Miracle-dz/UniFAR-FTUs huggingface dataset:
Computer-assisted quantitative evaluation of bisphosphonate treatment for Paget's disease of bone using the bone scan index

The purpose of the present study was to analyze the effect of treatment of Paget's disease of bone (PDB) with bone scintigraphy using a computer-assisted diagnosis system (BONENAVI) that quantitatively evaluates bone metabolism. Seven patients with PDB (three male, four female; average age, 60 years; age range, 33–80 years) underwent bone scintigraphy and measurement of serum alkaline phosphatase (ALP), bone-specific ALP (BAP), serum cross-linked N-telopeptide (NTx) of type I collagen, urinary NTx, and deoxypyridinoline (DPD) before and after bisphosphonate treatment. Bone scan index (BSI), artificial neural network (ANN) value, and hotspot number (HSn) were calculated using BONENAVI software. Mean follow-up period was 22 months (range, 11–35 months). Among three BONENAVI parameters (ANN, BSI, and HSn), only BSI was significantly lower after bisphosphonate treatment as compared with before. All bone metabolic markers excluding DPD were significantly lower following bisphosphonate treatment than before. Bone formation markers (ALP and BAP) were significantly lower than bone resorption markers (U-NTx and S-NTx). The correlation of BONENAVI parameters with four bone metabolic markers was analyzed before and after bisphosphonate treatment. Before treatment, the majority of the four markers did not correlate with the BONENAVI parameters. In contrast, post-treatment ALP, BAP, and U-NTx were significantly correlated with BSI and HSn. To the best of our knowledge, this is the first study to evaluate the treatment of PDB by bone scintigraphy using a computer-assisted diagnosis system that quantitatively evaluates bone metabolism. The findings demonstrated that, using BONENAVI software, bone scintigraphy is able to quantitatively and spatially evaluate the bisphosphonate treatment effect, particularly in patients with polyostotic PDB.
A Conceptual Model for Documentation of Clinical Information in the EHR

At a national level in Denmark the development of a Conceptual Model for Communication in Electronic Health Records (EHR) has moved towards a two-folded structure, i.e. a conceptual model for documentation of clinical information, the Clinical Process, and a Reference Information Model. The coupled structure derived in the final phase of the development of the Conceptual Model for Communication in EHR by the end of year 2001. This was inspired by the in-put and collaboration of several parties in the Danish healthcare sector throughout the period of development from 1999 to the current version 1.01 of the national standard was launched by The National Board of Health in January 2002. The modelling of the Clinical Process meets the need for a more clinical understanding of how the use of information technology, i.e. EHR, can support the work processes of shared-care and continuity of care in hospital settings. The Clinical Process as a model for documentation in EHR facilitates the capturing of clinical information where it emerges in the clinical work processes. The model retains in a logical way the clinical relevant relations between different information elements that comply with the concept of problem-oriented documentation. A comparison between European Pre-standard CEN/ENV 13606 and the Danish Conceptual Model reveals different approaches with regard to the focus of modelling the EHR information.
Building a Federated Relational Database System: An Approach Using a Knowledge-Based System

Due to the emerging interest in integrating different application environments, there have been many recent proposals for federated systems. In this paper, a federated system that permits the integration of heterogeneous relational databases using a terminological knowledge representation system is presented. In particular, two of the system's components: the translator and the integrator are explained in depth. The translator permits one to obtain a terminology from a relational schema, either semiautomatically, by expressing database properties, or manually, by using a set of predefined operations. In turn, the integrator generates a federated terminology by integrating several terminologies using the semantics expressed as correspondences between the data elements of different terminologies. Unlike many other approaches, the use of a terminological system permits us to obtain a semantically richer federated terminology and, at the same time, define a wider and more consistent integration process.
Identification of Oxygen-Responsive Transcripts in the Silage Inoculant Lactobacillus buchneri CD034 by RNA Sequencing

