Miracle-dz/UniFAR-FTUs huggingface dataset:
Join queries translation from SQL to XPath

SQL (Structured Query Language) was one of the standarized query language for requesting information from a database. Over the past few years organizations are using SQL for storing and managing the organization specific information. At the same time there is an emerging trend towards XML (Extensible Markup Language), and it has become a standard for information exchange over the internet. Users/Developers are supposed to use two different kinds of languages for data reception and manipulation. This problem is overcomed by converting the user's SQL queries into XML. In this paper, we propose a framework to convert SQL join (Left, Right, and Full) queries into XPath expressions. As a result user's can access XML database through SQL queries only. We also present algorithms for translating SQL join queries to XPath expressions.
B-Flow Twinkling Sign in Preoperative Evaluation of Cervical Lymph Nodes in Patients with Papillary Thyroid Carcinoma

Papillary thyroid cancer (PTC) is the most common histologic type of differentiated thyroid cancer. The first site of metastasis is the cervical lymph nodes (LNs). The ultrasonography (US) is the best diagnostic method for the detection of cervical metastatic LNs. We use a new technique, B-flow imaging (BFI), recently used for evaluation of thyroid nodules, to estimate the presence of BFI twinkling signs (BFI-TS), within metastatic LNs in patients with PTC. Two hundred and fifty-two patients with known PTC were examined for preoperative evaluation with conventional US and BFI. Only 83 with at least one metastatic LN were included. All patients included underwent surgery; the final diagnosis was based on the results of histology. The following LN characteristics were evaluated: shape, abnormal echogenicity, absent hilum, calcifications, cystic appearance, peripheral vascularization, and BFI-TS. A total of 604 LNs were analyzed. Of these, 298 were metastatic, according to histopathology. The BFI-TS showed high values of specificity (99.7%) and sensitivity (80.9%). The combination of each conventional US sign with the BF-TS increases the specificity. Our findings suggest that BFI can be helpful in the selection of suspicious neck LNs that should be examined at cytologic examination for accurate preoperative staging and individual therapy selection.
A Variable-Resolution Probabilistic Three-Dimensional Model for Change Detection

Given a set of high-resolution images of a scene, it is often desirable to predict the scene's appearance from viewpoints not present in the original data for purposes of change detection. When significant 3-D relief is present, a model of the scene geometry is necessary for accurate prediction to determine surface visibility relationships. In the absence of an a priori high-resolution model (such as those provided by LIDAR), scene geometry can be estimated from the imagery itself. These estimates, however, cannot, in general, be exact due to uncertainties and ambiguities present in image data. For this reason, probabilistic scene models and reconstruction algorithms are ideal due to their inherent ability to predict scene appearance while taking into account such uncertainties and ambiguities. Unfortunately, existing data structures used for probabilistic reconstruction do not scale well to large and complex scenes, primarily due to their dependence on large 3-D voxel arrays. The work presented in this paper generalizes previous probabilistic 3-D models in such a way that multiple orders of magnitude savings in storage are possible, making high-resolution change detection of large-scale scenes from high-resolution aerial and satellite imagery possible. Specifically, the inherent dependence on a discrete array of uniformly sized voxels is removed through the derivation of a probabilistic model which represents uncertain geometry as a density field, allowing implementations to efficiently sample the volume in a nonuniform fashion.
Admission, Discharge, or Change in B-Type Natriuretic Peptide and Long-Term Outcomes: Data From Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure (OPTIMIZE-HF) Linked to Medicare Claims

