Miracle-dz/UniFAR-FTUs huggingface dataset:
Opinion mining of text documents written in Macedonian language

The ability to extract public opinion from web portals such as review sites, social networks and blogs will enable companies and individuals to form a view, an attitude and make decisions without having to do lengthy and costly researches and surveys. In this paper machine learning techniques are used for determining the polarity of forum posts on kajgana which are written in Macedonian language. The posts are classified as being positive, negative or neutral. We test different feature metrics and classifiers and provide detailed evaluation of their participation in improving the overall performance on a manually generated dataset. By achieving 92% accuracy, we show that the performance of systems for automated opinion mining is comparable to a human evaluator, thus making it a viable option for text data analysis. Finally, we present a few statistics derived from the forum posts using the developed system.
A DISCRETE TRACKING BASED-ON REGION FOR RED-LIGHT RUNNING DETECTION

Red-light running problem has been recognized as a significant safety problem in Indonesia as well as throughout the world. This is a frequent and highly dangerous driving act. Reducing this risk behavior depends on understanding its prevalence, as well as the drivers involved. However, it should also improve the infrastructure system in order to be an intelligent system. In this study, modeling and simulations are made to measure the speed of each vehicle that will pass through the intersection to predict the possibility of vehicles violating traffic lights. The detection of vehicle IDs used discrete tracking algorithm base on region. The result showed that the position data and time detection sensor used successfully to determine the average speed, the distance from the intersection and acceleration of the movement of vehicles. From the predicted results, a vehicle violates traffic lights reached 82.68%.
Using the Learner-Generated Digital Media (LGDM) Framework in Tertiary Science Education: A Pilot Study

Learner-Generated Digital Media (LGDM) has become prevalent in higher education. Frameworks have been developed for video-making in the classroom that consider technical requirements, pedagogies, and the combination of both. However, missing is a practical model to guide academics and students on the implementation of LGDM assignments. This research aims to test a model to design, implement, and evaluate LGDM as an assessment tool. The model was built based on research gaps and it considers the following elements: (1) pedagogy, (2) student training, (3) hosting of videos, (4) marking schemes, (5) group contribution, (6) feedback, (7) reflection, and (8) evaluation. For this purpose, five science subjects (N = 270) were used to test the model as a guide to implementing LGDM assignments. Data was gathered using a validated 33-step questionnaire instrument. Additionally, group contributions were received using the SPARKPlus peer review application, and marks attained were gathered. Methodological triangulation of the datasets suggested that students have a positive attitude toward LGDM for science learning. Students enjoyed the group work and creativity, and they identified digital media support as a critical component of their learning experience. Preliminary data support using the LGDM framework to design digital media assignments for science education.
SHORTEST PATH EMPLOYING DIJKSTRA AND MONTE CARLO METHOD

Traffic information system is a very popular problem as a tangible application of dijkstra algorithm to seek shortest path. In some application this problem is solved by employing heuristic approach from dijkstra, which it does not guarantee an optimum result. Those this paper does not only discuss about the seek shortest path base on dijkstra algorithm but emphasizes more on the combination between dijkstra algorithm and monte carlo method. Here the monte carlo method is being use as a way to calculate probability characteristic of a path way. For instance traffic jam, and traffic light. The combination of the two method will give a result of a shortest path in time basis. The system will take into account vehicle dependent, time dependent and the level of traffic jam and it also capable of giving out information in a form of direction.
Iron line spectroscopy of NGC 4593 with XMM–Newton: where is the black hole accretion disc?

We present an analysis of the 2-10 keV XMM-Newton/EPIC-pn spectrum of the Seyfert-1 galaxy NGC 4593. Apart from the presence of two narrow emission lines corresponding to the Ka lines of cold and hydrogen-like iron, this spectrum possesses a power-law form to within ∼3-5 per cent. There is a marked lack of spectral features from the relativistic regions of the black hole accretion disc. We show that the data are, however, consistent with the presence of a radiatively efficient accretion disc extending right down to the radius of marginal stability if it possesses low iron abundance, an appropriately ionized surface, a very high inclination, or a very centrally concentrated emission pattern (as has been observed during the deep minimum state of the Seyfert galaxy MCG-6-30-15). Deeper observations of this source are required in order to validate or reject these models.
Strings in a 2-d extremal black hole

String theory on 2-d charged black holes corresponding to (SL(2) ? U(1)L)/U(1) exact asymmetric quotient CFTs are investigated. These backgrounds can be embedded, in particular, in a two dimensional heterotic string. In the extremal case, the quotient CFT description captures the near horizon physics, and is equivalent to strings in AdS2 with a gauge field. Such string vacua possess an infinite space-time Virasoro symmetry, and hence enhancement of global space-time Lie symmetries to affine symmetries, in agreement with the conjectured AdS2/CFT1 correspondence. We argue that the entropy of these 2-d black holes in string theory is compatible with semi-classical results, and show that in perturbative computations part of an incoming flux is absorbed by the black hole. Moreover, on the way we find evidence that the 2-d heterotic string is closely related to the N = (2,1) string, and conjecture that they are dual [3].
Whole Genome Phylogeny via Complete Composition Vectors

