Miracle-dz/UniFAR-FTUs huggingface dataset:
Type System Based Rational Lazy IDA

Meta-reasoning can improve numerous search algorithms, but necessitates collection of statistics to be used as probability distributions, and involves restrictive meta-reasoning assumptions. The recently suggested scheme of type systems in search algorithms is used in this paper for collecting these statistics. The statistics are then used to better estimate the unknown quantity of expected regret of computing a heuristic in Rational Lazy IDA* (RLIDA*), and also facilitate a second improvement due to relaxing one of the unrealistic meta-reasoning assumptions in RLIDA*.
An Algorithm for Mining Multidimensional Association Rules Using Boolean Matrix

In this paper an algorithm is proposed for mining multidimensional association rules. A Boolean Matrix based approach has been employed to discover frequent itemsets, the items forming a rule come from different dimensions. It is an algorithm for mining multidimensional association rules from relational databases. The algorithm adopts Boolean relational calculus to discover frequent predicate sets. When using this algorithm first time, it scans the database once and will generate the association rules. A priori property is used in algorithm to prune the item sets. It is not necessary to scan the database again, it uses Boolean logical operations to generate the association rules.
Denitrification by the Fungus Fusarium oxysporum Involves NADH-Nitrate Reductase

Fusarium oxysporum JCM11502 expresses a denitrifying (nitrate (NO3 −)-respiring) mechanism and can thrive under oxygen (O2) limitation. The fungus reduces NO3 − to nitrite at the initial step of denitrification. In this study, we cloned the gene coding NADH-NO3 − reductase (NADH-Nar) (niaD) from F. oxysporum JCM11502. The niaD gene complemented the defective NO3 − assimilation by mutant strain M10, indicating that the fungus reduced NO3 − through NADH-Nar activity and assimilated it like other fungi. We found that the transcription of niaD and the production of NADH-Nar activity were enhanced under O2-limited denitrifying conditions relative to aerobic conditions. Strain M10 produced less NADH-Nar activity and less denitrified product than the wild-type strain. Introducing niaD into the mutant also restored these defects, indicating that niaD is involved in denitrification. These results indicate that the fungus denitrified NO3 − through NADH-Nar activity in addition to the ubiquinol-Nar mechanism.
An Approach to Characterizing the Complicated Sequential Metabolism of Salidroside in Rats

Metabolic study of bioactive compounds that undergo a dynamic and sequential process of metabolism is still a great challenge. Salidroside, one of the most active ingredients of Rhodiola crenulata, can be metabolized in different sites before being absorbed into the systemic blood stream. This study proposed an approach for describing the sequential biotransformation process of salidroside based on comparative analysis. In vitro incubation, in situ closed-loop and in vivo blood sampling were used to determine the relative contribution of each site to the total metabolism of salidroside. The results showed that salidroside was stable in digestive juice, and it was metabolized primarily by the liver and the intestinal flora and to a lesser extent by the gut wall. The sequential metabolism method described in this study could be a general approach to characterizing the metabolic routes in the digestive system for natural products.
Identification and characterization of the core region of protein phosphatase-1

PP1, PP2A and PP2B all belong to PPP family of serine/threonine protein phosphatases. Their primary structures are highly conserved, particularly in the catalytic domain. In order to obtain correlative information about this conserved region, we constructed N-, C-deletion and N/C double-deletion mutants. We found that the N- and Csingle-deletion mutants exhibited higher enzymatic activities, while specific activity of N/C double-deletion mutant PP1 (9-306) did not notably change. The results of kinetics analysis showed that kcat and kcat/Km increased about 16-fold in the single-deletion mutants; while the two parameters of the double-deletion were lower than the single-deletions. We further explored stability of all mutants in existing denaturant guanidine hydrochloride (GdnHCl). It was noticeable that stability of PP1-(9-306) in all mutants was the highest. We speculated that PP1-(9-306) maybe retains a compact spherical structure, thus accordingly affected molecular catalysis. On the other hand the structures of single-deletion mutants were relatively relaxed, which were able to bind substrate easily, so activities of single-deletion mutants were higher than that of double-deletion mutant. We therefore deduced that PP1-(9-306) may be close to core region of PP1 molecule. In order to further solidify this idea, we used fluorescence spectra method to explore changes of space conformation. We found that emission peaks of all single-deletions were blue shifted in different degree in the absence of denaturant, while emission peak of N/C double-deletion mutant did not change obviously compared with that of the wild-type PP1. Conformation change of N/C double-deletion mutant was significantly less than those of single-deletion mutants in different GdnHCl concentration.
Comparative study of performance of distance measures in fuzzy C means clustering for CIELUV color images

