Miracle-dz/UniFAR-FTUs huggingface dataset:
NodeTrix-CommunityHierarchy: Techniques for Finding Hierarchical Communities for Visual Analytics of Small-world Networks

While there are several visualizations of the small world networks (SWN), how does one find an appropriate set of visualizations and data analytic processes in a data science workflow? Hierarchical communities in SWN aid in managing and understanding the complex network better. To enable a visual analytics workflow to probe and uncover hierarchical communities, we propose to use both the network data and metadata (e.g. node and link attributes). Hence, we propose to use the network topology and node-similarity graph using metadata, for knowledge discovery. For the construction of a four-level hierarchy, we detect communities on both the network and the similarity graph, by using specific community detection at specific hierarchical level. We enable the flexibility of finding non-overlapping or overlapping communities, as leaf nodes, by using spectral clustering. We propose NodeTrix-CommunityHierarchy (NTCH), a set of visual analytic techniques for hierarchy construction, visual exploration and quantitative analysis of community detection results. We extend NodeTrix-Multiplex framework [1], which is for visual analytics of multilayer SWN, to probe hierarchical communities. We propose novel visualizations of overlapping and non-overlapping communities, which are integrated into the framework. We show preliminary results of our case-study of using NTCH on co-authorship networks.
An Efficient Phone N-Gram Forward-Backward Computation Using Dense Matrix Multiplication

The forward-backward algorithm is commonly used to train neural network acoustic models when optimizing a sequence objective like MMI and sMBR. Recent work on lattice-free MMI training of neural network acoustic models shows that the forward-backward algorithm can be computed efficiently in the probability domain as a series of sparse matrix multiplications using GPUs. In this paper, we present a more efficient way of computing forward-backward using a dense matrix multiplication approach. We do this by exploiting the block-diagonal structure of the n-gram state transition matrix; instead of multiplying large sparse matrices, the proposed method involves a series of smaller dense matrix multiplications, which can be computed in parallel. Efficient implementation can be easily achieved by leveraging on the optimized matrix multiplication routines provided by standard libraries, such as NumPy and TensorFlow. Runtime benchmarks show that the dense multiplication method is consistently faster than the sparse multiplication method (on both CPUs and GPUs), when applied to a 4gram phone language model. This is still the case even when the sparse multiplication method uses a more compact finite state model representation by excluding unseen n-grams.
A signature technique for similarity-based queries

Jagadish et al. (see Proc. ACM SIGACT-SIGMOD-SIGART PODS, p.36-45, 1995) developed a general framework for posing queries based on similarity. The framework enables a formal definition of the notion of similarity for an application domain of choice, and then its use in queries to perform similarity-based search. We adapt this framework to the specialized domain of real-valued sequences. (Although some of the ideas we present are applicable to other types of data as well). In particular we focus on whole-match queries. By whole-match query we mean the case where the user has to specify the whole sequence. Similarity-based search can be computationally very expensive. The computation cost depends heavily on the length of sequences being compared. To make such similarity testing feasible on large data sets, we propose the use of a signature based technique. In a nutshell, our approach is to "shrink" the data sequences into signatures, and search the signatures instead of the real sequences, with further comparison being required only when a possible match is indicated. Being shorter, signatures can usually be compared much faster than the original sequences. In addition, signatures are usually easier to index. For such a signature-based technique to be effective one has to assure that (1) the signature comparison is fast, and (2) the signature comparison gives few false alarms, and no false dismissals. We obtain measures of goodness for our technique. The technique is illustrated with a couple of very different examples.
Functional Imaging and Language: Evidence from Positron Emission Tomography

Positron emission tomography (PET) provides an unprecedented opportunity to study the organization of cognitive functions in the working brain of normal individuals. A number of PET experiments, based on well-established paradigms derived from cognitive psychology, have investigated several aspects of language processing. These studies show that word processing is carried out by a distributed network of cortical areas with functional specificity. Results of this research Sometimes confirm sometimes clearly contradict classic axioms of language organization. This article illustrates some of the methodological issues in PET research, then provides an overview of the most relevant studies using PET. Integrated with other functional imaging methodologies and with behavioral data from cognitive psychology and lesion studies, PET will certainly continue to represent a precious tool to enhance our knowledge of the functional organization of language.
Blunt trauma of the aging eye: injury mechanisms and increasing lens stiffness.