Background— B-type natriuretic peptide (BNP) has been associated with short- and long-term postdischarge prognosis among hospitalized patients with heart failure. It is unknown if admission, discharge, or change from admission to discharge BNP measure is the most important predictor of long-term outcomes. Methods and Results— We linked patients ≥65 years of age from hospitals in Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF) to Medicare claims. Among patients with recorded admission and discharge BNP, we compared Cox models predicting 1-year mortality and/or rehospitalization, including clinical variables and clinical variables plus BNP. We calculated the net reclassification improvement (NRI) and integrated discrimination improvement (IDI) for the best-fit model for each outcome versus the model with clinical variables alone. Among 7039 patients in 220 hospitals, median (25th, 75th) admission and discharge BNP were 832 pg/mL (451, 1660) and 534 pg/mL (281, 1111). Observed 1-year mortality and 1-year mortality or rehospitalization rates were 35.2% and 79.4%. The discharge BNP model had the best performance and was the most important characteristic for predicting 1-year mortality (hazard ratio for log transformation, 1.34; 95% confidence interval, 1.28 to 1.40) and 1-year death or rehospitalization (hazard ratio, 1.15; 95% confidence interval, 1.12 to 1.18). Compared with a clinical variables only model, the discharge BNP model improved risk reclassification and discrimination in predicting each outcome (1-year mortality: NRI, 5.5%, P<0.0001; IDI, 0.023, P<0.0001; 1-year mortality or rehospitalization: NRI, 4.2%, P<0.0001; IDI, 0.010, P<0.0001). Conclusions— Discharge BNP best predicts 1-year mortality and/or rehospitalization among older patients hospitalized with heart failure. Discharge BNP plus clinical variables modestly improves risk classification and model discrimination for long-term outcomes.
Distance Estimation System based on ZigBee

Many systems exist (TOA, AOA, RSSI) that can be used with diverse technologies (ultrasounds, infrared, Bluetooth, 802,11.) for indoor location. In this article we choose to apply TOA on a ZigBee network, to be able to add useful functionalities for other applications in an existing network and, in addition, achieve minimum consumption and low cost. The results that we find are promising, because we obtain a precision within a meter in 90% of the cases.
Exploiting logical forms

The Delilah parser and generator for Dutch delivers three related levels of logical form: Stored Logical Form, Normal Logical Form and Flat Logical Form. SLF is produced by graph unification of attribute-value matrices as the value of a semantic feature. It is an underspecified level of semantic representation, as it does not spell out the exact scope of semantic operators like quantifiers, negation and modalities. NLF and FLF are postderivationally induced from SLF. Both representations specify all semantic dependencies, but in different ways. SLF is exploited for a purely semantic reduction of lexical ambiguity. FLF holds all information necessary for easy semantic inference. 1 Logical form and grammar Logical form we take to be that mode of linguistic analysis at which lexical concepts, inferential semantics and information structure interact. The required analysis is formal, in the sense that it should account for the intersubjective and— thus—systematic aspects of sentential and lexical meaning. In particular, logical form is a level of grammatical representation at which semantic consequences can be computed—a view already expressed by Higginbotham (1985). Thus, logical form is one of the ultimate targets of linguistic analysis and the representation of what makes natural language a unique module of human cognition. Typically, logical form emanates from deep processing; there are no shallow ways to semantic precision. The claim that logical form is formal by necessity, does not imply that it is bound to comply with first-order predicate logic. Predicate logic does not entertain a privileged relation to semantic interpretation: the set of meanings of a natural language is neither a subset nor a superset of the well-formed and interpretable propositions of predicate logic or their complement. It may be a helpful tool in describing certain aspects of the relations between concepts and operators in natural language; in our view, however, it is neither the target nor the anchor of natural language semantics. Logical form must be casted as a representation for which some adequate notion of semantic consequence (entailment) can be defined. Overviewing modern grammar, it makes sense to state that the relation between logical form and syntactic structure defines the arena. That is not a trivial observation: though linguistics ranks among the elder sciences in the world, it took millennia before the proper balance between form and interpretation was questioned from a grammatical perspective. In recent times, Bertrand Russell (1949) has argued that logical form is not homomorphic to syntactic structure. Generative grammar split on the question with which aspects of meaning grammar could afford to deal (Seuren 1998, ch. 7). In the same period, Montague (1973) defined logical form by compositional interpretation, but correlated it to a pseudo-
Drug and metabolite concentrations in tissues in relationship to tissue adverse findings: a review

