Miracle-dz/UniFAR-FTUs huggingface dataset:
Hierarchical Rhetorical Sentence Categorization for Scientific Papers

Important information in scientific papers can be composed of rhetorical sentences that is structured from certain categories. To get this information, text categorization should be conducted. Actually, some works in this task have been completed by employing word frequency, semantic similarity words, hierarchical classification, and the others. Therefore, this paper aims to present the rhetorical sentence categorization from scientific paper by employing TF-IDF and Word2Vec to capture word frequency and semantic similarity words and employing hierarchical classification. Every experiment is tested in two classifiers, namely Naïve Bayes and SVM Linear. This paper shows that hierarchical classifier is better than flat classifier employing either TF-IDF or Word2Vec, although it increases only almost 2% from 27.82% when using flat classifier until 29.61% when using hierarchical classifier. It shows also different learning model for child-category can be built by hierarchical classifier.
Topological design for wireless sensor networks for riverbank based on geographical characteristics

This paper investigates the mechanism for nodes placement along the riverbanks. The proposed algorithm intends to minimize the total number of sensor nodes with several constraints such as network connectivity and network reliability. This algorithm also aims to achieve the maximum transmission distance along the riverbank which will guarantee the river sensored information coverage, connectivity and reliability. The proposed algorithm will be adjustable to the geographical profiles of the river. Simulation results are obtained from four different river profiles. The proposed algorithm performs well as it could reduce the number of sensor nodes needed for sensoring.
Distortion Optimization based Image Completion from a Large Displacement View

We present a new image completion method based on an additional large displacement view (LDV) of the same scene for faithfully repairing large missing regions on the target image in an automatic way. A coarse‐to‐fine distortion correction algorithm is proposed to minimize the perspective distortion in the corresponding parts for the common scene regions on the LDV image. First, under the assumption of a planar scene, the LDV image is warped according to a homography to generate the initial correction result. Second, the residual distortions in the common known scene regions are revealed by means of a mismatch detection mechanism and relaxed by energy optimization of overlap correspondences, with the expectations of color constancy and displacement field smoothness. The fundamental matrix for the two views is then computed based on the reliable correspondence set. Third, under the constraints of epipolar geometry, displacement field smoothness and color consistency of the neighboring pixels, the missing pixels are orderly restored according to a specially defined repairing priority function. We finally eliminate the ghost effect between the repaired region and its surroundings by Poisson image blending. Experimental results demonstrate that our method outperforms recent state‐of‐the‐art image completion methods for repairing large missing area with complex structure information.
Microstructural anatomical differences between bilinguals and monolinguals

DTI is an established method to study cerebral white-matter microstructure. Two established measures of DTI are fractional anisotropy (FA) and mean diffusivity (MD) and both differ for bilingual and monolingual speakers. Less is known about differences in two other measures called radial (RD) and axial diffusivity (AD). We report differences in mean RD and AD-values in the right superior longitudinal fasciculus (SLF) and forceps minor between bilingual (Hindi–English) and monolingual (English) speakers as well as differences in mean FA-values in the anterior thalamic radiation, right inferior fronto-occipital and inferior longitudinal fasciculus (ILF) and mean MD-values in forceps minor and bilateral SLF. Noteworthy, a positive correlation between L2 proficiency and mean RD-values in the right SLF was observed. We suggest that changes in the geometry of white matter tracts reflect regular bilingual language experience and contend that neuroplasticity in right SLF results from demands on cognitive control for bilingual speakers.
Forecasting Crimes Using Autoregressive Models

