dataesr/scientific-paragraphs-categorization huggingface dataset:
2) showing that checking LTL-FO properties is undecidable for databases satisfying a functional dependency (FD). This uses a reduction from the PCP. Next, we note that satisfaction of FDs by the database can be expressed as a CTL-FO property. Using this, we wish to mimick the reduction from the PCP that works for databases with FDs. However, there is a glitch: LTL-FO model checking is decidable for feedback-free specifications and properties even in the presence of FDs. Thus, a direct reduction from the linear-time case is not possible. Instead, we show how feedback freedom can be circumvented collectively by different branches of the tree of runs while being obeyed by each individual branch, and use this to adapt the PCP reduction to the branching-time framework. Similarly to the linear-time case, it can be shown that effective regularity of T S * (Γ) implies decidability of CTL ( * ) -FO properties.
Theorem 19. T S * (Γ) is effectively regular for globally feedback-free artifact systems Γ. The proof requires some technical development, which we sketch in the remainder of the section. The basic idea is to show that there are only finitely many subtrees T Runs D (Γ) of T Runs * (Γ) up to bisimulation. Moreover, each is realized by a database of bounded size, depending only on |x|. Since bisimilar trees have the same branching-time service views, this establishes the theorem. We recall the standard notion of bisimulation. Two infinite trees T , T with labeled edges are bisimilar if there exists a relation ∼ from the nodes of T to those of T such that: (i) root(T ) ∼ root(T ), (ii) if α ∼ α and α σ -→ β then there exists β such that α σ -→ β and β ∼ β , and (iii) if α ∼ α and α σ -→ β then there exists β such that α σ -→ β and β ∼ β.
We now present the main steps in the proof. Let Γ = x, DB , Σ, Π be an artifact system, with |x| = k. As in the global feedback freedom definition, we assume that service pre-and-post conditions are in CQ ¬ form (conjunctions of literals). For a service σ = (π, ψ) we denote by f σ (x, ȳ) the formula π(x) ∧ ψ(x, ȳ). Definition 20. The set T n of n-types of x is defined inductively as follows. T 0 = { true } For n ≥ 0, T n+1 consists of all formulas of the form σ∈Σ0 τ ∈Tσ ∃ȳ(f σ (x, ȳ) ∧ τ (ȳ)) where ∅ = Σ 0 ⊆ Σ and ∅ = T σ ⊆ T n. Let D be a database over DB and ν be a valuation of x. It is easy to check that, for every ν that labels some node in T Runs D (Γ), and each n ≥ 0, there exists a unique strongest 5  τ n ∈ T n such that D, ν |= τ n. We denote the latter by τ n (D, ν). It is clear that τ n+1 (D, ν) → τ n (D, ν) for every n ≥ 0.
Lemma 21. Let Γ be a globally feedback-free artifact system. There exists b > 0, depending only on |x|, such that for every database D, tuple ν labeling a node in T Runs D (Γ) and n ≥ 0, τ n (D, ν) is equivalent to an FO sentence of quantifier rank ≤ b. Using the lemma, we can prove the following. Lemma 22. Let ν 1 , ν 2 be valuations of x labeling nodes in T Runs D (Γ). If τ n (D, ν 1 ) = τ n (D, ν 2 ) for every n ≥ 0 then T Runs ν1 D (Γ) and T Runs ν2 D (Γ) are bisimilar. From Lemma 21 it follows that for every D and reachable ν, there exists N > 0 such that τ n (D, ν) ≡ τ N (D, ν) for every n ≥ N. We denote τ N (D, ν) by τ * (D, ν) and call it the type of ν in D. Thus, τ * (D, ν) is equivalent to {τ n (D, ν) | n ≥ 0}. Observe that, by Lemma 21, there are finitely many tuple types. The set of all tuple types is denoted by T.
