Miracle-dz/UniFAR-FTUs huggingface dataset:
Explaining the Concept and Dimensions of Professional Functions in Online Learning System of Medical Sciences: A Qualitative Content Analysis

The increasing growth of technology affects all aspects of life, including the system of education, and requires the implementation of a new education system. Since Electronic-learning (E-L) is a new and mutated form of education in Iran, its professional functions approach is different from that of traditional education. The present article aims to explain the concept and dimensions of professional functions in this field. Through a qualitative study, method and data source triangulation were used. To do so, the data sources were the professors, scholars, students, and graduates of this educational system in the field of medical sciences. To triangulate the methods, in-depth semi-structured interviews as well as focus groups, note-taking and reminders were used. The purposeful sampling consisted of 10 professors and scholars. Fifteen students and graduates participated in the four-session focus group discussions purposeful, and the sample consisted of 10 professors and scholars as well as seven students and graduates, and a total of 15 students and graduates were willing to participate in the focus group discussions. Inductive content analysis was used for the analysis of data. Three themes arose from the study as follows: E-learning prerequisites, E-Leaning enabling factors, and E-Learning obstacles. Each of the themes is explained along with the relevant categories and subcategories. Discovering the dimensions and elements affecting professional functions in the E-Lsystem of medical sciences, this study provided documented meanings and dimensions of this phenomenon beyond the conventional sense. These dimensions can have direct or indirect impacts on professional functions in this field.
Hierarchical Classification Algorithm Based on FastText

 At present, methods for automatic assigning labels for literature using the Chinese Library Classification system are mostly based on machine learning methods, and many use the build knowledge base to improve classification effect. These methods are applicable to small-scale dataset, and as the categorical numbers increase, the classification effect will decrease and the time cost will increase dramatically. The paper proposes a hierarchical classification algorithm based on fastText text classification tool to solve classification indexing problem on large-scale literature dataset. The algorithm trains the two-layer classifier from the top-down method and designs an optimization algorithm to reduce the error transmission between the two layers. Experimental results showed that the optimized hierarchical classification technique improved the classification effect compared to the traditional classification technique.
CU-MAC: A MAC Protocol for Centralized UAV Networks with Directional Antennas

SUMMARY Media Access Control (MAC) is critical to guarantee different Quality of Service (QoS) requirements for Unmanned Aerial Vehicle (UAV) networks, such as high reliability for safety packets and high throughput for service packets. Meanwhile, due to their ability to provide lower delay and higher data rates, more UAVs are using frequently directional antennas. However, it is challenging to support different QoS in UAV networks with directional antennas, because of the high mobility of UAV which causes serious channel resource loss. In this paper, we propose CU-MAC which is a MAC protocol for Centralized UAV networks with directional antennas. First, we design a mobility prediction based time-frame optimization scheme to provide reliable broadcast service for safety packets. Then, a trafﬁc prediction based channel allocation scheme is proposed to guarantee the priority of video packets which are the most common service packets nowadays. Simulation results show that compared with other representative protocols, CU-MAC achieves higher reliability for safety packets and improves the throughput of service packets, especially video packets. key words
High-Dimensional Bayesian Multi-Objective Optimization

This thesis focuses on the simultaneous optimization of expensive-to-evaluate functions that depend on a high number of parameters. This situation is frequently encountered in fields such as design engineering through numerical simulation. Bayesian optimization relying on surrogate models (Gaussian Processes) is particularly adapted to this context.The first part of this thesis is devoted to the development of new surrogate-assisted multi-objective optimization methods. To improve the attainment of Pareto optimal solutions, an infill criterion is tailored to direct the search towards a user-desired region of the objective space or, in its absence, towards the Pareto front center introduced in our work. Besides targeting a well-chosen part of the Pareto front, the method also considers the optimization budget in order to provide an as wide as possible range of optimal solutions in the limit of the available resources.Next, inspired by shape optimization problems, an optimization method with dimension reduction is proposed to tackle the curse of dimensionality. The approach hinges on the construction of hierarchized problem-related auxiliary variables that can describe all candidates globally, through a principal component analysis of potential solutions. Few of these variables suffice to approach any solution, and the most influential ones are selected and prioritized inside an additive Gaussian Process. This variable categorization is then further exploited in the Bayesian optimization algorithm which operates in reduced dimension.
Patients with Meniere's Disease without Vertigo