Segmentation is one of the initial but vital processes in most of the image analysis and interpretation applications. In the image segmentation, the test image is divided into number of sub images called segments or clusters. All the pixels in the same segment having the similar characteristics such as texture, color or intensity. In this paper, the performance of squared Euclidean, city block and cosine distance measures in fuzzy c-means clustering is compared for the segmentation of satellite images. This experiment is performed in CIELUV color space which has many advantages as compared to RGB color space. The proposed method is tested with number of satellite images.
Deficits and Debt in the Short and Long Run

This paper begins by examining the persistence of movements in the U.S. Government%u2019s budget posture. Deficits display considerable persistence, and debt levels (relative to GDP) even more so. Further, the degree of persistence depends on what gives rise to budget deficits in the first place. Deficits resulting from shocks to defense spending exhibit the greatest persistence and those from shocks to nondefense spending the least; deficits resulting from shocks to revenues fall in the middle. The paper next reviews recent evidence on the impact of changes in government debt levels (again, relative to GDP) on interest rates. The recent literature, focusing on expected future debt levels and expected real interest rates, indicates impacts that are large in the context of actual movements in debt levels: for example, an increase of 94 basis points due to the rise in the debt-to-GDP ratio during 1981-93, and a decline of 65 basis point due to the decline in the debt-to-GDP ratio during 1993-2001. The paper next asks why deficits would exhibit the observed negative correlation with key elements of investment. One answer, following the analysis presented earlier, is that deficits are persistent and therefore lead to changes in expected future debt levels, which in turn affect real interest rates. A different reason, however, revolves around the need for markets to absorb the increased issuance of Government securities in a setting of costly portfolio adjustment. The paper concludes with some reflections on %u201Cthe Perverse Corollary of Stein%u2019s Law%u201D: that is, the view that in the presence of large government deficits nothing need be done because something will be done.
Metric Attitude

We present Metric Attitude, an Eclipse Rich Client Platform application, for the reverse engineering of object-oriented software systems. The approach graphically represents a suite of object-oriented design metrics and "traditional" code-size metrics. To assess the validity of Metric Attitude and its underlying approach, we have conducted a case study on the framework Eclipse 3.5.
Characterization of triple-phase computed tomography in dogs with pancreatic insulinoma

Little information is available regarding triple-phase computed tomography (CT) of canine pancreatic insulinoma. A few case reports with small numbers of cases have indicated that hyper-attenuation in the arterial phase was a common finding on multi-phasic CT in dogs with insulinoma. Our purpose was to clarify the characteristic findings of dogs with insulinoma on triple-phase CT. Nine dogs with insulinoma that underwent triple-phase CT were included in the present study. Attenuation patterns in the arterial phase indicated hypo-attenuation in 4 cases and hyper-attenuation in 2 cases. In the remaining 3 cases, 1 case showed hypo-attenuation and 1 case showed hyper-attenuation in the pancreatic phase, and 1 case presented hyper-attenuation in the later phase. Altogether, 5 cases showed hypo and 4 cases showed hyper-attenuation in at least one phase. The enhancement pattern was homogenous in 7 cases and heterogeneous in 2 cases. Tumor margins were well-defined in 5 cases and ill-defined in 4 cases. Capsule formation was present in 5 cases and absent in 4 cases. In conclusion, it is important to note that hypo-attenuation was as common as hyper-attenuation in dogs with insulinoma in triple-phase CT in at least one phase. Additionally, mass lesions were most conspicuous not only in the arterial phase but in the pancreatic and later phases in some cases. Therefore, it is important to perform triple-phase CT and notice about variable findings for the detection of canine pancreatic insulinoma.
Evaluation of a static architectural conformance checking method in a line of computer games