OBJECTIVE To investigate possible injury mechanisms in the eyes of elderly individuals and the effects of lens stiffness on model outputs indicative of injury as a function of age. METHODS Three separate frontal impact scenarios, a foam particle (30 m/s), steering wheel (15 m/s), and air bag (67 m/s), were simulated with a validated finite-element model to determine the effects of changing lens stiffness on the eye when subjected to blunt trauma. The lens stiffness of the model was increased with increasing age using stiffness values determined from the literature for 3 age groups. RESULTS The computational eye model demonstrated increasing peak stress in the posterior portion of the ciliary body and decreasing peak stress in the posterior portion of the zonules with increasing lens stiffness for the 2 most severe impact types, the air bag and steering wheel. Peak deformation of the lens decreased with increasing lens stiffness. CONCLUSIONS On the basis of the computational modeling analysis, the risk of eye injury increases with age; as a result, the eyes of elderly patients may be more susceptible to ciliary body-related eye injuries in traumatic-impact situations. Clinical Relevance These data support the contention that trauma-induced damage to the lens, ciliary body, and zonules may be related to increased stiffness of the lens. The data indicate that all people, especially elderly individuals, should use safety systems while driving an automobile and sit as far from the air bag as is comfortable. Those in sports or work environments requiring protective lenses should wear them. Designers of air bags and automobile companies should continue to work to reduce the potential that the air bag will contact the eye.
A Compressed 3D-Torus architecture for scalable router

With the explosion increasing data in Internet, high performance scalable router has become a hot spot research area both in academe and industry recently. The underlying topology is a very important fold for scalable router. In this paper, we propose a new underlying topology of the scalable router, and name it Compressed 3D-Torus (C3D-Torus). It's more like the 3D-Torus, which is a famous architecture and has been widely studied and used in high performance computer and scalable router before. With theory analysis and simulation, we find it has better performance than 3D-Torus in latency and scalability. Furthermore, we provide an internal routing algorithm which can effectively use multiple links existing simultaneously between neighbor routing nodes in C3D-Torus. We name it Multiple Link Dimension Order Routing (MLDOR) and design it's steps in this paper.
Omeprazole Stability and viscosity of a fl avored omeprazole oral suspension for pediatric use

JANE E. BURNETT, B.S., is Senior Research Specialist, Department of Surgery, University of Missouri Hospital and Clinics (UMHC), Columbia. ETHAN R. BALKIN, B.A., is Graduate Research Assistant, Area of Pathobiology, Harry S. Truman Memorial Veterans’ Hospital, Columbia; at the time of the study he was Senior Research Laboratory Technician, Department of Surgery, UMHC. Address correspondence to Ms. Burnett at the Department of Surgery, University of Missouri Hospital and Clinics, NW301 Medical Sciences Building DC096.00, Columbia, MO 65212 (burnettj@health. missouri.edu). Santarus, Inc., provided an unrestricted grant for this study, which included the authors’ salaries. The authors acknowledge Jeffrey O. Phillips, Pharm.D. , who served as a consultant during this study, and Pamela S. Cooper, Ph.D., who prepared the manuscript.
Multiple Identifications in Multi-Armed Bandits

We study the problem of identifying the top $m$ arms in a multi-armed bandit game. Our proposed solution relies on a new algorithm based on successive rejects of the seemingly bad arms, and successive accepts of the good ones. This algorithmic contribution allows to tackle other multiple identifications settings that were previously out of reach. In particular we show that this idea of successive accepts and rejects applies to the multi-bandit best arm identification problem.
On Friction and Wear Behavior of WC-12Co Microwave Clad

