Miracle-dz/UniFAR-FTUs huggingface dataset:
Strong Coresets for k-Median and Subspace Approximation: Goodbye Dimension

We obtain the first strong coresets for the k-median and subspace approximation problems with sum of distances objective function, on n points in d dimensions, with a number of weighted points that is independent of both n and d; namely, our coresets have size poly(k/ε). A strong coreset (1+ε)-approximates the cost function for all possible sets of centers simultaneously. We also give efficient nnz(A) + (n+d) poly(k/ε) + exp(poly(k/ε)) time algorithms for computing these coresets. We obtain the result by introducing a new dimensionality reduction technique for coresets that significantly generalizes an earlier result of Feldman, Sohler and Schmidt [FSS13] for squared Euclidean distances to sums of P-th powers of Euclidean distances for constant p≥1.
Energy Transfer from Photosystem I to Thermally Reduced Graphene Oxide

The energy transfer from photosynthetic complex photosystem I to thermally reduced graphene oxide was studied using fluorescence microscopy and spectroscopy, and compared against the structure in which monolayer epitaxial graphene was used as the energy acceptor. We find that the properties of reduced graphene oxide (rGO) as an energy acceptor is qualitatively similar to that of epitaxial graphene. Fluorescence quenching, which in addition to shortening of fluorescence decay, is a signature of energy transfer varies across rGO substrates and correlates with the transmission pattern. We conclude that the efficiency of the energy transfer depends on the number of rGO layers in the flakes and decreases with this number. Furthermore, careful analysis of fluorescence imaging data confirms that the energy transfer efficiency dependence on the excitation wavelength, also varies with the number of rGO flakes.
Anti-Obesity Effects of Collagen Peptide Derived from Skate (Raja kenojei) Skin Through Regulation of Lipid Metabolism

This study investigated the anti-obesity effects of collagen peptide derived from skate skin on lipid metabolism in high-fat diet (HFD)-fed mice. All C57BL6/J male mice were fed a HFD with 60% kcal fat except for mice in the normal group which were fed a chow diet. The collagen-fed groups received collagen peptide (1050 Da) orally (100, 200, or 300 mg/kg body weight per day) by gavage, whereas the normal and control groups were given water (n = 9 per group). The body weight gain and visceral adipose tissue weight were lower in the collagen-fed groups than in the control group (p < 0.05). Plasma and hepatic lipid levels were significantly reduced by downregulating the hepatic protein expression levels for fatty acid synthesis (sterol regulatory element binding protein-1 (SREBP-1), fatty acid synthase (FAS), and acetyl-CoA carboxylase (ACC)) and cholesterol synthesis (SREBP-2 and 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR)) and upregulating those for β-oxidation (peroxisome proliferator-activated receptor alpha (PPAR-α) and carnitine palmitoyltransferase 1 (CPT1)) and synthesis of bile acid (cytochrome P450 family 7 subfamily A member 1 (CYP7A1)) (p < 0.05). In the collagen-fed groups, the hepatic protein expression level of phosphorylated 5′ adenosine monophosphate-activated protein kinase (p-AMPK) and plasma adiponectin levels were higher, and the leptin level was lower (p < 0.05). Histological analysis revealed that collagen treatment suppressed hepatic lipid accumulation and reduced the lipid droplet size in the adipose tissue. These effects were increased in a dose-dependent manner. The findings indicated that skate collagen peptide has anti-obesity effects through suppression of fat accumulation and regulation of lipid metabolism.
Adenoviromics: Mining the Human Adenovirus Species D Genome

Human adenovirus (HAdV) infections cause disease world-wide. Whole genome sequencing has now distinguished 90 distinct genotypes in 7 species (A-G). Over half of these 90 HAdVs fall within species D, with essentially all of the HAdV-D whole genome sequences generated in the last decade. Herein, we describe recent new findings made possible by mining of this expanded genome database, and propose future directions to elucidate new functional elements and new functions for previously known viral components.
Quantum Language Model-based Query Expansion

The analogy between words, documents and queries and the Quantum Mechanics (QM) concepts gives rise to various quantum-inspired Information Retrieval (IR) models. As one of the most successful applications among them, Quantum Language Model (QLM) achieves superior performances compared to various classical models on ad-hoc retrieval tasks. However, the EM-based estimation strategy for QLM is limited in that it cannot efficiently converge to global optimum. As a result, subsequent QLM-based models are more or less restricted to a limited vocabulary. In order to ease this limitation, this study investigates a query expansion framework on the QLM basis. Essentially, the additional terms are selected from the constructed QLM of top-K returned documents in the initial ranking, and a re-ranking is conducted on the expanded query to generate the final ranks. Experiments on TREC 2013 and 2014 session track datasets demonstrate the effectiveness of our model.
Towards a domain-specific modeling language for self-adaptive systems conceptual modeling