We present an evaluation of a simple method to find architectural problems in a product line of computer games. The method uses dependencies (direct, indirect, or no) to automatically classify types in the implementation to high-level components in the product line architecture. We use a commercially available tool to analyse dependencies in the source code. The automatic classification of types is compared to a manual classification by the developer, and all mismatches are reported. To evaluate the method, we inspect the source code and look for a pre-defined set of architectural problems in all types. We compare the set of types that contained problems to the set of types where the manual and automatic classification disagreed to determine precision and recall. We also investigate what changes are needed to correct the found mismatches by either designing and implementing changes in the source code or refining the automatic classification. Our evaluation shows that the simple method is effective at detecting architectural problems in a product line of four games. The method is lightweight, customisable and easy to implement early in the development cycle.
Rural Economic Performance And Federal Credit Programs

Several theories of externalities and asymmetric information suggest a positive role for government programs to assist credit markets, though potential distortions by special interests carry attendant dangers. We examine the empirical association between funding by several federal government programs and subsequent economic performance, measured six ways, for nonmetropolitan U.S. counties during the 1990s. Significant differences are found across programs, performance measures, and market types. Observed tradeoffs suggest a need to compare policy objectives with acceptable costs in many cases. Overall, the results are consistent with theoretical predictions and with some standard policy objectives.
Valence‐Driven Connectivity Encoding for 3D Meshes

In this paper, we propose a valence‐driven, single‐resolution encoding technique for lossless compression of triangle mesh connectivity. Building upon a valence‐based approach pioneered by Touma and Gotsman22 , we design a new valence‐driven conquest for arbitrary meshes that always guarantees smaller compression rates than the original method. Furthermore, we provide a novel theoretical entropy study of our technique, hinting the optimality of the valence‐driven approach. Finally, we demonstrate the practical efficiency of this approach (in agreement with the theoretical prediction) on a series of test meshes, resulting in the lowest compression ratios published so far, for both irregular and regular meshes, small or large.
A New Model of Information Content for Measuring the Semantic Similarity between Concepts

The information content (IC) of concepts is a fundamental dimension in semantic similarity calculation. The IC of a concept is able to provide an evaluation of its degree of semantic generality and concreteness, which is great important semantic evidence modeled in the ontology. A proper quantification of IC requires an accurate evaluation of the structural differences among different concepts. This paper analyses several existing IC models and some structural factors in the ontological structure. After that, this paper proposes a criterion for evaluating IC models and a novel model employing three important factors to compute the concept's IC. This model is evaluated on two different test datasets, and the experiments show that our IC model distinguishes concepts with different topology in the taxonomy more effectively than other IC models, and the corresponding similarities are better correlated with human judgments than most other works.
Probabilistic Matrix Factorization Based on Similarity Propagation and Trust Propagation for Recommendation

Traditional collaborative filtering approaches are often confronted with two major problems: data sparsity and cold-start. Fortunately, along with the rise of social media, social network is producing a large and rich set of social data (such as labels, trust, etc.), which provides a new way to solve the problems of collaborative filtering, namely, we can make use of social data to enhance the recommendation accuracy. However, traditional recommendation algorithms may only consider either the influence of similarity relationships or trust relationships to the user model, but fail to take full advantage of the implications of social data. In this paper, we propose a novel recommendation algorithm called STPMF based on neighborhood model and matrix factorization model, where complementary roles of similarity relationships and trust relationships to the user model by means of a weight w are considered simultaneously. Furthermore, we propagate similarity relationships and trust relationships one step or two steps to alleviate the data sparsity and cold-start problems. We have conducted experiments on two real world data sets from Last.fm and Delicious. Compared with existing recommendation algorithms, our method can effectively alleviate the problems of collaborative filtering, and enhance the recommendation accuracy.
Landscape of RNA polyadenylation in E. coli