The availability of complete genomic sequences allows us to infer the evolutionary footprints between species in a global strategy. However, the length of these genomic sequences poses a challenge on computational efficiency and optimality of information representation in phylogenetic analyses. In this paper, a new method called complete composition vector (CCV) is described to infer evolutionary relationships between species using their complete genomic sequences. In this method, the character string frequencies in the complete genomic sequence of each species are represented by a complete composition vector in a high-dimensional space. After being filtered out the random mutation background, cosines of the angles between the representing vectors are converted into pairwise evolutionary distances, based on which the phylogeny tree is constructed using the neighbor-joining algorithm. The method bypasses the complexity of performing multiple sequence alignments and avoids the ambiguity of choosing individual genes, whereas is expected to effectively retain the rich evolutionary information contained in the whole genomic sequence. To verify its strengths, the method was applied to infer the evolutionary footprints of coronaviruses and microbes. On a typical desktop PC, it took only one and half days to construct the phylogeny for 109 species containing 103 microbes and 6 eukaryotes. The phylogenetic trees generated by our method are highly consistent with those annotated by biologists. Primary Keyphrases: Phylogenetic analysis, Genome evolution, Genome comparison, Comparative genomics, Computational genetics Secondary Keyphrases: Phylogenetics: algorithms, Phylogenetics: statistical aspects ∗Bioinformatics Research Group, Department of Computing Science, University of Alberta. Edmonton, Alberta T6G 2E8, Canada. Emails: xiaomeng, wgang, ghlin@cs.ualberta. ca. †Digital Biology Laboratory, Department of Computer Science, University of Missouri – Columbia. Columbia, Missouri 65211, USA. Emails: wanx, xudong@missouri.edu. ‡To whom correspondence should be addressed. Fax: (780) 492-1071. Email: ghlin@cs.ualberta. ca.
An Improved Otsu Threshold Segmentation Method for Underwater Simultaneous Localization and Mapping-Based Navigation

The main focus of this paper is on extracting features with SOund Navigation And Ranging (SONAR) sensing for further underwater landmark-based Simultaneous Localization and Mapping (SLAM). According to the characteristics of sonar images, in this paper, an improved Otsu threshold segmentation method (TSM) has been developed for feature detection. In combination with a contour detection algorithm, the foreground objects, although presenting different feature shapes, are separated much faster and more precisely than by other segmentation methods. Tests have been made with side-scan sonar (SSS) and forward-looking sonar (FLS) images in comparison with other four TSMs, namely the traditional Otsu method, the local TSM, the iterative TSM and the maximum entropy TSM. For all the sonar images presented in this work, the computational time of the improved Otsu TSM is much lower than that of the maximum entropy TSM, which achieves the highest segmentation precision among the four above mentioned TSMs. As a result of the segmentations, the centroids of the main extracted regions have been computed to represent point landmarks which can be used for navigation, e.g., with the help of an Augmented Extended Kalman Filter (AEKF)-based SLAM algorithm. The AEKF-SLAM approach is a recursive and iterative estimation-update process, which besides a prediction and an update stage (as in classical Extended Kalman Filter (EKF)), includes an augmentation stage. During navigation, the robot localizes the centroids of different segments of features in sonar images, which are detected by our improved Otsu TSM, as point landmarks. Using them with the AEKF achieves more accurate and robust estimations of the robot pose and the landmark positions, than with those detected by the maximum entropy TSM. Together with the landmarks identified by the proposed segmentation algorithm, the AEKF-SLAM has achieved reliable detection of cycles in the map and consistent map update on loop closure, which is shown in simulated experiments.
Comparison between Hybridoma and Fab/phage Anti-RhD: Their V Gene Usage and Pairings

Our 11 anti-RhD's in conjunction with 37 previously published RhD antibodies, produced by hybridoma technology were analysed for germline gene usage and restriction in VH and VL pairings. The 17 VH germline genes used by the hybridoma anti-RhD IgG were derived from 4 VH families (VH1, VH2, VH3 and VH4). Eighteen kappa chains were restricted to only 5 germline genes from only 2 Vκ families (Vκ1 and κ3). However, the 13 lambda chains were not as restricted, using 10 Vλ germline genes from 4 families (Vλ1, Vλ2, Vλ3 and Vλ8). Fifty six unique Fab/phage anti-RhD were also analysed. In all cases the Fab/phage VH germline genes were derived from the VH3 family (41/41). The 29 kappa chains were restricted to 4 germline genes primarily from Vκ1 (97%) germline genes from 5 families (Vλ1, Vλ2, Vλ3, Vλ4 and Vλ7). The VH germline genes of the Fab/phage were restricted to 4 of the 17 used by the hybridoma anti-RhD IgG (DP46, DP49, DP50 and DP77). Ninety percent of the Fab/phage were restricted to 1 of the 5 Vκ germline genes used by the IgG (DPK9). However, the repertoire of the Vλ germline genes used in these two systems is different, with analysis showing greater diversity in Vλ gene usage with 8 unique germline genes used by 76% Fab/phage compared to 4 unique genes used by 46% hybriboma anti-RhD.
Simulating the Implementation of Business Information Systems: The Case of Enterprise Resource Planning

