Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Level Analysis of Legitimacy in Bengali News Sentences

The tremendous increase in the growth of misinformation in news articles has the potential threat for the adverse effects on society. Hence, the detection of misinformation in news data has become an appealing research area. The task of annotating and detecting distorted news article sentences is the immediate need in this research direction. Therefore, an attempt has been made to formulate the legitimacy annotation guideline followed by annotation and detection of the legitimacy in Bengali e-papers. The sentence-level manual annotation of Bengali news has been carried out in two levels, namely “Level-1 Shallow Level Classification” and “Level-2 Deep Level Classification” based on semantic properties of Bengali sentences. The tagging of 1,300 anonymous Bengali e-paper sentences has been done using the formulated guideline-based tags for both levels. The validation of the annotation guideline has been done by applying benchmark supervised machine learning algorithms using the lexical feature, syntactic feature, domain-specific feature, and Level-2 specific feature in both levels. Performance evaluation of these classifiers is done in terms of Accuracy, Precision, Recall, and F-Measure. In both levels, Support Vector Machine outperforms other benchmark classifiers with an accuracy of 72% and 65% in Level-1 and Level-2, respectively.
Constraints to leveraging regular season sport team events

ABSTRACT Research on event leveraging has revealed that certain constraints inhibit the realisation of desired benefits from event hosting. Using qualitative action research methods, this study examined the constraints to leveraging regular season professional sport team events for tourism. The leveraging potential of regular season professional sport team events has been largely ignored – both by researchers and practitioners. This presented an ideal opportunity to examine the pre-leveraging phase with a view to understanding leveraging constraints. The results identified five overarching constraints: lack of collaboration; priorities and resources; perceived benefit radius; perceived tourism potential; and, unclaimed responsibility. We propose a process model to better understand how leveraging constraints emerge and can be negotiated over time. This research is among the first to demonstrate the utility of team events for inclusion in regional event portfolios. It, therefore, builds on extant knowledge by presenting a more holistic conceptualisation of the inherent constraints to event leveraging, and further, provides a basis from which to successfully negotiate these constraints. HIGHLIGHTS Constraints prevent regular season sport team events from being considered leverageable. Collaboration, priorities, and resources are constraints to leveraging sport team events. Perceived tourism potential and the perceived benefit radius were constraints to leverage. Discussing regular season events in relation to tourism leads to a shift in attitudes in opinions. Identifying responsibility for leverage remains a constraint.
Hybrid dynamic-static finite-difference approach for MMIC design

The efficiency of the Finite-Difference method is improved by combining the full-wave analysis with a quasi-static approach: those regions of a structure which require a spatial resolution far below the wavelength are described by a quasi-static analysis. As a consequence, the mesh size of the dynamic problem and hence the numerical efforts can be reduced significantly. The savings are particularly high for miniaturized geometries such as used in coplanar MMIC geometries.
Relationship between Organizational Culture and Performance Management Practices: A Case of University in Pakistan

The aim of this study is to expand the base of knowledge and empirically test the relationship between the components of organizational culture and performance management practices. The study adopted the exploratory research approach to explore the impact. In this study, primary data was collected through questionnaires from 140 employees at the COMSATS Institute of Information Technology. The sample consists of both male and female faculty members. The regression and correlation statistical analysis were used. The results from the statistical analysis show that, involvement is highly correlated with consistency and adapt- ability. Similarly, the other dimensions of organizational culture have a positive significant relationship with the performance management practices.
Retinal cell transplantation in retinitis pigmentosa

Retinitis pigmentosa is the most common hereditary retinal disease. Dietary supplements, neuroprotective agents, cytokines, and lately, prosthetic devices, gene therapy, and optogenetics have been employed to slow down the retinal degeneration or improve light perception. Completing retinal circuitry by transplanting photoreceptors has always been an appealing idea in retinitis pigmentosa. Recent developments in stem cell technology, retinal imaging techniques, tissue engineering, and transplantation techniques have brought us closer to accomplish this goal. The eye is an ideal organ for cell transplantation due to a low number of cells required to restore vision, availability of safe surgical and imaging techniques to transplant and track the cells in vivo, and partial immune privilege provided by the subretinal space. Human embryonic stem cells, induced pluripotential stem cells, and especially retinal organoids provide an adequate number of cells at a desired developmental stage which may maximize integration of the graft to host retina. However, stem cells must be manufactured under strict good manufacturing practice protocols due to known tumorigenicity as well as possible genetic and epigenetic stabilities that may pose a danger to the recipient. Immune compatibility of stem cells still stands as a problem for their widespread use for retinitis pigmentosa. Transplantation of stem cells from different sources revealed that some of the transplanted cells may not integrate the host retina but slow down the retinal degeneration through paracrine mechanisms. Discovery of a similar paracrine mechanism has recently opened a new therapeutic path for reversing the cone dormancy and restoring the sight in retinitis pigmentosa.
Developing a supplier selection system through integrating fuzzy AHP and fuzzy DEA: a case study on an auto lighting system company in Taiwan