The Lactobacillus buchneri CD034 strain, known to improve the ensiling process of green fodder and the quality of the silage itself was transcriptionally analyzed by sequencing of transcriptomes isolated under anaerobic vs. aerobic conditions. L. buchneri CD034 was first cultivated under anaerobic conditions and then shifted to aerobic conditions by aeration with 21% oxygen. Cultivations already showed that oxygen was consumed by L. buchneri CD034 after aeration of the culture while growth of L. buchneri CD034 was still observed. RNA sequencing data revealed that irrespective of the oxygen status of the culture, the most abundantly transcribed genes are required for basic cell functions such as protein biosynthesis, energy metabolism and lactic acid fermentation. Under aerobic conditions, 283 genes were found to be transcriptionally up-regulated while 198 genes were found to be down-regulated (p-value < 0.01). Up-regulated genes i. a. play a role in oxygen consumption via oxidation of pyruvate or lactate (pox, lctO). Additionally, genes encoding proteins required for decomposition of reactive oxygen species (ROS) such as glutathione reductase or NADH peroxidase were also found to be up-regulated. Genes related to pH homeostasis and redox potential balance were found to be down-regulated under aerobic conditions. Overall, genes required for lactic acid fermentation were hardly affected by the growth conditions applied. Genes identified to be differentially transcribed depending on the aeration status of the culture are suggested to specify the favorable performance of the strain in silage formation.
Waseda Bioinstrumentation system WB-2 - the new inertial measurement unit for the new motion caption system -

Personal robots and robot technology (RT)- based assistive devices are expected to play a major role in Japan's elderly-dominated society, both for joint activities with their human partners and for participation in community life. These new devices should be capable of smooth and natural adaptation and interaction with their human partners and the environment, should be able to communicate naturally with humans, and should never have a negative effect on their human partners, neither physical nor emotional. To achieve this smooth and natural integration between humans and robots, we need first to investigate and clarify how these interactions are carried out. Therefore, we developed the portable bioinstrumentation system WB-2 (Waseda bioinstrumentation system No.2), which can measure the movements of the head, the arms, and the hands (position, velocity, and acceleration), as well as several physiological parameters (electrical activity of the heart respiration, perspiration, pulse wave, and so on), to objectively measure and understand the physical and physiological effects of the interaction between robots and humans. In this paper we present our development of the Inertial Measurement Unit, which is at the heart of our new motion-capture system that replaces the system used in the Waseda bioinstrumentation system No.1 refined (WB-1R). Some preliminary results of experiments with the unit are also presented and analyzed.
Structural Mechanism for Substrate Inhibition of the Adenosine 5′-Phosphosulfate Kinase Domain of Human 3′-Phosphoadenosine 5′-Phosphosulfate Synthetase 1 and Its Ramifications for Enzyme Regulation*

In mammals, the universal sulfuryl group donor molecule 3′-phosphoadenosine 5′-phosphosulfate (PAPS) is synthesized in two steps by a bifunctional enzyme called PAPS synthetase. The APS kinase domain of PAPS synthetase catalyzes the second step in which APS, the product of the ATP-sulfurylase domain, is phosphorylated on its 3′-hydroxyl group to yield PAPS. The substrate APS acts as a strong uncompetitive inhibitor of the APS kinase reaction. We generated truncated and point mutants of the APS kinase domain that are active but devoid of substrate inhibition. Structural analysis of these mutant enzymes reveals the intrasubunit rearrangements that occur upon substrate binding. We also observe intersubunit rearrangements in this dimeric enzyme that result in asymmetry between the two monomers. Our work elucidates the structural elements required for the ability of the substrate APS to inhibit the reaction at micromolar concentrations. Because the ATP-sulfurylase domain of PAPS synthetase influences these elements in the APS kinase domain, we propose that this could be a communication mechanism between the two domains of the bifunctional enzyme.
Stochastic Context-Aware Saliency Detection

Most image retargeting algorithms rely heavily on valid saliency map detection to proceed. But the inefficiency of high quality saliency map detection severely restricts applications of these image retargeting methods. In this paper, we describe a stochastic algorithm for efficient context-aware saliency map detection. Our method is a multiple level saliency map detection algorithm which integrates multiple level coarse saliency maps into result saliency map and selectively updates unreliable regions of saliency map to refine detection results. With the virtue of randomized search, our method just needs very little extra memory beyond the input image and result map, and does not need build auxiliary data structures to accelerate saliency map detection. We implemented our algorithm on GPU, the performance of the proposed algorithm was demonstrated on a variety of images and video sequences, and was compared with the state of the art in image processing.
Optimized GDPWM based on Spontaneous Evolutionary GA for reducing switching losses on inverter

This paper presents analytical techniques for reducing switching losses of voltage source inverter (VSI) using Generalized Discontinuous PWM (GDPWM). The switching losses of inverter is influenced by the angle on the modulation of GDPWM. This problem will be optimized using a new optimization method. This method is called as Spontaneous Evolutionary GA (SEGA). The inverter switching losses is formulated as objective function to optimize the angle. At this optimization process, angle values will be determined to minimize the inverter switching losses. Thermal module of Power Simulator (PSIM) is used to verify the optimized angle of GDPWM. The simulation was performed using a three-phase voltage source inverter (VSI) and an inductive load. Simulation results confirm the method could minimize the losses of inverter.
UMON: flexible and fine grained traffic monitoring in open vSwitch