Finally, we define database types as follows. Definition 23. The type of a database D is τ (D) = {τ * (D, ν) | D |= Π(ν)}. We have the following. Lemma 24. Let D 1 and D 2 be databases over DB such that τ (D 1 ) = τ (D 2 ). Then T Runs D1 (Γ) and T Runs D2 (Γ) are bisimilar. Note that, since there are finitely many tuple types, there are also finitely many database types. Since a database type can be written as the conjunction of finitely many tuple types, Lemma 21 also applies to database types, and each can be written as an ∃ * FO sentence. Let d be the maximum number of existential quantifiers in these sentences. Thus, there are finitely many equivalence classes of trees of database runs under bisimulation, and each has a representative T Runs D (Γ) for some database D whose domain is of size ≤ d.
5 The impact of data dependencies In this section we consider the impact of data dependencies on the regularity of service views. We consider tuple and equality generating dependencies. We briefly recall (see  [1]  for details) that an equality-generating dependency (EGD) is an FO sentence of the form ∀x(ϕ(x) → y = z), where ϕ is a conjunction of relational atoms and y, z ∈ x. A tuple-generating dependency (TGD) is a sentence of the form ∀x(ϕ(x) → ∃zψ(x, z)), where ϕ and ψ are conjunctions of relational atoms. If z is empty, the dependency is called full; if every atom in ψ(x, z) contains an existentially quantified variable in z, it is called embedded (note that every TGD can be written as a conjunction of full and embedded TGDs). A set of TGDs is acyclic if the following graph is acyclic: the nodes are database relations and there is an edge from P to Q if P occurs in the body of a TGD whose head contains Q.
Inclusion dependencies are instances of TGDs and functional dependencies (FDs) are EGDs. Linear-time service views. We first consider the impact of EGDs. Let Γ = A, Σ, Π be an artifact system, where A = x, DB. For a set ∆ of dependencies, S ∆ lin (Γ) = {S(ρ) | ρ ∈ Runs D (Γ), D |= ∆}. We say that S ∆ lin (Γ) is effectively regular for a class A of artifact systems and D of dependencies, if a Büchi automaton defining S ∆ lin (Γ) can be effectively constructed from each Γ in A and set ∆ of dependencies in D. We can show the following. Theorem 26. S ∆ lin (Γ) is not effectively ω-regular for artifact systems Γ and sets ∆ of EGDs. Moreover, this holds even if ∆ consists of a single FD. Proof. It can be shown that it is undecidable, given an artifact system Γ, a set ∆ of EGDs, and a service σ, whether there exists a run of Γ on a database satisfying ∆ in which service σ is used.
We now consider TGDs. Rather surprisingly, the easy case is that of embedded TGDs. Theorem 27. S ∆ lin (Γ) is effectively ω-regular for artifact systems Γ and sets ∆ of embedded TGDs. Proof. It is enough to show that every symbolic run of Γ has an enactment on a database satisfying ∆. Indeed, this implies that S ∆ lin (Γ) = S lin (Γ), thus establishing effective ωregularity. Let be a symbolic run of Γ. By Theorem 14, has an enactment (D, ρ, θ). Let d be some domain value not occurring in D or the constants of Γ. Observe that an extension D of D satisfying ∆ can be obtained by chasing D with the TGDs in ∆ so that d is used as a witness to every existentially quantified variable in the head of a TGD. Since D is an extension of D, ( D, ρ, θ) is also an enactment of. For full TGDs we have the following.
Theorem 28. There exists an artifact system Γ and set ∆ of full TGDs such that S ∆ lin (Γ) is not ω-regular. Proof. Let the database schema of Γ consist of a binary relation R and ∆ be the full TGD ∀x∀y∀z (R(x, y) ∧ R(y, z) → R(x, z)), guaranteeing that R is transitive. Γ has one attribute variable x and two services init and next. The global precondition is ¬R(0, 0) ∧ x = 0 where 0 is a constant. The pre-condition of init is x = 0 and its post-condition is x = 0. The pre-condition of next is true and its post-condition is R(x, x ) ∧ ¬R(x , x ). Runs of Γ consist of stepping through R using next, starting from 0, using only elements which do not belong to a cycle, until init reinitializes x to 0 and the process is restarted. Since R is finite, S ∆ lin (Γ) consists of all ω-words of the form (next ) n1 • init • (next) n2 • init • • • such that for each word there exists N > 0 for which n i ≤ N for all i ≥ 1.