Supplier selection plays a very important role in supply chain management. This study intends to develop a novel performance evaluation method, which integrates both fuzzy analytical hierarchy process (AHP) method and fuzzy data envelopment analysis (DEA) for assisting organisations to make the supplier selection decision. Fuzzy AHP method is first applied to find the indicators’ weights through expert questionnaire survey. Then, these weights are integrated with fuzzy DEA. We use α -cut set and extension principle of fuzzy set theory to simplify the fuzzy DEA as a pair of traditional DEA model. Finally, fuzzy ranking using maximising and minimising set method is able to rank the evaluation samples. A case study on an internationally well-known auto lighting OEM company shows that the proposed method is very suitable for practical applications.
2D/3D switchable displays

A prerequisite for a wide market acceptance of 3D displays is the ability to switch between 3D and full resolution 2D. In this paper we present a robust and cost effective concept for an auto-stereoscopic switchable 2D/3D display. The display is based on an LCD panel, equipped with switchable LC-filled lenticular lenses. We will discuss 3D image quality, with the focus on display uniformity. We show that slanting the lenticulars in combination with a good lens design can minimize non-uniformities in our 20" 2D/3D monitors. Furthermore, we introduce fractional viewing systems as a very robust concept to further improve uniformity in the case slanting the lenticulars and optimizing the lens design are not sufficient. We will discuss measurements and numerical simulations of the key optical characteristics of this display. Finally, we discuss 2D image quality, the switching characteristics and the residual lens effect.
Evolutionary Algorithm-based images, humanly indistinguishable and adversarial against Convolutional Neural Networks: efficiency and filter robustness

Convolutional neural networks (CNNs) have become one of the most important tools for image classification. However, many models are susceptible to adversarial attacks, and CNNs can perform misclassifications. In previous works, we successfully developed an EA-based black-box attack that creates adversarial images for the target scenario that fulfils two criteria. The CNN should classify the adversarial image in the target category with a confidence ≥ 0.95, and a human should not notice any difference between the adversarial and original images. Thanks to extensive experiments performed with the CNN C = VGG-16 trained on the CIFAR-10 dataset to classify images according to 10 categories, this paper, which substantially enhances most aspects of [1], addresses four issues. (1) From a pure EA point of view, we highlight the conceptual originality of our algorithm EAdtarget,C, versus the classical EA approach. The competitive advantage obtained was assessed experimentally during image classification. (2) We then measured the intrinsic performance of the EA-based attack for an extensive series of ancestor images. (3) We challenged the filter resistance of the adversarial images created by the EA for five well-known filters. (4) We proceed to the creation of natively filter-resistant adversarial images that can fool humans, CNNs, and CNNs composed with filters.
Plant Leaf Disease Detection

— Plant leaf disease detection plays an important role in the field of agriculture. Early detection of the disease can prevent the loss of formers and help in the increasing the productivity of the crop. Diseases can be detected by different image processing and machine learning algorithms and pattern recognition. It is not a simple task to manually observe and classify leaf diseases, since it requires a lot of time, resources, commitment, etc. So, with an automated image processing and machine learning system, it's easier to identify diseases. Plant leaf disease detection consist of five basic steps; image acquisition, preprocessing, segmentation, feature extraction and classification. the denoising step can be achieved by application of different filters. This paper presents an analysis of various methods for detecting image processing plant leaf diseases.
Fault current analysis for a superconducting 1 kA YBCO cable

Superconducting cables can be used to transport large amounts of energy with small losses in considerably smaller volume compared to the conventional ones. The first YBCO cable demonstrations are under development and they are expected to outperform BSCCO cables. In the design work, the temperatures in the YBCO cables need to be simulated under any fault current conditions. In this paper, the temperature distribution in a 1 kA YBCO-cable was computed with various fault currents in order to study the thermal stability of the cable. The fault current is shared between the layers of superconducting YBCO tape and the copper shunt. FEM models were used to determine simultaneously both the current density and the temperature distributions of the cable as a function of time. Adiabatic conditions were assumed in order to obtain an upper limit for the temperature. According to the model, the copper core was able to absorb most of the heat. The cable maintained the thermal stability during 1 s with 10 and 20 kA (rms) fault currents. With 30 and 40 kA fault currents the cable was predicted to quench.
Characterization of Aminoglycoside Modifying Enzymes Producing E. coli and Klebsiella pneumoniae Clinical Isolates