We study how to provide fine-grained, flexible traffic monitoring in the Open vSwitch (OVS). We argue that the existing OVS monitoring tools are neither flexible nor sufficient for supporting many monitoring applications. We propose UMON, a mechanism that decouples monitoring from forwarding, and offers flexible and fine-grained traffic stats. We describe a prototype implementation of UMON that integrates well with the OVS architecture. Finally, we evaluate the performance using the prototype, and illustrate UMON's efficiency with the example use cases such as detecting port scans.
Vision-driven walking pattern generation for humanoid reactive walking

We present a novel approach to introduce visual information in the walking pattern generator for humanoid robots in a more direct way than the current existing methods. We make use of a model predictive control (MPC) visual servoing strategy, which is combined to the walking motion generator. We define two schemes based on that principle: a position-based and an image-based scheme, with a Quadratic Program (QP) formulation in both cases. Finally, we present some simulation results validating our approach.
Verifying Distributed Controllers with Local Invariants

Controllers restrict systems to behave only in good manners. Different from controlling monolithic systems where controllers can be automatically synthesized from specifications, controlling distributed systems often has to use distributed controllers that are manually programmed. To ensure their correctness, manually programmed controllers themselves need to be formally verified. This task can be challenging due to the complexity caused by the autonomy and asynchrony of distributed controllers. The limited scalability of existing model checkers also exacerbates the problem. In this paper we explore the modeling and verification of distributed controllers using Alloy. Besides resorting to the Small Scopes Hypothesis of the Alloy methodology, we also leverage local invariant based modular verification techniques for better scalability. A local invariant characterizes a logical relationship between a local sub-system and its neighbors and abstracts away the concrete interactions. These concrete interactions would otherwise explode the system state space during verification. The approach is first illustrated with the well-understood Two-Phase Commit protocol, and then is applied to the verification of several dynamic software update protocols, which gives an initial evidence of its effectiveness.
Understanding how the affective quality of motion is perceived in the user interface

More than ever, entertainment is being serviced via digital media. In this context, the user interface design must consider emotion, since it is a key aspect of entertainment. To approach user emotion, the affective quality of the user interface needs to be designed appropriately. In comparison to static elements such as color and texture, motion has received little attention, despite its increasing use for digital content. To gain positive emotion from an entertainment experience through interactive digital media, motion needs to be designed for affective quality as well. In this study, we investigated how the affective quality of motion is perceived in user interfaces. To do this, the Effort system, which is part of Laban's theory, and describes the affective quality of movement, was examined in relation to three properties of general motion: path curvature, duration, and acceleration. The applicability of the Effort system for the design of motion in user interfaces was also discussed.
Automatic Arabic Document Categorization Based on the Naïve Bayes Algorithm

This paper deals with automatic classification of Arabic web documents. Such a classification is very useful for affording directory search functionality, which has been used by many web portals and search engines to cope with an ever-increasing number of documents on the web. In this paper, Naive Bayes (NB) which is a statistical machine learning algorithm, is used to classify non-vocalized Arabic web documents (after their words have been transformed to the corresponding canonical form, i.e., roots) to one of five pre-defined categories. Cross validation experiments are used to evaluate the NB categorizer. The data set used during these experiments consists of 300 web documents per category. The results of cross validation in the leave-one-out experiment show that, using 2,000 terms/roots, the categorization accuracy varies from one category to another with an average accuracy over all categories of 68.78 %. Furthermore, the best categorization performance by category during cross validation experiments goes up to 92.8%. Further tests carried out on a manually collected evaluation set which consists of 10 documents from each of the 5 categories, show that the overall classification accuracy achieved over all categories is 62%, and that the best result by category reaches 90%.
Clustering Methods without Given Number of Clusters

As we know, kmeans method is a very effective algorithm of clustering. Its most powerful feature is the scalability and simplicity. However, the most disadvantage is that we must know the number of clusters in the first place, which is usually a difficult problem in practice. In this paper, we propose a new approach– peak-searching clustering– to realize clustering without given the number of clusters.
The gender gap in workplace authority in Sweden 1968-2000 – a family affair?