Let ∆ * by the closure of ∆ under partial unfoldings. Obviously, ∆ * and ∆ are equivalent. Because ∆ is acyclic, ∆ * is finite. The idea of the proof is to define a Büchi automaton B that accepts the runs of F(Γ) that are inconsistent with some TGD in ∆ *. Using ∆ * instead of ∆ facilitates this task by allowing to ignore compositions of TGDs. Let ξ = ∀ȳ(∃zϕ(ȳ, z) → R(ȳ)) in ∆ *. An inconsistency with ξ occurs in a symbolic run = {(x i , H i , i , σ i )} i≥0 if for some j ≥ 0 and ȳ ⊆ xj ∪ xj+1 , ¬R(ȳ) is in H j and there exist z ⊆ ∪ i≥0 xi such that ϕ(ȳ, z) is satisfied by ∪ i≥0 H i. It can be seen, using the construction in the proof of Theorem 14, that a symbolic run is consistent with ∆ * iff it has an enactment on a database satisfying ∆. The Büchi automaton non-deterministically guesses an inconsistency.
Intuitively, ν i (x i ) completely specifies the constraints placed on xi by the first i transitions. Let Φ = {∃x i ν i (x i ) | i ≥ 0}. It can be shown that there exists an enactment of on a database D satisfying ∆ iff D |= Φ ∪ ∆ (this uses the finiteness of D and a pigeonhole argument). As shown in  [11] , because Γ is feedback-free, each formula in Φ can be rewritten as a formula of quantifier rank bounded by |x| 2. Since there are finitely many non-equivalent formulas of bounded quantifier rank  [26] , Φ is equivalent to a single ∃FO formula ϕ. Moreover, because all formulas in ∆ are universally quantified, if has an enactment on a database satisfying ∆, it also has an enactment on such a database whose domain is bounded by the number of variables (say v) in ϕ. Thus Branching-time service views.
Proof. Recall the proof of Theorem 19 and the formulas ∃ * FO defining database types, whose number of existential quantifiers is bounded by some b depending only on Γ. Note that the EGDs and full TGDs in ∆ can be expressed by a sentence in ∀ * FO. Suppose there is a database D of type τ satisfying ∆. Then there exists D 0 ⊆ D, whose domain consists of b witnesses to the existentially quantified variables of τ , that also has type τ and satisfies ∆. Thus, every database type that includes an instance satisfying ∆, also has a representative satisfying ∆ whose domain is bounded by b. It follows that T S * ∆ (Γ) is regular, and a specification can be effectively constructed from Γ and ∆. Remark. Theorem 31 alternatively holds for sets ∆ of EGDs and arbitrary TGDs (full and embedded), as long as the set of TGDs is acyclic.
We also considered the impact of data dependencies (tuple and equality generating dependencies) on regularity of views. We showed that linear-time views are no longer regular in presence of FDs or cyclical full TGDs, but remain regular with acyclic or embedded TGDs. Regularity of branching-time service views is preserved in the presence of EGDs and full TGDs. Our results also have some interesting connections to verification. For instance, the techniques developed to show regularity of linear-time views yield potentially more efficient ways to generate counterexample databases witnessing violation of LTL-FO properties. As a side-effect of results on branching-time service views, we showed that CTL-FO properties are undecidable for artifact systems, but model-checking CTL*-FO becomes decidable under the same restrictions guaranteeing regularity of branching-time views.
