Miracle-dz/UniFAR-FTUs huggingface dataset:
Constraining Plane Configurations in CAD: Circles, Lines, and Angles in the Plane

This paper investigates the local uniqueness of designs of m-circles (lines and circles) in the plane up to inversion under a set of angles of intersection as constraints. This local behavior is studied through the Jacobian of the angle measurements in a form analogous to the rigidity matrix for a framework of points with distance constraints. After showing directly that the complete set of angle constraints on v distinct m-circles gives a matrix of rank 3v - 6, we show that the Jacobian is column equivalent by a geometric correspondence to the rigidity matrix for a bar-and-joint framework in Euclidean 3-space. As a corollary, the complexity of the independence of angle constraints on generic plane circles is the complexity of the old unsolved combinatorial problem of generic rigidity in 3-space. This theory is not known to have a polynomial time algorithm for generic independence that offers a warning about the complexity of general systems of geometric constraints even in the plane. Our correspondence extends to all dimensions. Angle constraints on spheres in 3-space then match the even more complex first-order theory of frameworks in 4-space. This theory is not predicted to have a polynomial time algorithm for generic points.
Reassembling the Fragmented JPEG Images Based on Sequential Pixel Prediction

File carving is a digital forensic technique which data files are extracted from unstructured data sources without the information of the previously stored file system. Since JPEG is one of the most popular image formats in the storage and distribution of digital photographic imagery, JPEG Carving aroused numerous researchers’ great interest. In this paper, a new algorithm of reassembling the fragmented JPEG file is described. To reassemble the fragmented JPEG file, a sequential pixel prediction model based on the neural network was proposed to determine whether or not the given fragment is adjacent to the last fragment in the original. The performance results obtained from the fragmented test-sets of DFRWS 2006 show that the method can be effectively used in recovery of fragmented JPEG files. Keywords-component; data recovery; file carving; BP algorithm; digital forensics
Neural Systems for Scene Recognition Differential Parahippocampal and Retrosplenial Involvement in Three Types of Visual Scene Recognition Neural Systems for Scene Recognition

Human observers can quickly and accurately interpret the meaning of complex visual scenes. The neural mechanisms underlying this ability are largely unexplored. We used functional magnetic resonance imaging (fMRI) to measure cortical activity while subjects identified briefly-presented scenes as either specific familiar locations ("Houston Hall"), general place categories ("kitchen"), or general situational categories ("party"). Sceneresponsive voxels in the parahippocampal place area (PPA) and retrosplenial cortex (RSC) were highly sensitive to recognition level when identifying scenes, responding more strongly during location identification than during place category or situation identification. In contrast, the superior temporal sulcus, cingulate sulcus, and supermarginal gyrus displayed the opposite pattern, responding more strongly during place category and situtation identification. Consideration of results from four experiments suggest that the PPA represents the visuospatial structure of individual scenes, while RSC supports processes that allow scenes to be localized within a larger extended environment. These results suggest that different scene identification tasks tap distinct cortical networks. In particular, we hypothesize that the PPA and RSC are critically involved in the identification of specific locations but play a less central role in other scene recognition tasks.
Analysis Of STK11/LKB1 Gene Using Bioinformatics Tools

Aim: The STK11 gene, also known as LKB1, encodes for a serine/threonine kinase with growth-suppressing activity, such as inhibition of cell cycle progression, cell growth retardation, apoptotic cell death, and cell polarity control. This study aimed to investigate some properties of the STK11 gene and its product, such as the homologous protein sequences in different species, the common transcription factor binding sites on their promoters, their phylogenetic relationship, their catalytic domains (S_TKc), and their expression profiles. Methods: We investigated the homology, conserved domain, promoter and expression profiles of the STK11/LKB1 genes in various species using bioinformatics approaches. Results: Our results revealed that STK11/LKB1 molecules are conserved among all organisms investigated. The kinase domain (S_TKc) of human STK11/LKB1 gene is closest to those of Pan troglodytes, Macaca mulatta and Macaca fascicularis. In contrast, the most diverse to the human S_TKc domain is that of Bos taurus. With the multiple alignment strategy, protein and domain sequences of M. fascicularis and B. Taurus are predicted to have a truncation. The comparative screening of the promoters demonstrated that STK11/LKB1 genes do not seem to have any common conserved transcription factor binding sites. Conclusion: This study demonstrated STK11 molecules in various species are well conserved throughout evolution. Comparative screening of the promoter sequences of the human STK11 and its homologues found in the NCBI database revealed that there was no any common transcription factor binding sites. Phylogenetic trees constructed using the neighbor-joining method (NJ) revealed a close evolutionary relationship of S_TKc in various species.
Emotions analysis of speech for call classification