In the present work, the friction and wear behavior of microwave-clad WC-12Co cermet was examined using a pin-on-disk tribometer as per ASTM G99. Microwave clads were tested against an EN-31 countersurface in unlubricated conditions. The WC-12Co clads were developed using an industrial microwave applicator at 2.45 GHz and 1.4 kW. The influence of varying normal load on the tribological characteristics of the microwave-induced clads have been investigated. Responses of the WC-12Co microwave clads and AISI 304 stainless steel substrate were monitored and the resulting wear was subsequently analyzed in terms of wear rate, pressure–velocity–time (p-v-t) characteristics, and friction coefficient. The worn surfaces of the WC-12Co microwave clad and AISI 304 substrate were studied using scanning electron microscope. Wear debris was analyzed using scanning electron microscopy and energy-dispersive X-ray spectroscopy. The developed clads exhibit significant resistance to wear attributable to the microwave-induced dense microstructure and material properties. The wear rate and friction coefficient were reduced by 67 and 56%, respectively for WC-12Co microwave clad compared to that of the AISI 304 substrate.
Ontology-based word sense disambiguation using semi-automatically constructed ontology

This paper describes a method for disambiguating word senses by using semi-automatically constructed ontology. The ontology stores rich semantic constraints among 1,110 concepts, and enables a natural language processing system to resolve semantic ambiguities by making inferences with the concept network of the ontology. In order to acquire a reasonably practical ontology in limited time and with less manpower, we extend the existing Kadokawa thesaurus by inserting additional semantic relations into its hierarchy, which are classified as case relations and other semantic relations. The former can be obtained by converting valency information and case frames from previously-built electronic dictionaries used in machine translation. The latter can be acquired from concept co-occurrence information, which is extracted automatically from large corpora. In our practical machine translation system, our word sense disambiguation method achieved a 9.2% improvement over methods which do not use an ontology for Korean translation.
A Combined Adaptive Law for Fuzzy Iterative Learning Control of Nonlinear Systems With Varying Control Tasks

To deal with the iterative control of uncertain nonlinear systems with varying control tasks, nonzero initial resetting state errors, and nonrepeatable mismatched input disturbance, a new adaptive fuzzy iterative learning controller is proposed in this paper. The main structure of this learning controller is constructed by a fuzzy learning component and a robust learning component. For the fuzzy learning component, a fuzzy system used as an approximator is designed to compensate for the plant nonlinearity. For the robust learning component, a sliding-mode-like strategy is applied to overcome the nonlinear input gain, input disturbance, and fuzzy approximation error. Both designs are based on a time-varying boundary layer which is introduced not only to solve the problem of initial state errors but also to eliminate the possible undesirable chattering behavior. A new adaptive law combining time- and iteration-domain adaptation is derived to search for suitable values of control parameters and then guarantee the closed-loop stability and error convergence. This adaptive algorithm is designed without using projection or deadzone mechanism. With a suitable choice of the weighting gain, the memory size for the storage of parameter profiles can be greatly reduced. It is shown that all the adjustable parameters as well as internal signals remain bounded for all iterations. Moreover, the norm of tracking state error vector will asymptotically converge to a tunable residual set even when the desired tracking trajectory is varying between successive iterations.
Apatite : Associative Browsing of APIs

Learning how to use new APIs can be difficult, in part because they are large and can be difficult to explore effectively using existing tools. Current objectoriented API documentation is usually organized by class, however programmers sometimes have a desired action or method in mind without knowing which class it might belong to. Programmers using existing API documentation often struggle to determine which of an API’s many classes and methods are the important ones to pay attention to, spending considerable time looking at obscure and irrelevant parts of APIs as a result. To help with these problems, we designed Apatite, an API browsing tool that lets programmers browse by association—investigating which packages, classes, methods go with others. Apatite also adds browsing by actions and properties, and uses statistics about the popularities of items and how often they are used together to provide weighted views of the most relevant items. We used an iterative design process to help tailor the tool to programmers’ needs, and a preliminary user study suggests that it offers advantages over existing tools.
Hydrogen trapping in AISI 4340 steel