There are patients who complain of a feeling of fullness in the ear and earache suggestive of acute tubotympanic catarrh or otitis media but in whom the tympanic membranes are entirely free from abnormalities and the Eustachian tubes show no evidence of obstruction on inflation by the eustachian catheter. These patients may show spontaneous nystagmus and deviations of labyrinthine origin on equilibrium tests, evidence of inner ear injury, but nevertheless they say they have never had an attack of vertigo. Audiometric tests reveal a 20 to 40dB elevation of the threshold in low frequency ranges and the hearing loss is not always of the sensorineural type.We encountered 25 patients with such symptoms during the 1-year period from September 1, 1977 to August 31, 1978. None of these patients had a history of trauma, drug therapy or fever that might have an etiologic relation with the disorder. Many affirmed the presence of stress as a precipitating cause in their past history, while some reported the occurrence of symptoms in repeated episodes. These findings led us to assume that the condition before us, even though lacking in vertigo, is none other than Meniere's disease.For these patients we prescribed rest, oral steroids and intravenous xylocaine. After 10-14 days of this combined regimen the patients were free from subjective symptoms (a feeling of fullness and otalgia), abnormalities on equilibrium tests (nystagmus and deviation) and perceptive deafness.Williams advocated the concept of “endolymphatic hydrops without vertigo” and stated that when the process of Meniere's disease is confined to the cochlea. Vestibular symptoms, notably vertigo, may not appear. In our present series, however, the abnormalities on equilibrium tests clearly indicated the presence of a disturbance in the vestibular segment of the labyrinth, and the disease entity in these cases is therefore quite distinct from the one which was designated as “endolymphatic hydrops without vertigo” by Williams. When a patient has no vertiginous attacks in the presence of a lesion in the vestibular segment of the end-organ, the cause of such a failure to develop vertigo must be sought from the psychological aspect.A psychological test using the Cornell medical index demonstrated that the patients in our present series showed a lesser tendency to neurosis than did Meniere's disease patients in general. This finding may be interpreted as indicating that Meniere's disease patients without vertigo are relatively insensitive to somatic distress, including vertigo.
Porous Pseudomaterials for Studying Structure-PropertyRelationships of Gas Adsorption

The discovery in 1995 of metal-organic frameworks (MOFs) – with record-breaking surface areas – sparked exponential growth in research efforts dedicated to the development of new porous adsorbents, particularly for energy related gas storage applications. However, despite their promise, decades of research have yet to yield MOFs that perform well enough for many of these applications, particularly high-pressure vehicular natural gas storage and post-combustion carbon capture. To understand why, I developed a novel computational methodology for generating large (100,000+) libraries of randomly configured Lennard-Jones (LJ) crystals, or “pseudomaterials”, with the intention of calculating various adsorption-related properties of interest en masse using grand canonical Monte Carlo (GCMC) simulations. These libraries were used to map an n-dimensional structure-property space, where n refers to the number different structure- and property-parameters. One approach for generating these libraries of pseudomaterials is random sampling, where each structure is generated algorithmically at random; however, we attempt to improve the overall computational efficiency using alternative methods. These alternative methods include mutation algorithms and augmenting random sampling with property prescreening. Mutation algorithms identify pseudomaterials with unique structure-property combinations and selectively perturb their structural characteristics to sample the sparsely populated regions of the structure-property space. Property prescreening uses machine learning models to predict the properties of a pseudomaterial to justify whether it is a candidate worthy of more computationally expensive GCMC simulations; it is an attempt at reducing the computational expense associated with running simulations on pseudomaterials with redundant properties. The overall goal of this new computational methodology was to observe structure-property relationships for porous materials in general (i.e., not limited to any particular sub-class). I showed that understanding these structure-property relationships provides insights into the design of better adsorbents for a wide range of gas storage and separations applications. In the future, this methodology could potentially be extended to better understanding porous materials for catalysis, sensing, and more.
Online Optimization for Networked Distributed Energy Resources With Time-Coupling Constraints

This paper proposes a Lyapunov optimization-based online distributed (LOOD) algorithmic framework for active distribution networks (ADNs) with numerous photovoltaic inverters and inverter air conditionings (IACs). In the proposed scheme, ADNs can track an active power setpoint reference at the substation in response to transmission-level requests while concurrently minimizing the social utility loss and ensuring the security of voltages. Conventional distributed optimization methods are rarely feasible to track the optimal solutions in fast variable environments using a fine-grained sampling interval where the underlying optimization problem evolves with the iterations of the algorithms. In contrast, based on the framework of online convex optimization (OCO), the developed approach uses a distributed algebraic update to compute the next round decisions relying on the current feedback of measurements. Notably, the time-coupling constraints of IACs are decoupled for online implementation with Lyapunov optimization technique. An incentive scheme is tailored to coordinate the customer-owned assets in lieu of the direct control from network operators. Optimality and convergency are characterized analytically. Finally, we corroborate the proposed method on a modified version of 33-node test feeder. Benchmark tests show that the proposed method is computationally and economically efficient, and outperforming existing algorithms.
Design of Traffic Monitoring System Based on Video Detection