Most existing research in the area of emotions recognition has focused on short segments or utterances of speech. In this paper we propose a machine learning system for classifying the overall sentiment of long conversations as being Positive or Negative. Our system has three main phases, first it divides a call into short segments, second it applies machine learning to recognize the emotion for each segment, and finally it learns a binary classifier that takes the recognized emotions of individual segments as features. We investigate different approaches for this final phase by varying how emotions for individual segments are aggregated and also by varying classification model used for the final phase. We present our experimental results and analysis based on a simulated data set collected specifically for this research.
Reconstructing Past Populations With Uncertainty From Fragmentary Data

Current methods for reconstructing human populations of the past by age and sex are deterministic or do not formally account for measurement error. We propose a method for simultaneously estimating age-specific population counts, fertility rates, mortality rates, and net international migration flows from fragmentary data that incorporates measurement error. Inference is based on joint posterior probability distributions that yield fully probabilistic interval estimates. It is designed for the kind of data commonly collected in modern demographic surveys and censuses. Population dynamics over the period of reconstruction are modeled by embedding formal demographic accounting relationships in a Bayesian hierarchical model. Informative priors are specified for vital rates, migration rates, population counts at baseline, and their respective measurement error variances. We investigate calibration of central posterior marginal probability intervals by simulation and demonstrate the method by reconstructing the female population of Burkina Faso from 1960 to 2005. Supplementary materials for this article are available online and the method is implemented in the R package “popReconstruct. ”
Dynamic Grasp Synthesis of Simple Convex Shapes

The general grasp planning problem has been studied in the academic community for decades. Developing efficient and versatile grasping systems has great implications in automating tasks that require dexterous and compliant manipulation. Traditional approaches tend to favor optimality over efficiency, producing grasping systems that are slow. I propose a new strategy that combines successful probabilistic approaches, object model abstraction schemes and force-closure constraint approximations into a single unifying algorithm. It is my hypothesis that through combining successful techniques already published in the literature, a more efficient strategy can be developed. The proposed algorithm will be tested in the dynamic simulation environment GraspIt! and then tested on the physical Barrett Hand and WAM arm
Highly flexible design of multi-rate multi-length quasi-cyclic LDPC codes

The design of Low-Density Parity-Check (LDPC) codes with fixed code rate and block length for a fixed channel condition has been well investigated and very close-to-capacity performance can be achieved by careful optimization of a code's degree distributions. The growing variety of services supported by mobile communication systems, however, constitutes the need for highly flexible Forward Error Correction (FEC) schemes. Pursuing this need, we present a design method for the construction of quasi-cyclic (QC) LDPC codes supporting arbitrarily many block lengths and code rates using only a single common mother code. Different block lengths are achieved by an optimized expansion of the mother code's lifting matrix. For the support of multiple code rates, a joint optimization of shortening and puncturing distributions as well as an optimized check matrix construction based on the progressive edge-growth algorithm is employed.
Conditional Random Fields Model for Web Content Extraction

The web contains an abundance of semi-structured information, but not all the information is useful for users, it always contains so many noises such as the advertisement, navigation information, and so on. Identifying which parts of the web page contain target content and classify them into right category (such as title, author, time, content and so on) become a significant problem that must be solved. To this problem, one kind of approach is based on writing rules or scripts manually to extract the content. This kind of method requires considerable time and effort, besides, hand-built rules are brittle: they often fail in some cases and break down when the structure of the web page changes. The other kind of approach is based on DOM tree analysis of the web page, this kind of method depends on the structure of the DOM tree heavily. Furthermore, both of the above two kinds of methods are difficult to assign a suitable category label to the extracted content in their implementation. In this paper, to better solve the drawbacks of the traditional methods, using Conditional Random Fields sequence labeling model, we correctly extract the real content of the web page and assign a suitable category label to each part of the content simultaneously. The accuracy of the extraction and labeling can achieve above 96%.
STRUCTURE-PRESERVING DOCUMENT IMAGE