Aim: The purpose of this study is to describe the development of an external 3dimensional (3D) scanner as a noninvasive method for imaging chest wall deformities. It allows objective assessment, reconstruction of the area of interest, and evaluation of the severity of the deformity by using external indexes. external 3D scanning system: The OrtenBodyOne scanner (Orten, Lyon, France) uses depth sensors to scan the entire 3D external body surface of a patient. The depth sensors combine structured light with two classic computer vision techniques: depth from focus and depth from stereo. The data acquired are processed and analyzed using the Orten-Clinic software.
External Sternal Depression Angle: "Banana Index" The purpose of this index is to evaluate the angle of the sternal depression. To calculate the index, it is important that the anterior anatomic landmarks (sternal notch, deepest point, and xiphoid process) are correctly placed prior to data acquisition with the 3D scanner. Using the image analyzer, a sagittal cross section is obtained through the sternum at the midline of the trunk, allowing evaluation the total sternal surface (Figure  7 ). The angle between the theoretical anatomical sternal line and the sternal line of the patient is the "banana index. " The larger the angle, the greater the depression. This index can be used to plan strategies for corrective PE surgery and for localizing the best positions to place the Nuss bars.
Ten adult female RSM were transferred from the colony with a fine brush onto each leaf disc. Mites on leaf discs dipped in distilled water (instead of acaricide solutions) served as untreated control. All experiments were conducted with five replicates for each concentration of acaricide. Six such concentrations were tried. Based on percent mortality data lethal concentrations LC 50 and LC 95 were calculated using the statistical package for social sciences (SPSS) version 10. 0 SPSS Inc. , USA, based on probit analysis method  (Finney, 1973). To assess the tolerance/resistance of a given population of RSM, the resistance coefficient (RC) was calculated after  Węgorek et al. (2009)  as follows: RC = LC 95 /recommended field dose. The following values of ratios were considered for assessment of resistance level: RC ≤ 1, lack of resistance; RC 1.
ACKNOWLEDGEMENTS We are thankful to The Head, Department of Zoology [supported by  University Grants Commission (UGC)   Special Assistant Programme  (SAP) and  Department of Science and Technology-Fund for Improvement of Science and Technology (DST-FIST) ] for providing lab and other facilities. We acknowledge the grant provided by  UGC  under  Rajiv Gandhi National Fellowship  to  Ms. Jayashree Saren  for carrying out the study.
A summary is provided to describe loci carrying genes that display expression in blood cells relatively similar to NRAMP1. This set includes genes that exhibit tissue-specific expression profile similar to NRAMP1, as indicated by GTEx datasets  [50]  i. e. , high expression levels in vivo in blood and/or lung, spleen, and which encode functions that contribute to iron (including heme) acquisition, iron storage and lysosomal recycling. A fraction of these exhibit candidate S-Es that may enable coordinated regulation of MF iron genes. Lastly, to evaluate whether NRAMP1 epigenetic regulation is conserved, the expression of the mouse orthologous gene Nramp1 was examined during embryogenesis and organognesis; activation of Nramp1 locus was studied during hematopoiesis, both primitive and definitive, and compared between cells either explanted or cultured in vitro.
E ), and NRAMP1 TSS as well as surrounding genes are indicated; chromosome 2 scale; CTCF ChIP-seq data for CD14 + monocytes (MNs), acute promyelocytic leukemia HL-60 and NB4, erythroleukemia K562, human umbilical vein epithelial cells (HUVEC) and embryonic stem cells (ESC; data from ENCODE consortium  [9, 10] ); CpG islands; DNAse1 footprints: hypersensitive sites (DHS) in CD14 + MNs (ENCODE)  [9, 10] ; UCSC browser genes; RNA Pol II ChIP-seq data for HL-60, NB4, K562, HUVEC and ESC (ENCODE); RefSeq genes; CAGE data  [16, 17]  for 22 blood cell types. Three lines of evidence argue that NRAMP1 ~40 kb locus likely represents an autonomous regulatory domain: (i) transcription data reveal NRAMP1 is the sole gene that shows strictly myelo-monocytic specific expression (Figure  S1B ); (ii) ENCODE data for chromatin interaction analysis by paired-end tag sequencing (ChIA-PET)  [51, 52] , obtained for both K562 megakaryocytic cells and MCF-7 epithelial cells  [53] , indicate similar chromatin loops that suggest insulation of NRAMP1 locus by its flanking CTCF sites (Figure  S1B, C ); and (iii) single nucleotide polymorphisms (SNPs) that were identified at genome-wide significance as potential quantitative trait loci affecting NRAMP1 expression in cis (cis eQTLs) reveal a possible regulatory influence of the areas carrying CTCF sites E and A (Figure  S1D )  [54].