Self-adaptive Systems (SaSs) are able to adapt their behavior at runtime in response to contextual changes. In this work, we are interested in SaSs conceptual modeling, which is the act of creating models that describe aspects of the world. SaSs modeling is a non-trivial activity because it deals with requirements uncertainty, contextual changes, and behavior adaptation. This complexity can be minimized by using Domain-Specific Modeling Languages (DSMLs), which may be created by extending Unified Modeling Language (UML). In this paper, we propose a UML profile that represents the higher-level abstractions required to provide support for SaSs conceptual modeling. We developed the UML profile by modeling the domain of interest and extending the UML class metaclass. The UML profile was evaluated through the focus group technique, which was performed by software engineering professors. As the outcome, the focus group participants considered the UML profile able to produce SaSs conceptual models with more expressiveness than UML standard.
A Vertical PRF Architecture for Microblog Search

In microblog retrieval, query expansion can be essential to obtain good search results due to the short size of queries and posts. Since information in microblogs is highly dynamic, an up-to-date index coupled with pseudo-relevance feedback (PRF) with an external corpus has a higher chance of retrieving more relevant documents and improving ranking. In this paper, we focus on the research question:how can we reduce the query expansion computational cost while maintaining the same retrieval precision as standard PRF? Therefore, we propose to accelerate the query expansion step of pseudo-relevance feedback. The hypothesis is that using an expansion corpus organized into verticals for expanding the query, will lead to a more efficient query expansion process and improved retrieval effectiveness. Thus, the proposed query expansion method uses a distributed search architecture and resource selection algorithms to provide an efficient query expansion process. Experiments on the TREC Microblog datasets show that the proposed approach can match or outperform standard PRF in MAP and NDCG@30, with a computational cost that is three orders of magnitude lower.
Modeling the Human Visuo-Motor System to Support Remote-Control Operation

The working hypothesis in this project is that gaze interactions play a central role in structuring the joint control and guidance strategy of the human operator performing spatial tasks. Perceptual guidance and control is the idea that the visual and motor systems form a unified perceptuo-motor system where necessary information is naturally extracted by the visual system. As a consequence, the response of this system is constrained by the visual and motor mechanisms and these effects should manifest in the behavioral data. Modeling the perceptual processes of the human operator provides the foundation necessary for a systems-based approach to the design of control and display systems used by remotely operated vehicles. This paper investigates this hypothesis using flight tasks conducted with remotely controlled miniature rotorcraft, taking place in indoor settings that provide rich environments to investigate the key processes supporting spatial interactions. This work also applies to spatial control tasks in a range of application domains that include tele-operation, gaming, and virtual reality. The human-in-the-loop system combines the dynamics of the vehicle, environment, and human perception–action with the response of the overall system emerging from the interplay of perception and action. The main questions to be answered in this work are as follows: (i) what is the general control and guidance strategy of the human operator, and (ii) how is information about the vehicle and environment extracted visually by the operator. The general approach uses gaze as the primary sensory mechanism by decoding the gaze patterns of the pilot to provide information for estimation, control, and guidance. This work differs from existing research by taking what have largely been conceptual ideas on action–perception and structuring them to be implemented for a real-world problem. The paper proposes a system model that captures the human pilot’s perception–action loop; the loop that delineates the main components of the pilot’s perceptuo-motor system, including estimation of the vehicle state and task elements based on operator gaze patterns, trajectory planning, and tracking control. The identified human visuo-motor model is then exploited to demonstrate how the perceptual and control functions system can be augmented to reduce the operator workload.
Differential Expression of Keratinocyte-Derived Extracellular Vesicle Mirnas Discriminate Exosomes From Apoptotic Bodies and Microvesicles

Extracellular vesicles (EVs) are mammalian cell-derived nano-scale structures enclosed by a lipid bilayer that were previously considered to be cell debris with little biological value. However, EVs are now recognized to possess biological function, acting as a packaging, transport and delivery mechanisms by which functional molecules (i.e., miRNAs) can be transferred to target cells over some distance. To examine the miRNA from keratinocyte-derived EVs, we isolated three distinct populations of EVs from both HaCaT and primary human keratinocytes (PKCs) and characterized their biophysical, biochemical and functional features by using microscopy, immunoblotting, nanoparticle tracking, and next generation sequencing. We identified 1,048; 906; and 704 miRNAs, respectively, in apoptotic bodies (APs), microvesicles (MVs) and exosomes (EXs) released from HaCaT, and 608; 506; and 622 miRNAs in APs, MVs and EXs released from PKCs. In which, there were 623 and 437 identified miRNAs common to three HaCaT-derived EVs and PKC-derived EVs, respectively. In addition, we found hundreds of exosomal miRNAs that were previously un-reported. Differences in the abundance levels of the identified EV miRNAs could discriminate between the three EV populations. These data contribute substantially to knowledge within the EV-identified miRNA database, especially with regard to keratinocyte-derived EV miRNA content.
Knowledge Node and Relation Detection