This paper seeks to understand the dynamics of information systems implementation within firms and more specifically focuses on the case of Enterprise Resource Planning (ERP). This contribution applies a simple differential equation based model to a real firm and successfully fits the model to the observed data. The model is able to predict the implementation time under various conditions. In a broader perspective, the paper discusses the use of simulations and how these methods could be the engine behind actionable managerial tools. This contribution outlines that these tools will become more prevalent in the future as graphics hardware becomes utilised, allowing computational intensive simulations to be performed far more cheaply and quickly than is currently possible.
Uncertainty in the fate of soil organic carbon: A comparison of three conceptually different decomposition models at a larch plantation

Conventional Q10 soil organic matter decomposition models and more complex microbial models are available for making projections of future soil carbon dynamics. However, it is unclear (1) how well the conceptually different approaches can simulate observed decomposition and (2) to what extent the trajectories of long‐term simulations differ when using the different approaches. In this study, we compared three structurally different soil carbon (C) decomposition models (one Q10 and two microbial models of different complexity), each with a one‐ and two‐horizon version. The models were calibrated and validated using 4 years of measurements of heterotrophic soil CO2 efflux from trenched plots in a Dahurian larch (Larix gmelinii Rupr.) plantation. All models reproduced the observed heterotrophic component of soil CO2 efflux, but the trajectories of soil carbon dynamics differed substantially in 100 year simulations with and without warming and increased litterfall input, with microbial models that produced better agreement with observed changes in soil organic C in long‐term warming experiments. Our results also suggest that both constant and varying carbon use efficiency are plausible when modeling future decomposition dynamics and that the use of a short‐term (e.g., a few years) period of measurement is insufficient to adequately constrain model parameters that represent long‐term responses of microbial thermal adaption. These results highlight the need to reframe the representation of decomposition models and to constrain parameters with long‐term observations and multiple data streams. We urge caution in interpreting future soil carbon responses derived from existing decomposition models because both conceptual and parameter uncertainties are substantial.
Correlation of FRAX Risk Score and Severity in Osteoporotic Vertebral Fracture

Objectives: To identify the correlation between FRAX risk score and severity of osteoporotic vertebral fracture Methods: The study subjects were 214 in-patients who had osteoporotic vertebral fracture. The subjects were divided into 2 groups according to whether or not they had a BMD score (BMD, non-BMD group). Fracture severity index was calculated from lateral vertebral x-ray film with Genant's semiquantitive method. The correlation between FRAX risk score and fracture severity index were analyzed. Results: Significant correlation was detected between FRAX risk score (major osteoporotic & hip fracture) and fracture severity index in the BMD group (r=0.463, p<0.001, r=0.446, p<0.001) as well as between FRAX risk score and BMD (r=-0.322, p<0.001). There was no correlation in the non-BMD group Conclusions: This study demonstrates a correlation between FRAX risk score and osteoporotic vertebral fracture severity in BMD group.
Link prediction based on generalized cluster information

Understanding of which new interactions among data objects are likely to occur in the future is crucial for a deeper understanding of network dynamics and evolution. This question is largely unexplored except a local neighborhood perspective, partly owing to the difficulty in finding major factors which heavily affect the link prediction problem. In this paper, we propose LPCSP, a novel link prediction method which exploits the generalized cluster information containing cluster relations and cluster evolution information. Experiments show that our proposed LPCSP is accurate, scalable, and useful for link prediction on real world graphs.
Specification and verification of the Co/sub 4/ distributed knowledge system using LOTOS

This paper relates the formal specification and verification of a consensual decision protocol based on Co/sub 4/, a computer environment dedicated to the building of a distributed knowledge base. This protocol has been specified in the ISO formal description technique LOTOS. The CADP tools from the EUCALYPTUS LOTOS toolset have been used to verify different safety and liveness properties. The verification work has confirmed an announced violation of knowledge consistency and has put forth a case of inconsistent hierarchy, four cases of unexpected message reception and some further local corrections in the definition of the protocol.
Serglycin is part of the secretory repertoire of LPS-activated monocytes