As a result of steadily increasing urbanization, by 2030 more than sixty percent of the global population will live in cities. This phenomenon is stimulating significant economic and social transformations, both positive (such as, increased opportunities offered in urban areas) and negative (such as, increased crime and pressures on city budgets). Nevertheless, new technologies are enabling police departments to access growing volumes of crime-related data that can be analyzed to understand patterns and trends. Such knowledge is useful to anticipate criminal activity and thus to optimize public safety resource allocation (officers, patrol routes, etc.) through mathematical techniques to predict crimes. This paper presents an approach, based on auto-regressive models, for reliably forecasting crime trends in urban areas. In particular, the main goal of the work is to design a predictive model to forecast the number of crimes that will happen in rolling time horizons. As a case study, we present the analysis performed on an area of Chicago, using a variety of open data sources available for exploration and examination through the University of Chicagos Plenario platform. Experimental evaluation shows that the proposed methodology predicts the number of crimes with an accuracy of 84% on one-year-ahead forecasts and of 80% on two-year-ahead forecasts.
Visualisation of heart rate and blood pressure dysregulation in young patients with type 1 diabetes mellitus by Poincaré plot

Time series analysis of cardiovascular signals is usually performed by linear methods. Inspired by an effort to apply nonlinear time series analysis into cardiovascular variability signals, the aim of this study was to compare heart rate and blood pressure variabilities (HRV and BPV) between young patients with type 1 diabetes mellitus (DM) and control subjects by Poincare plot. We analysed supine rest HRV and BPV time series using Poincare plot pattern analysis. The length and widths of Poincare plot were evaluated by self-developed software. In patients with type 1 DM, we found significant reduction of all HRV Poincare plot measures indicating heart rate dysregulation detected in visually understandable manner. However, no significant differences in BPV Poincare plot measures were observed - we suggest that dysregulation of vessels" sympathetic control occurs later in the course of DM.
Identification of live news events using Twitter

Twitter presents a source of information that cannot easily be obtained anywhere else. However, though many posts on Twitter reveal up-to-the-minute information about events in the world or interesting sentiments, far more posts are of no interest to the general audience. A method to determine which Twitter users are posting reliable information and which posts are interesting is presented. Using this information a search through a large, online news corpus is conducted to discover future events before they occur along with information about the location of the event. These events can be identified with a high degree of accuracy by verifying that an event found in one news article is found in other similar news articles, since any event interesting to a general audience will likely have more than one news story written about it. Twitter posts near the time of the event can then be identified as interesting if they match the event in terms of keywords or location. This method enables the discovery of interesting posts about current and future events and helps in the identification of reliable users.
Scale-invariant line descriptors for wide baseline matching

In this paper we propose a method to add scale-invariance to line descriptors for wide baseline matching purposes. While finding point correspondences among different views is a well-studied problem, there still remain difficult cases where it performs poorly, such as textureless scenes, ambiguities and extreme transformations. For these cases using line segment correspondences is a valuable addition for finding sufficient matches. Our general method for adding scale-invariance to line segment descriptors consist of 5 basic rules. We apply these rules to enhance both the line descriptor described by Bay et al. [1] and the mean-standard deviation line descriptor (MSLD) proposed by Wang et al. [14]. Moreover, we examine the effect of the line descriptors when combined with the topological filtering method proposed by Bay et al. and the recent proposed graph matching strategy from K-VLD [6]. We validate the method using standard point correspondence benchmarks and more challenging new ones. Adding scale-invariance increases the accuracy when confronted with big scale changes and increases the number of inliers in the general case, both resulting in smaller calibration errors by means of RANSAC-like techniques and epipolar estimations.
What's New in Development Economics?

too: the study of economic development is probably the most challenging in all of economics, and pro vided we are patient about getting to "the bottom line" and the "policy implications," it can have enormous payoffs. Fortunately, considerations of space allow me to use brevity as an excuse for selectivity. So rather than attempt an exhaustive review of several areas, I would like to concentrate on a few methodologi cal points around which recent literature appears to have clustered. More than anything else, I want to bring out for you a certain way of thinking about development that has become increasingly influen tial over the last couple of decades, one that is changing and will continue to change the face of research in this discipline. The main trend I would like to try and document is a move? welcome, in my opinion? away from a traditional preoccupation with the notion of conver gence. This is the basic notion that given certain parameters, say savings or fertility rates, economies inevitably move towards some steady state. If these parameters are the same across economies, then in the long run all economies converge to one another.
The developmental course and outcome of reading disability in a population followed from kindergarten to young adulthood

