts such as object-oriented analysis models, object-oriented design models, and object-oriented implementation models. Software quality is the degree to which a software artifact exhibits a desired combination of quality-carrying attributes (e.g. testability, reliability, reusability, interoperability, and other quality-carrying attributes). This research specializes on improving the code quality of object-oriented systems through a quality model that utilizes a suite of object-oriented metrics and a machine learning technique, namely Naive Bayes. Most of the existing object-oriented metrics and machine learning techniques capture similar dimensions in the data sets, thus reflecting the fact that many of the object-oriented metrics and machine learning techniques are based on similar hypotheses, properties, and principles. Accurate quality models can be built to predict the quality of object-oriented systems by using a subset of the existing object-oriented design metrics and machine learning techniques. This research proposes a software quality model, namely QUAMO to assess the quality of object-oriented code on-the-fly. The primary objective of the model is to make similar studies on software quality more comparable and repeatable. The model is augmented from five quality models, namely Boehm Model, McCall Model, FURPS, ISO 9126, and Dromey Model. The quality model specializes on Bayesian network classifier, Naive Bayes. The Naive Bayes classifier, a simple classifier based Bayes’ law with strong independence assumptions among features is comparable to other state-of-the-art classifiers, namely ID3 Decision Tree, J48 Decision Tree, and C4.5 Decision Tree. Naive Bayes is very effective in solving the classification problems addressed in this research, namely the conditional maximum likelihood prediction of faults in object-oriented systems. Most of the metrics proposed by other researchers mainly specialized at the class level such as CK Metrics Suite and MOOD Metrics Suite (Chidamber & Kemerer, 1994). Fewer component level metrics have been proposed such as Rate of Component Observability, Rate of Component Customizability, and Self-Completeness of Component's Return Value. As such, this research also proposes a suite of specialized object-oriented metrics that can be applied at the class and component levels as some insights can be gained by examining the average characteristics of both a class and a component. Each metric quantifies a particular feature of an object-oriented system. In other words, each refers to a structural mechanism of the