Monocytes play multiple roles in the immune system, and are active in both acute and chronic diseases. Patients exposed to bacterial infections depend on monocytes in defense reactions, but excessive immune reactions may also cause morbidity through systemic inflammatory responses. Few studies have addressed the importance of proteoglycans, and in particular, the hematopoietic serglycin, in such monocyte immune reactions. Adherent primary monocytes were cultured in absence and presence of LPS. Media were analyzed by ELISA for detection of serglycin. Lysed cell fractions were used to determine the mRNA level of serglycin. Monocytes were also cultured on chamber slides to investigate if serglycin could be detected intracellularly by immunocytochemistry. Monocytes secreted serglycin, and LPS‐stimulation increased the secretion. Secretion of inflammatory cytokines increased to a larger extent than serglycin. mRNA levels of serglycin were also increased, suggesting both increased expression and secretion. Immunocytochemistry revealed the presence of serglycin in intracellular vesicles, many destined for secretion. Serglycin containing vesicles increased in number and size when the cells were exposed to LPS. Intracellular vesicle localization and secretion of the proteoglycan serglycin is shown for the first time in primary human monocytes. Monocyte activation by LPS increased the expression and secretion of serglycin, suggesting roles for serglycin in inflammatory processes.
A comparative study of probabilistic ranking models for spoken document summarization

The purpose of extractive document summarization is to automatically select a number of indicative sentences, passages, or paragraphs from the original document according to a target summarization ratio and then sequence them to form a concise summary. In the paper, we present a comparative study of various supervised and unsupervised probabilistic ranking models for spoken document summarization on the Chinese broadcast news. Moreover, we also investigate the possibility of using unsupervised summarizers to boost the performance of supervised summarizers when manual labels are not available for the training of supervised summarizers. Encouraging results were initially demonstrated.
Does generational status matter in college? Expectations and academic performance among second-generation college students in the US

Using the 2004–2009 wave of the Beginning Postsecondary Students Longitudinal Study, a nationally representative sample of students who enroll in college in 2004, we examine generational differences in the relationship between educational expectations, academic achievement, and college persistence among native-born and immigrant youth in the United States. Using the theory of immigrant optimism, which has primarily focused on high school youth, we examine whether immigrant parents provide children an advantage in completing their college degrees. Our analyses suggest that students who have at least one immigrant parent are (1) more likely to expect to earn advanced degrees and (2) more likely to complete college on time and less likely to withdraw with no degree compared to their counterparts with native-born parents. We also find that the higher expectations held by these students are associated with higher levels of persistence and attainment. We argue that the optimism conferred by having immigrant parents persists through young adulthood.
Gesture generation with low-dimensional embeddings

There is a growing demand for embodied agents capable of engaging in face-to-face dialog using the same verbal and nonverbal behavior that people use. The focus of our work is generating coverbal hand gestures for these agents, gestures coupled to the content and timing of speech. A common approach to achieve this is to use motion capture of an actor or hand-crafted animations for each utterance. An alternative machine learning approach that saves development effort is to learn a general gesture controller that can generate behavior for novel utterances. However learning a direct mapping from speech to gesture movement faces the complexity of inferring the relation between the two time series of speech and gesture motion. We present a novel machine learning approach that decomposes the overall learning problem into learning two mappings: from speech to a gestural annotation and from gestural annotation to gesture motion. The combined model learns to synthesize natural gesture animation from speech audio. We assess the quality of generated animations by comparing them with the result generated by a previous approach that learns a direct mapping. Results from a human subject study show that our framework is perceived to be significantly better.
Varying linezolid susceptibility of vancomycin-resistant Enterococcus faecium isolates during therapy: a case report.

OBJECTIVES Linezolid is an oxazolidinone antibiotic used in the treatment of infections caused by vancomycin-resistant enterococci. Resistance to linezolid has been associated with a G2576U mutation in domain V of the 23S rRNA. PATIENT AND METHODS We present clinical details and susceptibility data from multiple Enterococcus faecium strains isolated from a liver transplant patient over 13 months. MICs of linezolid, vancomycin and quinupristin/dalfopristin were determined using Etest. Molecular typing was performed by pulsed-field gel electrophoresis. Domain V of the 23S rRNA gene in the vancomycin-resistant Enterococcus faecium was amplified. Linezolid concentrations were analysed by HPLC. RESULTS We report the emergence of resistance to linezolid in a vancomycin-resistant Enterococcus faecium during linezolid treatment. After discontinuation of the linezolid therapy, the isolate reverted to susceptibility. However, after re-administration of linezolid the vancomycin-resistant Enterococcus faecium became resistant to linezolid again. The isolates that were resistant to linezolid had a G2576T mutation in their 23S rDNA. CONCLUSION We describe a clinical case that shows the shift of a vancomycin-resistant Enterococcus faecium from linezolid resistance to susceptibility and then back to resistance again related to linezolid therapy.