THE OUTCOME OF READING DISABILITY IN A POPULATION FOLLOWED FROM KINDERGARTEN TO YOUNG ADULTHOOD Fabienne C. Bourgeois, John M. Holahan PhD, Bennett A Shaywitz MD, Sally E Shaywitz MD, Department of Pediatrics, Yale University, School of Medicine, New
Looking in From the Outside: Perspectives of Caring for an Individual Diagnosed with Agenesis of the Corpus Callosum

Agenesis of the corpus callosum (AgCC) is a rare condition in which the neural connection between the left and right hemispheres of the brain is missing. This descriptive phenomenological study included the voices of 82 individuals, spanning three countries, who were identified as family members and caregivers of individuals diagnosed with AgCC, and three adults diagnosed with AgCC living independently. Analysis of the data revealed there was a lack of information about the disorder to support families and health professionals. Results of the study provide insight into the financial struggles, relationship issues, and the hopes for the future through the lived experiences of the participants. There is an undeniable impact upon families of individuals born with disabilities. As the number of individuals with AgCC continues to escalate due to improved medical techniques, proactive problem-solving for children and adults with AgCC must be considered.
Prevalence of high blood pressure and elevated serum creatinine level in the United States: findings from the third National Health and Nutrition Examination Survey (1988-1994).

BACKGROUND The prevalence and incidence of end-stage renal disease in the United States are increasing, but milder renal disease is much more common and may often go undiagnosed and undertreated. METHODS A cross-sectional study of a representative sample of the US population was conducted using 16 589 adult participants aged 17 years and older in the Third National Health and Nutrition Examination Survey (NHANES III) conducted from 1988 to 1994. An elevated serum creatinine level was defined as 141 micromol/L or higher (>/=1.6 mg/dL) for men and 124 micromol/L or higher (>/=1.4 mg/dL) for women (>99th percentile for healthy young adults) and was the main outcome measure. RESULTS Higher systolic and diastolic blood pressures, presence of hypertension, antihypertensive medication use, older age, and diabetes mellitus were all associated with higher serum creatinine levels. An estimated 3.0% (5.6 million) of the civilian, noninstitutionalized US population had elevated serum creatinine levels, 70% of whom were hypertensive. Among hypertensive individuals with an elevated serum creatinine level, 75% received treatment. However, only 11% of all individuals with hypertension had their blood pressure reduced to lower than 130/85 mm Hg (the Sixth Report of the Joint National Committee on Detection, Evaluation, and Treatment of High Blood Pressure recommendation for hypertensive individuals with renal disease); 27% had a blood pressure lower than 140/90 mm Hg. Treated hypertensive individuals with an elevated creatinine level had a mean blood pressure of 147/77 mm Hg, 48% of whom were prescribed one antihypertensive medication. CONCLUSION Elevated serum creatinine level, an indicator of chronic renal disease, is common and strongly related to inadequate treatment of high blood pressure.
A Game-inspired Modeling Framework for Multiple Intelligent Agents Control Systems - A Water Resources Regulation Problem Application

Some interesting papers apply concepts and modeling approaches for multiple interacting intelligent autonomous agents control systems analysis and design inspired in game theory, where 'players' are treated as 'agents', in several conflicts of interests situations. This paper presents and uses the named strategic games matrix (SGM) as a general framework for these new types of control problems. A methodology for analysis of hierarchical multilevel architectures models based on the SGM concept is applied to a water resources regulation control problem, with multiple interacting autonomous stakeholders, as posed by Hamalaien et al as "The Paijanne lake regulation policy" case.
A novel in vivo assay for the analysis of protein-protein interaction