g. , C or D) may be part of loops directed by downstream CTCF sites, which would contribute to insulate NRAMP1 as well. To investigate NRAMP1 CTCF looping pattern ChIA-PET data derived from K562 and MCF-7 cells were examined. The results appeared consistent between both cell types. Hence, site D, which is the most downstream "F" site, was found in loops involving further downstream areas, each comprising a CTCF site in "R" orientation (chr2:219,330,316-479 (K562)/219,330,530-1,339 (MCF7) and 219,512,425-946 (K562); indicated as sites 331 and 513, respectively, Figure  S1B, C ). Regarding the "R" sites A, located within NRAMP1 3 UTR, and E, forming the locus 5 boundary, both are part of loops connecting further upstream areas that carry an "F" site (219,   S1 ). Because similar loops were observed both in K562 and MCF-7 cells, it seems plausible similar domains are also formed in myelo-monocytic cells to insulate NRAMP1 40 kb locus.
Candidate Super-Enhancer Domain The cluster of footprints F12, F13, F5 and F2 covers a region that is highly transcribed in professional phagocytes (Figure  S3 ) and abundantly marked in CD14 + MNs with histone modifications that support transcriptional activity (Figure  2A ). Accordingly, this region matches an S-E domain predicted by profiling K27ac ChIP-seq signals in the interactive database DBsuper  [101]  (Figure  S11 ). Integrating ChIP-seq signals for additional trans-factors (such as Mediator complex, BRD4 and RNA Pol II) and active histone marks (e. g. , K4me2/3) may strengthen such S-E predictions  [102]. The proposition that NRAMP1 upstream area spanning F12-F2 DHSs, perhaps including also F4B (cf. Section 2. 3. 2. 2), forms an S-E in CD14 + MNs is supported by comparing chromatin marking intensity of this domain with a predicted "classic" enhancer (see Section 2.
Altogether data suggest that, within this chr2 205 kb interval, CTCF boundaries delineate functional gene units, supporting that NRAMP1 40 kb locus comprises the regulatory determinants controlling myelo-monocytic expression. Prior genetic analyses indicated that NRAMP1 locus is divided in 5 and 3 haplotypes  [109] [110] [111]  (Figure  5B ). Most of TF interactions revealed so far take place within NRAMP1 5 haplotype (e. g. , PU. 1, C/EBPb, HIFs, IRF1) while several negative interactions involved determinants from the 3 haplotype (e. g. , F10, F3 and the 3 CTCF stretch). NRAMP1 5 and 3 haplotypes may therefore reflect distinct regulatory roles to control myelo-monocytic determinants within NRAMP1 TAD.
Reappraisal of NRAMP1 Tissue-Specificity Using Large Scale Transcriptomic Datasets Multi-organ RNA-seq analyses  [50]  demonstrated NRAMP1 gene expression is tissue-specific (principally found in blood, spleen and lung, ranked by decreasing transcript abundance). These data confirmed prior studies which showed high level expression in professional phagocytes  [74, 112] , and revealed some molecular mechanisms controlling NRAMP1 transcription specificity, using model cell lines for myelo-monocytic differentiation, such as granulocyte-MF progenitors (HL-60),  [12, 76, [113] [114] [115]  and monocyte-like cells (U-937 and THP1)  [104, 105, 116, 117]. Examining NRAMP1 locus decoration with K36me3 in a variety of tissues (121 samples, NIH Roadmap)  [14]  confirms that ORF transcription is restricted to tissues highly enriched in MFs, such as spleen, or in MNs (e.