Traffic monitoring system is an important means to ensure the safe operation of traffic. According to the characteristics of road traffic monitoring environment, a real-time traffic monitoring system is designed by using image processing, computer vision, pattern recognition and other technologies. Experiments show that the system can effectively detect various typical traffic incidents and traffic operation parameters, and provide a favorable guarantee for traffic safety.
An improved evolutionary multi-objective optimization algorithm based on decomposition

Multi-objective optimization (MOP) is a hot and difficult problem in the field of industrial production and scientific research, involving simultaneous optimization of multiple objectives. In this paper, an improved decomposition-based multi-objective evolutionary algorithm is proposed to solve MOP. Firstly, the Latin hypercube sampling method is used to generate the initial population in order to improve the diversity of the initial population and the probability of convergence to the global optimal solution. Secondly, the adaptive differential crossover operator is used to adjust the parameter settings adaptively for different problems, including the differential proportionality factor and crossover probability, so as to improve the performance of the algorithm. Finally, the reference point is set to coordinate origin, which can pull the population back to the real front faster and accelerate the convergence speed of the population. In a group of benchmark problems, ZDT and DTLZ test problems, the algorithm is widely compared with four most advanced algorithms. The experimental results show that the algorithm has better ability to solve MOP problems.
Strategy of Repairing Coverage Hole for Different Holes Shapes in Heterogeneous Wireless Sensor Networks

 For the randomness of the initial deployment of sensor nodes and the exhaustion of node energy during network operation, the problem of covering holes may be generated, the coverage repair strategies for different holes shapes are proposed. Firstly, the holes polygons formed by static nodes of randomly deployed heterogeneous wireless sensor networks are classified. Secondly, according to different polygon types, different repair strategies are adopted to determine the location of virtual repair nodes. Finally, according to the distance between the virtual repair node and the mobile node, the relation function of energy threshold value, and the movement of the mobile node with finite distance, the covering cavity is repaired. Simulation results show that the coverage is improved by adopting different repair strategies according to different holes types.
Toward Scalable and Robust Indoor Tracking: Design, Implementation, and Evaluation

Although indoor localization has been studied over a decade, it is still challenging to enable many IoT applications, such as activity tracking and monitoring in smart home and customer navigation and trajectory mining in smart shopping mall, which typically require meter-level localization accuracy in a highly dynamic and large-scale indoor environment. Therefore, this article aims at designing and implementing an adaptive and scalable indoor tracking system in a cost-effective way. First, we propose a zero site-survey overhead (ZSSO) algorithm to enhance the system scalability. It integrates the step information and map constraints to infer user’s positions based on the particle filter and supports the auto labeling of scanned Wi-Fi signal for constructing the fingerprint database without the extra site-survey overhead. Further, we propose an iterative-weight-update (IWU) strategy for ZSSO to enhance system robustness and make it more adaptive to the dynamic changing of environments. Specifically, a two-step clustering mechanism is proposed to delete outliers in the fingerprint database and alleviate the mismatch between the auto-tagged coordinates and the corresponding signal features. Then, an iterative fingerprint update mechanism is designed to continuously evaluate the Wi-Fi fingerprint localization results during online tracking, which will further refine the fingerprint database. Finally, we implement the indoor tracking system in real-world environments and conduct a comprehensive performance evaluation. The field testing results conclusively demonstrate the scalability and effectiveness of the proposed algorithms.
Construction of Competitive Advantage Instrument in Jordanian SME Context Using Structural Equation Modelling

Jordanian SMEs are becoming increasingly hard to endure and thrive in the aggressive entrepreneurial world economy due to weak capital structure, poor leadership and weak marketing strategy, as well as other legislative limitations. As a consequence, Jordan faces problems in achieving full advantage from the SME industry as well, making an inadequate contribution to the domestic GDP. Competitive advantage (CA) can, however, perform a crucial part in achieving fast economic development due to sustainability of SMEs and a coherent appropriate input to Jordan's GDP. But the construction of CA is still underdeveloped and ignores a unifying hypothesis, resulting in fragmented study attempts. In addition, there are now several frameworks for the evaluation and benchmarking of firm performance (FP), but none of these frameworks provide an approach for assessing the competitive advantage of the firm. Therefore, this study aims to explore and determine the dimensionality of items measuring CA construct. The issue has previously been discussed, but there is still no prevalent agreement between scholars as the number of dimensions and items to assess CA should be used. This research investigated the CA measurement items created by past researchers and tailored these items to accommodate the environment of SMEs in Jordan. In this regard, the Delphi technique has been combined by the Structural Equation Modeling (SEM) and also followed the steps of instrument creation developed by Churchill (1979). The primary objective of this research is to develop an instrument capable of assessing CA in Jordanian SME sector. The tool developed in this research provides a relevant and efficient tool that disclosed three aspects by satisfying all the socio-metric properties required by the measuring tool in the social science, namely dimensionality, reliability, and validity.
Performance Analysis of Downlink NOMA Systems Over <inline-formula><tex-math notation="LaTeX">$\kappa$</tex-math></inline-formula>-<inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> Shadowed Fading Channels