The Ras Recruitment System (RRS) is a method for identification and isolation of protein-protein interaction. The method is based on translocation of cytoplasmic mammalian Ras protein to the inner leaflet of the plasma membrane through protein-protein interaction. The system is studied in a temperature-sensitive yeast strain where the yeast Ras guanyl nucleotide exchange factor is inactive at 36 degrees C. Protein-protein interaction results in cell growth at the restrictive temperature. We developed a gene reporter assay for the analysis of protein-protein interaction in mammalian cells. Ras activation in mammalian cells induces the mitogen-activated kinase cascade (MAPK), which can be monitored using Ras-dependent reporter genes. This greatly extends the usefulness of the system and provides a novel assay for protein-protein interaction in mammalian cells.
Intrusion detection using adaptive time-dependent finite automata

In intrusion detection system, signature discovery is an important issue, since the performance of an intrusion detection system heavily depends on the accuracy and abundance of signatures. In most cases, we have to find these signatures manually. This is a time-consuming and error-prone work. Some researchers apply data mining to the intrusion detection system. However, they are almost for anomal IDS detection. In this paper, we use a causal knowledge based on inference technique to discover useful signature for intrusion, and to raise the detection performance. The paper presents how Hsiao's sequential approach and finite automata are used in the causal knowledge acquisition and to support the causal knowledge reasoning process.
Aging Increases Aortic MMP‐2 Activity and Angiotensin II in Nonhuman Primates

Abstract— To seek evidence that the nonhuman primate arterial wall, as it ages in the absence of atherosclerosis, exhibits alterations in pathways that are involved in the pathogenesis of experimental atherosclerosis, we assessed aortic matrix metalloproteinase‐2 (MMP‐2) and its regulators, ie, membrane type‐1 of matrix metalloproteinase (MT1‐MMP) and tissue inhibitor of matrix metalloproteinase‐2 (TIMP‐2), and the expression of angiotensin II (Ang II), angiotensin‐converting enzyme (ACE), and chymase in young (6.4±0.7 years) and old (20.0±1.9 years) male monkeys. With advancing age, (1) the intimal thickness increased 3‐fold and contained numerous vascular smooth muscle cells and matrix, but no inflammatory cells; (2) the intimal MMP‐2 antibody–staining fraction increased by 80% (P <0.01); (3) in situ zymography showed that MMP‐2 activity, mainly confined to the intima, increased 3‐fold (P <0.01); (4) the MT1‐MMP antibody–staining fraction increased by 150% (P <0.001), but the TIMP‐2 antibody–staining fraction did not significantly change; (5) steady levels of the mRNA‐staining fraction (via in situ hybridization) for MMP‐2 increased 7‐fold, for MT1‐MMP increased 9‐fold, and for TIMP‐2 increased 2‐fold (all P <0.001); and (6) intimal Ang II and ACE immunofluorescence were increased 5‐fold and 5.6‐fold, respectively, and colocalized with MMP‐2. Thus, age‐associated arterial remodeling and the development and progression of experimental atherosclerosis in young animals share common mechanisms, ie, MMP‐2 activation and increased Ang II signaling. This might explain, in part, the dramatically exaggerated prevalence and severity of vascular diseases with aging.
Diversity of low-density lattices

We describe full-diversity constructions of real lattices defined by their integer-check matrix, i.e. the inverse of their generator matrix. In the first construction suited to maximum-likelihood decoding, these lattices are defined by sparse (low-density) or non-sparse integer-check matrices. Based on a special structure of the lattice binary image, a second full-diversity lattice construction is described for sparse integer-check matrices in the context of iterative probabilistic decoding. Full diversity is theoretically proved in both cases. Computer simulation results also confirm that the proposed low-density lattices attain the maximal diversity order.
The Stability of Magnetized Rotating Plasmas with Superthermal Fields