CP is formed by heterodimers or heterotetramers of S100A8 and S100A9 proteins that in the presence of Ca 2+ act as potent chelators of divalent metals (Zn, Mn and Fe)  [167]. To seek genes that may share expression properties with NRAMP1 the GTEx RNA expression database  [50]  and epigenetic datasets hosted at UCSC  [48]  were interrogated to visualize and compare transcription patterns of these genes; RNA-seq data of hematopoietic cell-types from NIH Roadmap epigenomics projects were also examined  [14, 72]  as well as those of MDMs in baseline conditions (using GM-CSF or M-CSF) and activated with 28 stimulation conditions that depict various states comprised in the current M1 vs. M2 polarization spectrum  [132]. A survey of NRAMP1 specific expression properties indicates that none of the selected genes displays similar characteristics, i.
Acknowledgments: The following networked communities and online facilities are gratefully acknowledged: NCBI, UCSC, ENCODE, RIKEN FANTOM,  NIH Roadmap  and  EU Blueprint  epigenome as well as authors of individual studies that were analyzed in this work, including  Pierre Cauchy ,  Elzo de Wit ,  Brian Lee ,  Joost Martens  and  Michael Rehli  for help with data processing. The author received no specific funding for this work.
Training data The experimental data set contains records of binary tablets made from MCC and lactose. Powder mixtures were roll compacted under constant conditions. Ribbons were milled to produce granules of three different size ranges (315-500; 630-800, and 800-1,000 μm). In continuation of the process, the feed powders (binary mixtures) and their granules from each size range were die compacted using six different die compaction forces. The experiments were done in triplicates. 22 he tablets were characterized through the porosity. Therefore, the porosity is an outcome (Table  1A ). After ejection, the tablet dimensions (diameter and thickness) were measured with a digital micrometer (Mitutoyo, Takatsu-ku, Japan), and tablet mass was weighed with an electronic balance (CP224S). These data were used to calculate the relative density (ρ r ) of each tablet, as follows: ρ ρ r t = 4 2 m hD π ( 1 ) where m is the mass, h is the tablet thickness, D is the tablet diameter, and ρ t is the true density of each binary mixture.
Validation data An additional data set from single-powder tableting experiments was used to validate the CI models. The data set is explained in Perez-Gandarillas et al. 23  The validation set is composed of data generated by varying roll compaction over two sets of tooling (cheek plates and sealed rim rolls) and two roll compaction forces (4 kN/cm and 8 kN/cm). The ribbons were milled under constant settings and granules were compacted under seven different die compaction forces (Table  1B ). Variation in roll compactor tooling and roll compaction/die compaction forces introduces a challenge to trained CI models.
symbolic regression by rgp Genetic programming (GP) is a bioinspired algorithm based on evolution principles to solve complex problems. A complex problem is broken down into smaller, simpler problems with random solutions. These solutions are then evolved through the biologically mimicked process of variation and selection until the end condition is reached or a workable solution is generated. Thus, rgp is an implementation of GP methods in the R environment. 29 Package rgp results are simple representations of the problem without being exposed to a priori information. rgp offers various options for initialization, variation, and selection procedures inherent in GP. GP implements a tree structure representation to show the mathematical equations. The tree structure is composed of two parts: function set (nodes) and a terminal set (leaves).
35, 36 dependent feature selection by fscaret The package fscaret allows semiautomatic feature selection, working as a wrapper for the caret package in R. Fscaret is specialized for in silico feature selection experiments, whereby approximately 120 different packages are used to fit models. 37 Input feature ranking is extracted from trained models by using weighted averages. Sum of squared errors (SSE), mean squared errors (MSEs), and RMSEs are used to evaluate models. fscaret has been successfully implemented in recent studies. 38, 39.