Maintaining a document in image form is often preferable in order to avoid the high cost of manual conversion or the introduction of large numbers of errors by automatic OCR and/or graphics interpretation. The large volume of data in the image can be greatly reduced by using compression techniques. Text-intensive document images typically have a great deal of redundancy in the bitmap representations of symbols, and we make use of that redundancy for compression by clustering components, representing each cluster by a template and encoding the error. Our method is novel in modeling the error associated with each cluster and in preserving structure, an important component for readability and processing. Document image compression for storage or transmission is an important research topic, in part because of the relatively large amounts of data that documents contain. Text-intensive document images typically have signiicant amounts of symbol-level redundancy as characters of the same size and font repeat in the text. Our research centers around exploiting the redundancy to provide a compressed representation which preserves document-level features necessary for later processing and analysis 5]. Many image compression schemes are widely available. For binary document images, CCITT Group 3 and 4 are among the industry standards 8]. These standards are lossless compression schemes which were proposed for fax and modem use. They use variations of run-length encoding for optimized binary image transmission. For grayscale and color images, the JPEG standard 6] is a widely accepted lossy compression scheme. This method works well with textured images but does not exploit the structural redundancies within a document. In general, methods of image (a) (b) Figure 1: a) Symbolic image, b) Error image coding based on image models (e.g., 2]) do not exploit the redundancies that exist in documents and may render a document unreadable. Since many document processing algorithms degrade at resolutions below 300 dpi, simply reducing the resolution to save space is not necessarily an option. An important consideration is the preservation of structure so that symbols remain recognizable. In this paper we use a structural approach to compress textual images. The general approach, suggested in part by Ascher and Nagy 1] and later enhanced by Witten 7], rst clusters text-like components and represents each cluster by a single template (presumably of the underlying symbol); the residual error is then encoded (Figure 1). Our contribution is the use of a probabilistic model of the errors. In …
Number Counts at 3 μm < λ < 10 μm from the Spitzer Space Telescope

Infrared source counts at wavelengths 3 μm < λ < 10 μm cover more than 10 mag in source brightness, reach 4 orders of magnitude in surface density, and reach an integrated surface density of 105 sources deg-2. At m < 14 mag, most of the sources are Galactic stars, in agreement with models. After removal of Galactic stars, galaxy counts are consistent with what few measurements exist at nearby wavelengths. At 3.6 and 4.5 μm, the galaxy counts follow the expectations of a Euclidean world model down to ∼16 mag and drop below the Euclidean curve for fainter magnitudes. Counts at these wavelengths begin to show decreasing completeness around 19.5 mag. At 5.8 and 8 μm, the counts relative to a Euclidean world model show a large excess at bright magnitudes. This is probably because local galaxies emit strongly in the aromatic dust ("polycyclic aromatic hydrocarbon") features. The counts at 3.6 μm resolve less than 50% of the cosmic infrared background at that wavelength.
Nol12 is a multifunctional endonuclease at the nexus of RNA and DNA metabolism

Endo‐ and exonucleases are major contributors to RNA metabolism through their diverse roles in maturation and turnover of different species of RNA as well as transcription. Recent data suggests RNA nucleases also affect genome stability programs and act along DNA repair pathways. Here, we describe Nol12 as a multifunctional RNA/DNA endonuclease found in different subcellular compartments - the nucleoplasm, where it co-localizes with the RNA/DNA helicase Dhx9 and paraspeckles, nucleoli as well as GW/P-bodies. We show that Nol12 is required for a key step in ribosomal RNA processing, separating large and small subunit precursors at site 2, rerouting ribosome biogenesis via an alternative pathway in its absence to ensure ribosome production. Furthermore, loss of Nol12 results in increased oxidized DNA levels followed by a rapid p53-independent ATR-Chk1-mediated apoptotic response, suggesting a role for Nol12 in the prevention or resolution of oxidative DNA damage. Identification of a complex Nol12 interactome, which includes NONO, Dhx9 and DNA-PK, further supports its diverse functions in RNA metabolism and DNA maintenance, establishing Nol12 as a multifunctional endonuclease.
Differences in Middle School Science Achievement by School District Size.

This study examined differences in Texas middle school student achievement in science by school district enrollment size. Quantitative research utilized analysis of variance to determine whether significant differences existed between student achievement on the 2010 Texas Assessment of Knowledge and Skills 8 th grade science results and four school district enrollment size groups. A significant difference was found between means of small district science scores and medium, large, and mega district science scores.
Unexplored Hypotheses on Potency-Magnitude Relations of eWOM Messages with Intensified Comparative Expressions

Electronic word-of-mouth (eWOM) is an important information source that influences consumer product evaluations. The author previously developed a computational model that predicts the potency-magnitude relations of eWOM messages involving subjective rank expressions, which refer to linguistic representations related to the attitude-levels of the benefits of product attributes. This paper extends the typology of message expressions and mathematically investigates potency-magnitude relations with a focus on intensified comparative expressions that involve the “degree” of the differences among two or more objects. The investigations were performed first under the premise of a strict assumption called an interval assumption, and the results were verified under the premise of a conservative assumption called a surjection assumption. These assumptions were introduced to determine the cognitive relationship between attitude-levels and their difference-levels. The investigations include the development of a Q-magnitude Relation Map (Q-Map) that illustrates how the relations change based on the values of two evaluation parameters: evaluation target size and evaluation scale size. Based on the observations of the Q-Maps, five unexplored hypotheses on the potency-magnitude relations were developed with respect to intensified comparative expressions. Unexplored Hypotheses on Potency-Magnitude Relations of eWOM Messages with Intensified Comparative Expressions
The conformal Penrose limit and the resolution of the pp-curvature singularities