We assess whether the gender gap in authority in Sweden has changed during the period 1968–2000, and investigate to what extent family factors are responsible for this gap. We find that the gap has narrowed modestly during this period, and identify the life-event of parenthood as a major cause of the gap. When men become fathers, they gain authority; when women become mothers, they do not. Our fixed effects panel estimates of the effects of family factors deviate from the cross-sectional estimates, suggesting that unobserved individual heterogeneity – routinely neglected in this line of research – matters.
An improved Spatial index based on the R*Q-tree

In order to solve the problem of the conventional R*Q-tree about inserting the data object into which queue, a new R*Q-tree spatial database indexing technology is proposed based on the analysis of the conventional R*Q-tree, the new R*Q-tree is created by adding the parent node pointers VP and HP, making the data set of R*Q-tree in the partition forms of narrow-band line shape, the overlapping and coverage between the sub-trees of the R*-tree can be greatly reduced, at the same time, the entire area of the spatial data objects is divided into narrow-band. So there exists no repetition between the R*-tree and the sub-regions. The experiment shows that the query efficiency of the improved R*Q-tree is significantly enhanced, and it can achieve the quick index in the massive data set.
Chebyshev FLN-based Nonlinearity Estimation of LMCS

Lumber moisture content (LMC) is a key parameter for regulating and controlling wood drying process. With detailed study, authors found that the precision of LMC is influenced by many nonlinear factors such as noises, intercross-sensitivity existing among multiple environmental factors, and the electric characteristic of ionic groups changing with the ambient temperature fluctuating, etc. A novel functional link network (FLN) based on Chebyshev polynomial is put forward for this purpose to compensate for the nonlinear response characteristics and complex nonlinear dependency of the environmental factors on the sensor characteristics. The hidden layers of conventional neural networks is eliminates by functional expansion. The computational economy to be gained by Chebyshev series increases when the power series is slowly convergent. The simulation studies that the FLN-based algorithm estimated MC errors remain within plusmn0.8 at ultimate stage over a wide range of temperature (24degC~80degC). Therefore, nonlinearity estimation based on FLN is a very effective method for lumber MC measuring
Controlling physical memory fragmentation in mobile systems

Since the adoption of hardware-accelerated features (e.g., hardware codec) improves the performance and quality of mobile devices, it revives the need for contiguous memory allocation. However, physical memory in mobile systems is highly fragmented due to the frequent spawn and exit of processes and the lack of proactive anti-fragmentation scheme. As a result, the memory allocation for large and contiguous I/O buffers suffer from the highly fragmented memory, thereby incurring high CPU usage and power consumption. This paper presents a proactive anti-fragmentation approach that groups pages with the same lifetime, and stores them contiguously in fixed-size contiguous regions. When a process is killed to secure free memory, a set of contiguous regions are freed and subsequent contiguous memory allocations can be easily satisfied without incurring additional overhead. Our prototype implementation on a Nexus 10 tablet with the Android kernel shows that the proposed scheme greatly alleviates fragmentation, thereby reducing the I/O buffer allocation time, associated CPU usage, and energy consumption.
Tax Evasion in Italy

We perform a detailed analysis of the phenomenon of tax evasion in Italy, looking for determinants and policy solutions. We first discuss the characteristics of the tax system, the coercive system and the economic structure; we then investigate empirically the determinants of personal income tax evasion, building to this aim a microeconometric analysis based on the results of the actual detection policy. A few determinants of tax evasion are singled out by the analysis: the inefficiencies of tax administration, the high progressivity of the personal income tax, the characteristics of the plea-bargaining system and the widespread use of tax amnesties. Accordingly, we propose a number of policy actions aimed to remove these factors.
Appendices and Additional Results for “ Inflation-Gap Persistence in the U . S . ” ”

The state and measurement innovation variances are defined as Qt = (B −1 s ) ′Hst(B−1 s ), (2) Rt = (B −1 y ) ′Hyt(B−1 y ), respectively, where Hst and Hyt are diagonal matrices with univariate stochastic volatilities along the main diagonal and Bs and By are triangular matrices with ones along the main diagonal and static covariance parameters below. The univariate stochastic volatilities are geometric random walks; the vectors σs and σy list their innovation variances. The notation x represents the complete history of xt. We use a ‘Metropolis-within-Gibbs’ algorithm to simulate the posterior. The parameters are partitioned into 7 blocks: ∗New York University. Email: tim.cogley@nyu.edu. †Northwestern University, CEPR, and NBER. Email: g-primiceri@northwestern.edu. ‡New York University and Hoover Institution, Stanford University. Email: ts43@nyu.edu. The MCMC algorithm for the univariate AR is a special case of that for the VAR.