Abstract Polyadenylation is thought to be involved in the degradation and quality control of bacterial RNAs but relatively few examples have been investigated. We used a combination of 5΄-tagRACE and RNA-seq to analyze the total RNA content from a wild-type strain and from a poly(A)polymerase deleted mutant. A total of 178 transcripts were either up- or down-regulated in the mutant when compared to the wild-type strain. Poly(A)polymerase up-regulates the expression of all genes related to the FliA regulon and several previously unknown transcripts, including numerous transporters. Notable down-regulation of genes in the expression of antigen 43 and components of the type 1 fimbriae was detected. The major consequence of the absence of poly(A)polymerase was the accumulation of numerous sRNAs, antisense transcripts, REP sequences and RNA fragments resulting from the processing of entire transcripts. A new algorithm to analyze the position and composition of post-transcriptional modifications based on the sequence of unencoded 3΄-ends, was developed to identify polyadenylated molecules. Overall our results shed new light on the broad spectrum of action of polyadenylation on gene expression and demonstrate the importance of poly(A) dependent degradation to remove structured RNA fragments.
Bupropion SR in adults with ADHD: a short-term, placebo-controlled trial

Increased attention has been given to the alternatives to stimulants in the treatment of attention deficit hyperactivity disorder (ADHD) in both adults and children. This short-term, double-blind trial was designed to evaluate the extended-release form of bupropion in adult subjects meeting DSM-IV and the Utah Diagnostic Criteria for ADHD. Outcome measures were the Clinical Global Impressions-Improvement (CGI-I) and the Wender-Reimherr Adult Attention Deficit Disorder Scale (WRAADDS), which assesses adult ADHD symptoms. Outcome (defined by the CGI-I, average WRAADDS scores, or a 50% improvement on the WRAADDS) favored bupropion SR over placebo, but achieved statistical significance on only one, post hoc measure. Other measures showed trends for improvement with bupropion. Given the small size of this study, these findings deserve further exploration.
MIMO and massive MIMO — Analysis for a local area scenario

The performance of centralized and distributed deployments of massive MIMO in an office building is analyzed both with and without cooperation. It is shown that using twice as many base station antennas as data streams provides most of the massive MIMO benefits. A simple transmission scheme achieves user fairness and operates close to a capacity upper bound. An example scheduling algorithm improves efficiency only for less than twice the number of base station antennas as data streams. The tradeoff between performance and cost for backhauling is evaluated by comparing cooperation of distributed base stations with a single central deployment.
Model-based clustering of non-Poisson , non-homogeneous , point process events , with application to neuroscience

Neurons communicate by propagating electric pulses called “spikes”. Experimental neuroscientists analyze the point process of spike times (“spike train”) to study how neural activity relates to behavior. In experiments with behaving subjects, each electrode in the brain receives the combined signal of multiple neurons. Before we can analyze such data, we need to process the signal to identify the spikes of individual neurons, a procedure known as “spike-sorting”. The traditional practice is to perform spike-sorting by clustering the characteristic spike voltage waveforms and then to estimate neuron properties, e.g. firing rates as functions of behavioral covariates, from the sorted data. This approach ignores the information available for spike-sorting in the neurons’ firing rates and in dependencies between neurons. As a consequence, the traditional procedure yields inconsistent estimates of firing rates and correlations between neurons (Ventura, 2009; Ventura and Gerkin, 2011). The goal of this thesis is to design a spike-sorting method which incorporates in a principled way all variables that contain information about spike identities. This new method would allow us to obtain consistent estimates of neuron parameters such as firing rates and correlations. This requires defining a model for spike identities and designing an algorithm to estimate the model parameters from data.
A near real-time evolutive strategy for adaptive Color Quantization of image sequences