Introduction: Drug blood (or plasma) levels measured during safety preclinical investigations do not always correlate with toxicological findings. Concentrations in target tissues or, even better, at target receptors would probably be more relevant. In addition, toxicity may be caused by drug metabolites which, in turn, can be tissue specific. Tissue concentrations and tissue metabolism may be crucial for interpreting tissue toxicity. Areas covered: This paper, starting from the authors' direct experience, focuses on distribution of the parent compound and metabolites in target toxicity tissues and presents a review of several examples where organ or tissue concentrations have been either useful or not relevant for interpreting safety findings. Regulatory aspects and technological progresses are also mentioned. Expert opinion: The authors advocate directing more attention and efforts toward investigating tissue distribution: this approach might reduce late stage attrition. When unexpected tissue toxicity is found, measuring drug concentrations in the target tissue and characterising and measuring tissue metabolites could bring relevant information for interpreting the adverse finding. Evidence of slow accumulation of a long lasting metabolite in a tissue should be considered as an alert: this evidence can be obtained during short-term toxicity studies.
From cluster properties to concentrations and from concentrations to cluster properties

A large fraction of atmospheric aerosol particles are formed from condensable vapors in the air. This particle formation process has been observed to correlate in many locations with the sulfuric acid concentration, but the very first steps of cluster formation have remained beyond the reach of experimental investigation until recently. Charged clusters can now be detected and characterized starting from the smallest sizes and even neutral clusters consisting of only a few molecules can be detected, although their composition cannot be fully characterized. However, measuring the concentrations of different cluster types does not tell the full story of how the clusters were formed, and detailed simulations are needed in order to get a full understanding of the cluster formation pathways. Cluster formation is described by a set of nonlinear differential equations that cannot be solved analytically in any realistic situation. The best way to understand the complex behavior of cluster populations is by cluster kinetics simulations. The focus of this Thesis is on developing tools for simulating cluster formation, and using the simulation results to improve the detailed understanding of atmospheric aerosol particle formation. As sulfuric acid has been identified as the main driving force of cluster formation in many locations, it is also the main compound in the simulations of this Thesis. It cannot explain the observed atmospheric particle formation rates alone, and other possible participating species considered in this Thesis are ammonia, dimethylamine and water. In the first two papers of the Thesis, theoretical values are used for the collision and evaporation rates, and simulated cluster concentrations and formation rates are compared to experimental observations. The simulation results agree well with experimental findings from two very different studies. The third and fourth paper asses existing methods for interpreting cluster measurements and point out details that should be taken into account: the effect of dipole moments on chemical ionization of neutral molecules and clusters, and the conditions for the widely used nucleation theorem to be valid. The last paper introduces a new method for extracting cluster evaporation rates from measured cluster distributions.
Prevalence of bronchoconstriction induced by eucapnic voluntary hyperpnoea in recreationally active individuals

Abstract Objective: Exercise-induced bronchoconstriction (EIB) is more prevalent in elite athletes than in the general population. Many of these athletes provide a positive eucapnic voluntary hyperpnoea (EVH) challenge without previous diagnosis of EIB. It is unknown whether this is specific to elite athletes or whether the same risk applies to recreationally active individuals. The purpose of this study was to investigate the prevalence of a positive EVH challenge in a population of recreationally active individuals. Methods: 136 recreationally active individuals (Age: 21.9 ± 3.7 years; Height: 175 ± 9 cm; Weight: 70.9 ± 10.0 kg) without previous history of asthma or EIB, volunteered to take part in the study. All participants completed an EVH challenge, which was deemed positive if FEV1 fell ≥10% from baseline at two consecutive time points, and was reversible following inhalation of a short acting β2-agonist. Results: 18 of 136 (13.2%) participants had a positive EVH challenge. Of the 18 individuals, the fall in FEV1 from baseline ranged from −12% to −50%. At baseline, percentage predicted FEV1 (97.5 ± 12.5% versus 104.9 ± 10%; p < 0.01), FEV1/FVC ratio (79.5 ± 6.9% versus 87.8 ± 5.5%; p < 0.01), FEF25-75 (3.73 ± 1.00 versus 4.73 ± 1.00 l/s; p < 0.01) and predicted PEF (89.4 ± 8.8% versus 97.5 ± 13.6%; p < 0.05) values for EVH positive participants were significantly lower than EVH negative participants respectively. Conclusions: Overall, 13.2% of recreationally active individuals with no previous history of asthma presented with a positive EVH challenge. Individuals who are recreationally active may benefit from an objective bronchial provocation challenge, given that self-reported symptoms alone only provide a supportive role towards a valid EIB diagnosis.
An approach to detection ontology changes