Antimicrobial resistance gene profile characterization and dissemination offer useful detail on the possible challenge in treating bacteria. The development of aminoglycoside modifying enzymes (AMEs) is considered as the primary mechanism of resistance to aminoglycosides, in addition to the 16S rRNA methylases. This study aimed at isolation and characterization of aminoglycosides resistant clinical isolates of enterobacteriaceae family from different clinical samples. Over a period of 24 months, thirty samples were collected and 49 clinical isolates of E. coli [n=25], Klebsiella [n=13], Enterobacter species (n=7) and Proteus species (n=4) were isolated from Egyptian clinical laboratories. The identities of the cultures were confirmed following standard microbiological procedures. Resistance of the isolates to aminoglycosides was determined by the disc diffusion method and isolates with highest resistance (n=9) were selected and investigated for 16S rRNA methylase and AMES encoding genes by polymerase chain reaction (PCR) and sequencing. In general, aminoglycoside resistance was found in 95% of the isolates; the isolates displayed the highest rate of resistance to netilmicin (75%) and kanamycin (55%), while resistance to gentamycin (18%) and tobramycin (16%) was low. A total of 9 isolates have the highest aminoglycoside resistant rate, showed the highest appearance for aac(6′)-Ib as well as ant (3″)-Ia resistant genes, with aac (3)-II (44%) and ant (4′)-IIb (34%) following closely. The high prevalence of AMEs observed among resistant isolates in this study suggests the urgent need for more efficient treatment designs to mitigate the selection burden as well as improved care of patients who have been infected with these drug-resistant organisms.
Functional recovery of secondary tropical forests

Significance Tropical forests disappear rapidly through deforestation but also have the potential to regrow naturally through a process called secondary succession. To advance successional theory, it is essential to understand how these secondary forests and their assembly vary across broad spatial scales. We do so by synthesizing continental-scale patterns in succession using a functional trait approach. We show that the start and pathway of succession varies with climatic water availability. In dry forests, succession is driven by drought tolerance traits and in wet forests by shade tolerance traits. Based on these successional principles, we propose an ecologically sound strategy to improve active forest restoration. One-third of all Neotropical forests are secondary forests that regrow naturally after agricultural use through secondary succession. We need to understand better how and why succession varies across environmental gradients and broad geographic scales. Here, we analyze functional recovery using community data on seven plant characteristics (traits) of 1,016 forest plots from 30 chronosequence sites across the Neotropics. By analyzing communities in terms of their traits, we enhance understanding of the mechanisms of succession, assess ecosystem recovery, and use these insights to propose successful forest restoration strategies. Wet and dry forests diverged markedly for several traits that increase growth rate in wet forests but come at the expense of reduced drought tolerance, delay, or avoidance, which is important in seasonally dry forests. Dry and wet forests showed different successional pathways for several traits. In dry forests, species turnover is driven by drought tolerance traits that are important early in succession and in wet forests by shade tolerance traits that are important later in succession. In both forests, deciduous and compound-leaved trees decreased with forest age, probably because microclimatic conditions became less hot and dry. Our results suggest that climatic water availability drives functional recovery by influencing the start and trajectory of succession, resulting in a convergence of community trait values with forest age when vegetation cover builds up. Within plots, the range in functional trait values increased with age. Based on the observed successional trait changes, we indicate the consequences for carbon and nutrient cycling and propose an ecologically sound strategy to improve forest restoration success.
Twinning Time and Cost in Incentive-Based Contracts

The work presented in this paper focuses on contractual management of projects using a unique risk-management–driven strategy in which the twin variables of time and cost play a fundamental role. To illustrate the conceptual basis of this technique, an example project is presented first. Through the application of the writer's methodology to this project it has been shown how an incentive scheme could be set as the main contractual strategy with significant potential savings in both time and cost. The mean and 90% characteristic value for construction duration and cost, respectively, are estimated by the owner first using the writer's probabilistic forecasting method. These are used to specify an incentive scheme within which the two primary risk variables of time and cost are managed jointly by the owner and the contractor. Contractual issues such as owner's tender strategy, contractor's risk assessment, scope variation, and rise and fall adjustment have also been considered briefly.
Protocols for very high-speed optical fiber local area networks using a passive star topology