AbstractHydrogen trapping in AISI 4340 steel was investigated by thermal analysis at a constant heating rate of 3·4 K min−1. Peaks were observed in the evolution rate v. temperature plots at 388, 545, 611, 678, and 768 K in AISI 4340 steel samples having either pearlitic or spheroidized carbide structure, and analysis suggested that the evolution rate peaks at 388, 545, 611, and 768 K corresponded to the hydrogen release from ferrite/carbide interfaces, dislocations, microvoids, and MnS interfaces respectively. The activation energies for the evolution of trapped hydrogen from microvoids and MnS interfaces were found to be 48·3 and 72·3 KJ mol−1, respectively. It is observed that microvoids were formed at MnS interfaces during the thermomechanical process and these were related to the hydrogen embrittlement phenomena in AISI 4340 steel. It is also found that, in cold worked AISI 4340 steel having a pearlitic structure, the main trapping site of hydrogen was dislocations, not microvoids, the interface area.
Characterization of the Core Rumen Microbiome in Cattle during Transition from Forage to Concentrate as Well as during and after an Acidotic Challenge

This study investigated the effect of diet and host on the rumen bacterial microbiome and the impact of an acidotic challenge on its composition. Using parallel pyrosequencing of the V3 hypervariable region of 16S rRNA gene, solid and liquid associated bacterial communities of 8 heifers were profiled. Heifers were exclusively fed forage, before being transitioned to a concentrate diet, subjected to an acidotic challenge and allowed to recover. Samples of rumen digesta were collected when heifers were fed forage, mixed forage, high grain, during challenge (4 h and 12 h) and recovery. A total of 560,994 high-quality bacterial sequences were obtained from the solid and liquid digesta. Using cluster analysis, prominent bacterial populations differed (P≤0.10) in solid and liquid fractions between forage and grain diets. Differences among hosts and diets were not revealed by DGGE, but real time qPCR showed that several bacteria taxon were impacted by changes in diet, with the exception of Streptococcus bovis. Analysis of the core rumen microbiome identified 32 OTU's representing 10 distinct bacterial taxa including Bacteroidetes (32.8%), Firmicutes (43.2%) and Proteobacteria (14.3%). Diversity of OTUs was highest with forage with 38 unique OTUs identified as compared to only 11 with the high grain diet. Comparison of the microbial profiles of clincial vs. subclinical acidotic heifers found a increases in the relative abundances of Acetitomaculum, Lactobacillus, Prevotella, and Streptococcus. Increases in Streptococcus and Lactobacillus likely reflect the tolerance of these species to low pH and their ability to proliferate on surplus fermentable carbohydrate. The acetogen, Acetitomaculum may thereforeplay a role in the conversion of lactate to acetate in acidotic animals. Further profiling of the bacterial populations associated with subclinical and clinical acidosis could establish a microbial fingerprint for these disorders and provide insight into whether there are causative microbial populations that could potentially be therapeutically manipulated.
Range selection and median: tight cell probe lower bounds and adaptive data structures