Ontologies change and evolve both on the level of schema and individuals in order to meet requirements of changing world. Changes involve adding, deleting and modifying elements in the ontology both on structural (schema related) and content (individuals related) levels. The changes can lead to incorrect conclusions and can cause malfunction of systems, which use ontology data. In this paper we describe a proposal of the method for automated detection of currentness of presented data, including meta-data, which are represented by an ontology. Method comes out from a detection of changes between different versions of the ontology. Besides identifying modifications in the ontology, the purpose of the method lies also in identifying equivalent elements, thanks to which we are able to track information sources over time. We describe possibilities of automated identification of changes between ontologies using heuristic methods and their realization as a software tool called OntoDiff for comparing ontologies.
The Writing Segment of an Intensive Program for Students of English as a Second Language.

The ultimate goal of a writing program for academically oriented ESL students is to teach the written form of English required for success in United States colleges and universities. Foreign students must learn the same skills required of native speakers, such as the writing of reports, research papers, and essay exams. Indeed, many students with a solid background in English and high English proficiency (TOEFL 1 500 or more) on campuses where there is no intensive English program learn these skills in freshman composition classes along with native English speakers. Students who know little or no English when they arrive, however, have special needs which are met by special programming. In intensive English programs, students study English for a minimum of 20 hours per week, with each class day divided among the language skill areas, typically listening and speaking, reading, writing, structure and possibly language laboratory. 2 Depending on entering proficiency and learning speed a student may require three months to a year of English study before he is ready to begin academic work. Our program is divided into three distinct levels to accommodate the entering English proficiencies of our students. Level One students are virtually monolingual in their native language (TOEFL range 200-375) although they may have studied a year or two of English in their home countries. Level Two students (TOEFL 375-425) are at the intermediate
Intelligent malware detection system

Malicious programs spy on users’ behavior and compromise their privacy. Unfortunately, existing techniques for detecting malware and analyzing unknown code samples are insufficient and have significant shortcomings. We observe that malicious information access and processing behavior is the fundamental trait of numerous malware categories breaching users’ privacy (including key loggers, password thieves, network sniffers, stealth backdoors, spyware and root kits), which separates these malicious applications from benign software. Commercial anti-virus software is unable to provide protection against newly launched (“zero-day”) malware. In this dissertation work, we propose a novel malware detection technique which is based on the analysis of byte-level file content. The proposed dissertation work will demonstrate the implementation of system for detection of various types of malware.
Determining optimal dilation factor of non-dyadic wavelet transform

Wavelet analysis is widely and effectively used in data processing and analysis. Due to fast and simple algorithm dyadic wavelet transforms are mostly used. However non-dyadic wavelet transforms can provide more precise detection of singularities. In this paper we present a method for determining an optimal value of dilation factor for non-dyadic transforms. Also we provide two examples in order to illustrate proposed approach.
Intrusion Detection System Using K-SVMeans Clustering Algorithm 1