We consider the exact solutions of the supergravity theories in various dimensions in which the spacetime has the form Md × SD−d where Md is an Einstein space admitting a conformal Killing vector and SD−d is a sphere of an appropriate dimension. We show that if the cosmological constant of Md is negative and the conformal Killing vector is spacelike, then such solutions will have a conformal Penrose limit: M(0)d × SD−d where M(0)d is a generalized d-dimensional AdS plane wave. We study the properties of the limiting solutions and find that M(0)d has 1/4 supersymmetry as well as a Virasoro symmetry. We also describe how the pp-curvature singularity of M(0)d is resolved in the particular case of the D6-branes of D = 10 type IIA supergravity theory. This distinguished case provides an interesting generalization of the plane waves in D = 11 supergravity theory and suggests a duality between the SU(2) gauged d = 8 supergravity theory of Salam and Sezgin on M(0)8 and the d = 7 ungauged supergravity theory on its pp-wave boundary.
Efficient testing and estimation in two Lehmann alternatives to symmetry-at-zero models

We consider two variations on a Lehmann alternatives to symmetry-at-zero semiparametric model, with a real parameter ! quantifying skewness and a symmetric-at-0 distribution as a nuisance function. We show that a test of symmetry based on the signed logrank statistic (Hall [2011]) is asymptotically e! cient in these models, derive its properties under local alternatives and present e! ciency results relative to other signed-rank tests. We develop e! cient estimation of the primary parameter in each model, using modelspecific estimates of the nuisance function, and provide a method for choosing between the two models. All inference methods proposed are based solely on the signed ranks of the absolute values of the observations, the invariantly su! cient statistic. A simulation study is summarized and an example presented. Extensions to regression modeling are envisaged.
Plasminogen Activator Inhibitor-1 Controls Vascular Integrity by Regulating VE-Cadherin Trafficking

Background Plasminogen activator inhibitor-1 (PAI-1), a serine protease inhibitor, is expressed and secreted by endothelial cells. Patients with PAI-1 deficiency show a mild to moderate bleeding diathesis, which has been exclusively ascribed to the function of PAI-1 in down-regulating fibrinolysis. We tested the hypothesis that PAI-1 function plays a direct role in controlling vascular integrity and permeability by keeping endothelial cell-cell junctions intact. Methodology/Principal Findings We utilized PAI-039, a specific small molecule inhibitor of PAI-1, to investigate the role of PAI-1 in protecting endothelial integrity. In vivo inhibition of PAI-1 resulted in vascular leakage from intersegmental vessels and in the hindbrain of zebrafish embryos. In addition PAI-1 inhibition in human umbilical vein endothelial cell (HUVEC) monolayers leads to a marked decrease of transendothelial resistance and disrupted endothelial junctions. The total level of the endothelial junction regulator VE-cadherin was reduced, whereas surface VE-cadherin expression was unaltered. Moreover, PAI-1 inhibition reduced the shedding of VE-cadherin. Finally, we detected an accumulation of VE-cadherin at the Golgi apparatus. Conclusions/Significance Our findings indicate that PAI-1 function is important for the maintenance of endothelial monolayer and vascular integrity by controlling VE-cadherin trafficking to and from the plasma membrane. Our data further suggest that therapies using PAI-1 antagonists like PAI-039 ought to be used with caution to avoid disruption of the vessel wall.
“This Condition isn't Going to get any Better so I can't see why we're Prolonging it”: Risks and Benefits of using Empirical Research to Inform Normative Decisions Concerning End-of-Life Care

Abstract Progressive neurological diseases are often complicated by declining cognitive function (leading to impaired decision-making capacity) in addition to the physical impairments which have significant emotional and social consequences. Options for managing the later stages vary from invasive medical procedures, palliative care, and (in some jurisdictions) assisted suicide or euthanasia. Decisions about the right approach to take may be influenced by facts about the likely effectiveness of treatment. However, moral questions, such as the right balance between preserving life and maximizing quality of life, are an inherent part of the care-planning process. This paper takes nutritional support as an example of one area of decision-making that needs to be addressed during care-planning for people with progressive neurological disease. It describes research into the way in which the values of practitioners, members of the public and people with lived experience of progressive neurological disease may influence their decision-making about the right approach to maintaining nutritional intake during end -of-life care; and discusses some of the challenges of incorporating such findings into normative frameworks.