<i>Range selection</i> is the problem of preprocessing an input array <i>A</i> of <i>n</i> unique integers, such that given a query (<i>i, j, k</i>), one can report the <i>k</i>'th smallest integer in the subarray <i>A</i>[<i>i</i>], <i>A</i>[<i>i</i> + 1],. , <i>A</i>[<i>j</i>]. In this paper we consider static data structures in the word-RAM for range selection and several natural special cases thereof. The first special case is known as <i>range median</i>, which arises when <i>k</i> is fixed to ⌊(<i>j -- i</i> + 1)/2⌋. The second case, denoted <i>prefix selection</i>, arises when <i>i</i> is fixed to 0. Finally, we also consider the <i>bounded rank prefix selection</i> problem and the <i>fixed rank range selection</i> problem. In the former, data structures must support prefix selection queries under the assumption that <i>k</i> ≤ κ for some value κ ≤ <i>n</i> given at construction time, while in the latter, data structures must support range selection queries where <i>k</i> is fixed beforehand for all queries. We prove cell probe lower bounds for range selection, prefix selection and range median, stating that any data structure that uses <i>S</i> words of space needs Ω(log <i>n</i>/log(<i>Sw/n</i>)) time to answer a query. In particular, any data structure that uses <i>n</i>log<sup><i>O</i>(1)</sup> <i>n</i> space needs Ω(log <i>n</i>/log log <i>n</i>) time to answer a query, and any data structure that supports queries in constant time, needs <i>n</i><sup>1+Ω(1)</sup> space. For data structures that uses <i>n</i> log<sup><i>O</i>(1)</sup> <i>n</i> space this matches the best known upper bound. Additionally, we present a linear space data structure that supports range selection queries in <i>O</i>(log <i>k</i>/log log <i>n</i> + log log <i>n</i>) time. Finally, we prove that any data structure that uses <i>S</i> space, needs Ω(log κ/log(<i>Sw/n</i>)) time to answer a bounded rank prefix selection query and Ω(log <i>k</i>/log(<i>Sw/n</i>)) time to answer a fixed rank range selection query. This shows that our data structure is optimal except for small values of <i>k</i>.
Multiuser XOR-and-forward relaying using Alamouti STBC

In this paper we propose a multiuser two-way relaying scheme using an XOR-and-forward strategy with space-time block coding (STBC). In this scheme, all users transmit their symbols simultaneously to the relay in the first phase. The relay uses minimum mean square error detection to estimate the transmitted symbols, and then it uses an XOR operation to combine the estimates of the symbols for each user pair and broadcasts them in the second phase. The bit error rate performance and the outage capacity for the proposed scheme is evaluated numerically in an uncorrelated flat fading channel. The simulation results show that the scheme can improve the throughput and the channel reliability.
Algorithm 1 Dynamic Graph Matching ( DGM ) Input : Unlabelled features

Label estimation is an important component in an unsupervised person re-identification (re-ID) system. This paper focuses on cross-camera label estimation, which can be subsequently used in feature learning to learn robust re-ID models. Specifically, we propose to construct a graph for samples in each camera, and then graph matching scheme is introduced for cross-camera labeling association. While labels directly output from existing graph matching methods may be noisy and inaccurate due to significant crosscamera variations, this paper propose a dynamic graph matching (DGM) method. DGM iteratively updates the image graph and the label estimation process by learning a better feature space with intermediate estimated labels. DGM is advantageous in two aspects: 1) the accuracy of estimated labels is improved significantly with the iterations; 2) DGM is robust to noisy initial training data. Extensive experiments conducted on three benchmarks including the large-scale MARS dataset show that DGM yields competitive performance to fully supervised baselines, and outperforms competing unsupervised learning methods.
Modification at position 9 with 1-methyladenosine is crucial for structure and function of nematode mitochondrial tRNAs lacking the entire T-arm

The mitochondria of the nematode Ascaris suum have tRNAs with unusual secondary structures that lack either the T-arm or D-arm found in most other organisms. Of the twenty-two tRNA species present in the mitochondria of A.suum, twenty lack the entire T-arm and two serine tRNAs lack the D-arm. To understand how such unusual tRNAs work in the nematode mitochondrial translation system, we analyzed post-transcriptional modifications of 11 mitochondrial tRNA species purified from A.suum, 10 of which lacked a T-arm and one of which lacked a D-arm. The most characteristic feature of nematode mitochondrial tRNAs lacking a T-arm was the presence of 1-methyladenosine at position 9 (m1A9). Synthesis of T-armless tRNAs with or without the modified nucleoside showed that T-armless tRNAs without the modification had much lower aminoacylation and EF-Tu-binding activities than native tRNAs. The addition of a single methyl group to A9 of these tRNAs was sufficient to restore nearly native levels of aminoacylation and EF-Tu-binding activity as well as tertiary structure, suggesting that m1A9 is a key residue for the activity of T-armless tRNAs. Thus, m1A9 is indispensable for the structure and function of T-armless tRNAs of nematode mitochondrial origin.