This paper deals with the problem of interconnection of many high-speed bursty traffic users via an optical passive star coupler. Each user can tune its laser over a range of wavelengths, thus resulting in a wavelength division multiplexed communication. The total number of wavelengths over which user tunability exists could be much smaller than the number of users. Therefore, some form of random access sharing and packet switching may be necessary. We propose several protocols that require each user to have a tunable receiver. The information on "where" and "when" to tune the laser is confined to a control (setup) channel that users tune to when in idle mode. An interconnection between two users lasting for the length of a data packet is set up on the control channel by the transmitting user who informs the receiving user where to tune in order to receive the data packet. No centralized control or coordination is required among the users. After analyzing each protocol, we present the throughput/ delay versus the offered traffic and the delay versus throughput in a sequence of plots. We show that in typical applications an average throughput of up to 0.95 can be achieved at a reasonable average delay using one of these protocols. In our benchmark examples we present an optical local area network (LAN) with a total throughput of 100- Gbit/s in which every user has access to a 1-Gbit/s data rate and the network can support over 1000 users. The protocols can be used in a) large LAN's that do not require a large capacity, b) small LAN's (1 kin) that require a large capacity and c) large LAN's (tens of kilometers) that require a rather large capacity.
Simulation of nonlinear standing wave excitation in very-high-frequency asymmetric capacitive discharges: roles of radial plasma density profile and rf power

It is recognized that in large-area, very-high-frequency capacitively coupled plasma (VHF CCP) reactors, the higher harmonics generated by nonlinear sheath motion can lead to enhanced standing wave excitation. In this work, a self-consistent electromagnetic model, which couples a one-dimensional, radial nonlinear transmission line model with a bulk plasma fluid model, is employed to investigate the nonlinear standing wave excitation in a VHF driven, geometrically asymmetric capacitive argon discharge operated at low pressure. By considering a radially non-uniform plasma density profile (case I) calculated self-consistently by the nonlinear electromagnetic model and the corresponding radially-averaged, uniform plasma density profile (case II), we first examine the effect of the plasma density non-uniformity on the propagation of electromagnetic surface waves in a 3 Pa argon discharge driven at 100 MHz and 90 W. Compared to case II, the higher plasma density at the radial center in case I determines a higher plasma series resonance frequency, yielding stronger high-order harmonic excitations and more significant central peak in the harmonic current density J z,n and the harmonic electron power absorption p n profiles. Therefore, under the assumption of the radially uniform plasma density in a CCP discharge, the self-excitation of higher harmonics at the radial center should be underestimated. Second, using the self-consistent electromagnetic model, the effect of the rf power on the excitation of nonlinear standing waves is investigated in a 3 Pa argon discharge driven at 100 MHz. At a low power of 30 W, the discharge is dominated by the first two harmonics. The higher harmonic excitations and the nonlinear standing waves are observed to be enhanced with increasing the rf power, resulting in a more pronounced central peak in the radial profiles of the total electron power absorption density p e, the electron temperature T e, and the electron density n e. For all rf powers, the calculated radial profiles of n e show good agreement with the experimental data obtained by a floating double probe.
Decision Making by Austin, Texas, Residents in Hypothetical Tornado Scenarios*

Abstract One of the goals of the Warning Project is to understand how people receive warnings of hazardous weather and subsequently use this information to make decisions. As part of the project, 519 surveys from Austin, Texas, floodplain residents were collected and analyzed. About 90% of respondents understood that a tornado warning represented a more serious and more likely threat than a tornado watch. Most respondents (86%) were not concerned about a limited number of false alarms or close calls reducing their confidence in future warnings, suggesting no cry-wolf effect. Most respondents reported safe decisions in two hypothetical scenarios: a tornado warning issued while the respondent was home and a tornado visible by the respondent while driving. However, nearly half the respondents indicated that they would seek shelter from a tornado under a highway overpass if they were driving. Despite the limitations of this study, these results suggest that more education is needed on the dangers of highway o.
Analytical performance evaluation of nonreturn-to-zero transmission systems operating in normally dispersive nonlinear fibers

An analytical theory for the evaluation of the performance of a nonreturn-to-zero (NRZ) transmission system operating in weakly normally dispersive nonlinear fibers is presented. Explicit expressions are given to compute an estimate of the transmission bit error rate, and those are compared with results obtained through numerical simulations. A good agreement is found, both for systems having fibers with a constant dispersion value, and for systems encompassing dispersion management technique.
Robot's motion decision-making system in unknown environment and its application to a mobile robot

A fuzzy decision-making system, which is developed from a fuzzy decision-making method and an autonomous functional architecture, for multi-objective robots motion planning and control is described. The system is applied to an omni-directional mobile robot with active stereo cameras capable of panoramic viewing. The mobile robot can be commanded to move to a target point through an unknown environment while satisfying multiple goals and constraints. The advantages of the proposed system are confirmed by simulation experiments.
Impact of low-rate sampling on the reconstruction of ECG in phase-space

This paper examines the chaotic and multifractal characteristics of the electrocardiogram (ECG) through its time series. Although multifractalities exist in the reconstructed strange attractor we find some limitations of strange attractor reconstruction from low-rate sampled (333 Hz) ECG signals by investigating the convergence of the false nearest neighbours and the Renyi dimension. The reconstruction parameters, lag of 4 and embedding dimension of 7, are obtained from experiments.