During the last decade it has become evident that the magnetorotational instability is at the heart of the enhanced angular momentum transport in weakly magnetized accretion disks around neutron stars and black holes. In this paper we investigate the local linear stability of differentially rotating, magnetized flows and the evolution of the magnetorotational instability beyond the weak-field limit. We show that, when superthermal toroidal fields are considered, the effects of both compressibility and magnetic tension forces, which are related to the curvature of toroidal field lines, should be taken fully into account. We demonstrate that the presence of a strong toroidal component in the magnetic field plays a nontrivial role. When strong fields are considered, the strength of the toroidal magnetic field not only modifies the growth rates of the unstable modes but also determines which modes are subject to instabilities. We find that, for rotating configurations with Keplerian laws, the magnetorotational instability is stabilized at low wavenumbers for toroidal Alfvén speeds exceeding the geometric mean of the sound speed and the rotational speed. For a broad range of magnetic field strengths, we also find that two additional distinct instabilities are present; they both appear as the result of coupling between the modes that become the Alfvén and the slow modes in the limit of no rotation. We discuss the significance of our findings for the stability of cold, magnetically dominated, rotating fluids and argue that, for these systems, the curvature of toroidal field lines cannot be neglected even when short-wavelength perturbations are considered. We also comment on the implications of our results for the validity of shearing box simulations in which superthermal toroidal fields are generated.
D2MOPSO: MOPSO Based on Decomposition and Dominance with Archiving Using Crowding Distance in Objective and Solution Spaces

This paper improves a recently developed multi-objective particle swarm optimizer () that incorporates dominance with decomposition used in the context of multi-objective optimization. Decomposition simplifies a multi-objective problem (MOP) by transforming it to a set of aggregation problems, whereas dominance plays a major role in building the leaders’ archive. introduces a new archiving technique that facilitates attaining better diversity and coverage in both objective and solution spaces. The improved method is evaluated on standard benchmarks including both constrained and unconstrained test problems, by comparing it with three state of the art multi-objective evolutionary algorithms: MOEA/D, OMOPSO, and dMOPSO. The comparison and analysis of the experimental results, supported by statistical tests, indicate that the proposed algorithm is highly competitive, efficient, and applicable to a wide range of multi-objective optimization problems.
Supporting the monitoring of the verification process of critical systems'software

Critical software systems face stringent requirements in safety, security, and reliability due to the circumstances surrounding their operation. Safety and security have progressively gained importance over the years due to the integration of hardware with software-intensive deployments that introduce additional sources of errors. It is, then, necessary to follow high-quality exhaustive software development processes that besides the needed development activities to increase safety and security also integrate techniques to increase the reliability of the software development process itself. In practice, the use of automated techniques for the verification of the verification process is, however, not sufficiently wide spread. This is mainly due to the high cost of the required techniques and to their degree of complexity when adjusting to the different norms and regulations. This work presents an approach for comprehensive management of the verification processes; the approach allows engineers to monitor and control the project status regarding the applicable standards. This approach has been validated through its implementation in a tool and its application to real projects.
A New DL-Lite N Bool Probabilistic Extension Using Belief

Dealing with uncertainty is a very important issue in description logics (DLs). In this paper, we present PrDL‐ Litebool N a new probabilistic extension of DL‐ Litebool N by supporting the belief interval in a single axiom or a set of axioms connected with conjunction (by ∧ ) or disjunction (by ∨ ) operators. The PrDL‐ Litebool N semantics is based on DL‐ Litebool N features which are a new alternative semantics for DL‐ Litebool N having a finite structure and its number is always finite unlike classical models. PrDL‐ Litebool N also supports terminological and assertional probabilistic knowledge and the main reasoning tasks: satisfiability, deciding the probabilistic axiom entailment and computing tight interval for entailment are achieved by solving linear constraints system. A prototype is implemented using OWL API for knowledge base creation, Pellet for reasoning and LpSolve for solving the linear programs.