In recent years, as the usage of internet increases, new types of attack on network information keep increasing. Intrusion Detection System (IDS) is an important tool to identify various attacks to secure the networks. Traditional clustering algorithms work on “flat” data, making the assumption that the data instances are homogeneous in nature. Many real world data, however, is heterogeneous in nature. To handle the heterogeneity of the data, in this paper, we propose IDS using K-SVMeans clustering algorithm and other classification techniques. Here we use KDD-Cup99 dataset as simulation dataset for our experiment. The experimental results show that the proposed model reduces the time complexity, improves overall detection accuracy and minimizes the false alarm rate considerably.
Diacylglycerol Kinase-ε: Properties and Biological Roles

In mammals there are at least 10 isoforms of diacylglycerol kinases (DGK). All catalyze the phosphorylation of diacylglycerol (DAG) to phosphatidic acid (PA). Among DGK isoforms, DGKε has several unique features. It is the only DGK isoform with specificity for a particular species of DAG, i.e., 1-stearoyl-2-arachidonoyl glycerol. The smallest of all known DGK isoforms, DGKε, is also the only DGK devoid of a regulatory domain. DGKε is the only DGK isoform that has a hydrophobic segment that is predicted to form a transmembrane helix. As the only membrane-bound, constitutively active DGK isoform with exquisite specificity for particular molecular species of DAG, the functional overlap between DGKε and other DGKs is predicted to be minimal. DGKε exhibits specificity for DAG containing the same acyl chains as those found in the lipid intermediates of the phosphatidylinositol-cycle. It has also been shown that DGKε affects the acyl chain composition of phosphatidylinositol in whole cells. It is thus likely that DGKε is responsible for catalyzing one step in the phosphatidylinositol-cycle. Steps of this cycle take place in both the plasma membrane and the endoplasmic reticulum membrane. DGKε is likely present in both of these membranes. DGKε is the only DGK isoform that is associated with a human disease. Indeed, recessive loss-of-function mutations in DGKε cause atypical hemolytic-uremic syndrome (aHUS). This condition is characterized by thrombosis in the small vessels of the kidney. It causes acute renal insufficiency in infancy and most patients develop end-stage renal failure before adulthood. Disease pathophysiology is poorly understood and there is no therapy. There are also data suggesting that DGKε may play a role in epilepsy and Huntington disease. Thus, DGKε has many unique molecular and biochemical properties when compared to all other DGK isoforms. DGKε homologs also contain a number of conserved sequence features that are distinctive characteristics of either the rodents or specific groups of primate homologs. How cells, tissues and organisms harness DGKε's catalytic prowess remains unclear. The discovery of DGKε's role in causing aHUS will hopefully boost efforts to unravel the mechanisms by which DGKε dysfunction causes disease.
Connective tissue adaptations in the fingers of performance sport climbers

Abstract This study investigates the changes of the connective tissue in the fingers of performance sport climbers resulting after a minimum of 15 years of climbing. Evaluation was performed by ultrasonography on the palmar side of the fingers (Dig) II–V to measure the thickness of the A2 and A4 annular pulleys, the flexor digitorum superficialis (FDS) and profundus (FDP) tendons and the palmar plates (PP's) of the proximal interphalangeal (PIP) as well as distal interphalangeal (DIP) joint in sagittal and axial direction. Totally, 31 experienced male sport climbers (mean age 37y, 30–48y grade French scale median 8b, range 7b+ to 9a+) participated in the study. The control-group consisted of 20 male non-climbers (age 37y, 30–51y). The A2 and A4 pulleys in climbers were all significantly thicker (A2 Dig III 62%, Dig IV 69%; A4 Dig III 69%, Dig IV 76%) as compared to non-climbers pulleys. All PP's of the DIP joints were also significantly thicker, particularly at Dig III and IV (76 and 67%), whereas the PP's at PIP joints were only scarce significant for three joints. Differences of the diameter of the flexor tendons were less distinct (1–21%) being significant only over the middle phalanx. High load to the fingers of rock climbers after a minimum of 15 years of climbing years induced considerable connective tissue adaptions in the fingers, most distinct at the flexor tendon pulleys and joint capsule (PP) of the DIP joints and well detectable by ultrasound.