Non-orthogonal multiple access (NOMA) has emerged as a promising technology for 5G networks and beyond. In order to fully reap the benefits of NOMA, it is essential to characterize its performance for different channel conditions. In this paper, we carry out a performance analysis of downlink NOMA systems subject to <inline-formula><tex-math notation="LaTeX">$\kappa$</tex-math></inline-formula>-<inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> shadowed fading channels. Specifically, ergodic capacity, outage probability, and average bit error rate expressions for a two-users NOMA scheme under <inline-formula><tex-math notation="LaTeX">$\kappa$</tex-math></inline-formula>-<inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> shadowed fading links are derived. The accuracy of the analytical results has been validated by extensive simulations.
The dangers of including nonclassical cystic fibrosis variants in population-based screening panels: p.L997F, further genotype/phenotype correlation data

Purpose: Recently, a major CLIA-certified commercial laboratory began offering an extended cystic fibrosis (CF) carrier screening panel containing 103 variants including p.L997F. Our laboratory has already received two invasive prenatal diagnostic samples where one parent carries a classic CF mutation and the other carries p.L997F. One fetus inherited both variants.Methods: We queried our databases containing >2500 CF sequencing analyses to find all individuals with the p.L997F variant. For all compound heterozygous patients, clinical information was obtained by a genetic counselor telephoning the medical provider.Results: There were four compound heterozygous patients carrying the p.L997F variant and a second pathogenic CF allele. Three patients were discovered by newborn screening and were asymptomatic at ages 28, 40, and 60 months, respectively. The fourth individual is currently aged 10 years and has the diagnosis of atypical CF with recurrent pancreatitis, sinusitis with nasal polyps, and mild lung disease. His length and weight are in the 90th and 75th centile, respectively. The fifth patient was a compound heterozygote for p.F508del and a complex allele containing p.L997F and a deletion of exons 2–9. This patient has the diagnosis of classical CF.Conclusion: The p.L997F variant is not a classical CF mutation, and its inclusion in population-based carrier screening panels is a disservice to couples who may make poorly informed reproductive decisions based on incorrect assumptions.
Working with Lentivirus for Generation of Transgenic Bovine Embryos

Pharmaceutical industry started with the production of proteins for therapeutic purposes using the extraction from producing tissues, such as insulin derived from a pig’s pancreas and growth hormone from the pituitary gland. The proteins from these tissues often show low quality and increase in the risk of transmitting diseases such as HIV or those caused by prions. Recombinant DNA technology has allowed the heterologous proteins production using the bacterial system [1] that results in increased protein availability, therefore, improving quality and reducing the risk of disease transmission. Bacteria have been widely used as bioreactors because they are easily cultured. However, these microorganisms have limited ability to perform post-translational modifications of proteins necessary for the formation of biologically active molecules [2].
Two-Level Grid Access Control Model Based on Resource Performance and Request Priority

– This paper summarizes all the mechanisms presented previously to efficiently represent grid computing security policies. The prime advantage of this work is to reduce the complexity by minimizing the number of security rules that require checking. This is achieved by combining the Grid Authorization Graph (GAG) and the Weighted Grid Authorization Graph (WGAG) in a two-level access control model. This model attributes the grid resources to users according to the performance that the job requires, thus avoiding performance waste. Simulations results showed the effectiveness of the proposed model in reducing the number of security rules that require checking.
Connective-Lex: A Web-Based Multilingual Lexical Resource for Connectives

In this paper, we present a tangible outcome of the TextLink network: a joint online database project displaying and linking existing and newly-created lexicons of discourse connectives in multiple languages. We discuss the definition and demarcation of the class of connectives that should be included in such a resource, and present the syntactic, semantic/pragmatic, and lexicographic information we collected. Further, the technical implementation of the database and the search functionality are presented. We discuss how the multilingual integration of several connective lexicons provides added value for linguistic researchers and other users interested in connectives, by allowing crosslinguistic comparison and a direct linking between discourse relational devices in different languages. Finally, we provide pointers for possible future extensions both in breadth (i.e., by adding lexicons for additional languages) and depth (by extending the information provided for each connective item and by strengthening the crosslinguistic links).