A bottleneck problem in detecting knowledge nodes and their relations is how to extract accurately and correctly and codify the complex knowledge assertions from full-text documents (human intelligence) into the format of “machine intelligence” (computer-processable knowledge assertions). This paper reports a preliminary study that aims at this bottleneck problem by starting from the fundamentals of KR—representing knowledge from full-text documents by using knowledge node and relation recognition methods and tools. We collected data from full-text biomedical research publications and used manual and automatic tools to investigate the strengths and limitations of these methods. The findings show that MetaMap did a better job in detecting concepts from texts while SemRep is capable of extract relations between k-nodes. The paper presents the findings from the perspectives of degree of abstraction, types of k-nodes and relations, and linguistic structures and the evaluation results using the BLEU and cosine similarity measures.
Beyond Bisection: Spectral Partitioning of Networks into Multiple Communities

Thomas Richardson, Peter J. Mucha, and Mason A. Porter Carolina Center for Interdisciplinary Applied Mathematics, Department of Mathematics, University of North Carolina, Chapel Hill, NC 27599-3250, USA; Institute for Advanced Materials, Nanoscience and Technology University of North Carolina, Chapel Hill, NC 27599; and Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, OX1 3LB, United Kingdom (Dated: December 15, 2008)
Dietary fiber intake and risks of proximal and distal colon cancers

Abstract The purpose of this study was to conduct a systematic review and meta-analysis of studies investigating the relationship between dietary fiber intake and subsite-specific colon cancer. The PubMed database was searched to identify relevant cohort studies published from inception to August 2016 in order to examine individually the association between dietary fiber intake and the risk of proximal colon cancer (PCC), and that between dietary fiber intake and the risk of distal colon cancer (DCC). We searched the reference lists of the studies included in our analysis as well as those listed in the published meta-analyses. A random-effects model was used to compute summary risk estimates. Heterogeneity was assessed using I2 and Q statistics. Publication bias was assessed with the Egger's and Begg's tests, with a P value of P < . 10 indicating publication bias. All statistical tests were 2-sided. We identified and included 11 prospective cohort studies in the final meta-analysis. The risks of PCC and DCC among individuals in the highest dietary fiber intake quartile/quintile were 14% (relative risk [RR] = 0.86, 95% confidence interval [CI] = 0.78–0.95) and 21% (RR = 0.79, 95% CI = 0.71–0.87) lower, respectively, than those among individuals with the lowest dietary fiber intake. In a subgroup analysis, the inverse association observed in the sex-based subgroup was apparent only for men with PCC. Dietary fiber intake was inversely associated with DCC for both men and women. In addition, dietary fiber intake appeared to be inversely associated with PCC only in European countries, whereas this association was observed for DCC in both European countries and the United States. Our findings reveal that dietary fiber intake is associated inversely with the risk of both PCC and DCCs.
What's Old Is New Again: The Sacroiliac Joint as a Cause of Lateralizing Low Back Pain

It has not been easy to identify mechanical failure of the sacroiliac joint (SIJ) with traditional imaging. The integrated model of function (Lee and Vleeming, 1998) suggests that under normal circumstances, form and force closure combined contribute to sacral nutation and “locking” the SIJ for optimal load transfer. This model is supported by clinical evidence and scintigraphic findings that contribute to successful therapy in 80% of cases. Single-photon emission computed tomography and x-ray computed tomography (SPECT-CT), a hybrid device, was used in a study of 1200 patients (64% female and 36% male patients with an average age of 42 years; range, 15–78 years) with a clinical diagnosis of SIJ incompetence (pelvic girdle pain syndrome). Standard clinical testing and an alternate series of tests were used as a reference standard for imaging. Symptoms were present for a mean of 43 months. Imaging finding were of increased uptake in the upper SIJ (S1–S2), with extension into the dorsal interosseous ligament and measurable by count profile. Associated findings of tendon enthesopathy reflected altered biomechanics around the pelvis. Ipsilateral adductor enthesopathy was found in 70% and contralateral hamstring enthesopathy in 60% of patients. SPECT-CT criteria for the diagnosis of SIJ incompetence were developed and validated. SPECT-CT is a valid and reproducible technique for the diagnosis of SIJ incompetence with high concordance and specificity compared to the reference standards. Findings are supportive of the integrated model of SIJ function proposed by Lee and Vleeming.
Development of Model Predictive Controller for a Tail-Sitter VTOL UAV in Hover Flight