Color quantization of still images can be easily stated as a clustering problem. Color quantization of sequences of images becomes a non-stationary Clustering problem. In this paper we propose a very simple and effective evolutive strategy to perform adaptively the computation of the color representatives for each image in the sequence. Salient features of the evolutive strategy proposed here are: individuals correspond to individual cluster centres, to approach real-time response we impose one-generation adaptation for each image, mutation operators are guided by the actual covariance matrices of the clusters. Experimental results on a sequence of indoor images are presented.
From implicit to explicit knowledge: a tool for preserving and sharing mental links in science

In this paper we propose MentaLink, a tool for preserving and sharing mental links in science. MentaLink is intended as a public knowledge base of links between scientific publications. Contributors can collaboratively define and edit links between entire articles or specific text passages. MentaLink builds on the idea of typed links, allowing authors to explicitly specify how the publications relate to each other, e.g., whether they share the problem statement, whether one publication is built on another or whether they contain contradictory results.
(5, k) regular LDPC codes using novel code-construction

This paper is a continuation of the work in [15] wherein a novel code-construction method was proposed for constructing (3, k) regular LDPC codes. In this paper, the (3, k) construction technique is generalized to construct (5, k) regular code. The basic design of the proposed code-construction utilizes deterministic base matrices for information part and parity part in three stages of code-construction to achieve no rank-deficiency of H, no girth of 4-cycles, non-singular parity part (Hpar) and low encoding complexity. A typical performance of proposed (5, k) regular LDPC codes has been shown.
Improvement in Neural Respiratory Drive Estimation From Diaphragm Electromyographic Signals Using Fixed Sample Entropy

Diaphragm electromyography is a valuable technique for the recording of electrical activity of the diaphragm. The analysis of diaphragm electromyographic (EMGdi) signal amplitude is an alternative approach for the quantification of the neural respiratory drive (NRD). The EMGdi signal is, however, corrupted by electrocardiographic (ECG) activity, and this presence of cardiac activity can make the EMGdi interpretation more difficult. Traditionally, the EMGdi amplitude has been estimated using the average rectified value (ARV) and the root mean square (RMS). In this study, surface EMGdi signals were analyzed using the fixed sample entropy (fSampEn) algorithm, and compared to the traditional ARV and RMS methods. The fSampEn is calculated using a tolerance value fixed and independent of the standard deviation of the analysis window. Thus, this method quantifies the amplitude of the complex components of stochastic signals (such as EMGdi), and being less affected by changes in amplitude due to less complex components (such as ECG). The proposed method was tested in synthetic and recorded EMGdi signals. fSampEn was less sensitive to the effect of cardiac activity on EMGdi signals with different levels of NRD than ARV and RMS amplitude parameters. The mean and standard deviation of the Pearson's correlation values between inspiratory mouth pressure (an indirect measure of the respiratory muscle activity) and fSampEn, ARV, and RMS parameters, estimated in the recorded EMGdi signal at tidal volume (without inspiratory load), were 0.38 ± 0.12, 0.27 ± 0.11, and 0.11 ± 0.13, respectively. Whereas at 33 cmH2O (maximum inspiratory load) were 0.83 ± 0.02, 0.76 ± 0.07, and 0.61 ± 0.19, respectively. Our findings suggest that the proposed method may improve the evaluation of NRD.
A retrospective on the adoption of the ACES technology at Framestore

This talk will give an overview of Framestore's VFX pipeline, focusing on the colour transformation steps; it will then cover the migration to using the Academy Color encoding System (ACES) over the last few years. Showing how the changing state of ACES furthered Framestore adoption, by adding features to better match the requirements of VFX studios in general. We will also mention a few other areas Framestore uses ACES technologies, and some of the areas where the latest ACES version 1.0 would benefit from additional work, along with some suggestions and workarounds.