This paper presents a model predictive controller (MPC) for position control of a vertical take-off and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV) in hover flight. A ‘cross’ configuration quad-rotor tail-sitter UAV is designed with the capabilities for both hover and high efficiency level flight. The six-degree-of-freedom (DOF) nonlinear dynamic model of the UAV is built based on aerodynamic data obtained from wind tunnel experiments. The model predictive position controller is then developed with the augmented linearized state-space model. Measured and unmeasured disturbance model are introduced into the modeling and optimization process to improve disturbance rejection ability. The MPC controller is first verified and tuned in the hardware-in-loop (HIL) simulation environment and then implemented in an on-board flight computer for real-time indoor experiments. The simulation and experimental results show that the proposed MPC position controller has good trajectory tracking performance and robust position holding capability under the conditions of prevailing and gusty winds.
Neural Machine Translation of Logographic Language Using Sub-character Level Information

Recent neural machine translation (NMT) systems have been greatly improved by encoder-decoder models with attention mechanisms and sub-word units. However, important differences between languages with logographic and alphabetic writing systems have long been overlooked. This study focuses on these differences and uses a simple approach to improve the performance of NMT systems utilizing decomposed sub-character level information for logographic languages. Our results indicate that our approach not only improves the translation capabilities of NMT systems between Chinese and English, but also further improves NMT systems between Chinese and Japanese, because it utilizes the shared information brought by similar sub-character units.
Automated Test Generation to Detect Individual Discrimination in AI Models

Dependability on AI models is of utmost importance to ensure full acceptance of the AI systems. One of the key aspects of the dependable AI system is to ensure that all its decisions are fair and not biased towards any individual. In this paper, we address the problem of detecting whether a model has an individual discrimination. Such a discrimination exists when two individuals who differ only in the values of their protected attributes (such as, gender/race) while the values of their non-protected ones are exactly the same, get different decisions. Measuring individual discrimination requires an exhaustive testing, which is infeasible for a non-trivial system. In this paper, we present an automated technique to generate test inputs, which is geared towards finding individual discrimination. Our technique combines the well-known technique called symbolic execution along with the local explainability for generation of effective test cases. Our experimental results clearly demonstrate that our technique produces 3.72 times more successful test cases than the existing state-of-the-art across all our chosen benchmarks.
GEOSEG: A Computer Vision Package for Automatic Building Segmentation and Outline Extraction

Recently, deep learning algorithms, especially fully convolutional network based methods, have become very popular in the field of remote sensing. However, these methods are implemented and evaluated through various datasets and deep learning frameworks. There has not been a package that covers these methods in a unified manner. In this study, we introduce a computer vision package termed Geoseg that focuses on building segmentation and outline extraction. Geoseg implements nine state-of-the-art models as well as utility scripts needed to conduct model training, logging, evaluation, and visualization. The implementation of Geoseg emphasizes unification, simplicity, and flexibility. The performance and computational efficiency of all implemented methods are evaluated by a comparison experiment using a unified, high-quality aerial image dataset.
Nasointestinal tubes versus nasogastric tubes in the management of small-bowel obstruction

Background: There is no consensus regarding the therapeutic effect of nasointestinal tubes (NITs) versus nasogastric tubes (NGTs) in the management of small-bowel obstruction (SBO). This study aimed to compare the clinical outcomes between the use of NITs and NGTs in the management of SBO. Methods: Published studies on comparing NITs with NGTs in the treatment of SBO were searched from electronic databases. Two investigators independently extracted the data; any discrepancies were adjudicated by a third investigator. Pooled odds ratio (OR) and 95% confidence interval (CI) were calculated using Review Manager 5.0. Results: An extensive literature search identified 268 relevant publications, 4 of which met the inclusion criteria. There were no significant differences in the nonrequirement of operative intervention between NITs and NGTs groups (OR: 1.79; 95% CI: 0.55, 5.84). Compared with the NGTs, the NITs, which successfully passed through the pylorus, did not decrease the rate of operation in patients with SBO (OR: 2.19; 95% CI: 0.59, 8.15). There was no advantage of NITs over NGTs in patients with partial SBO (P-SBO) (OR: 1.04; 95% CI: 0.23, 4.60). Postoperative complications were compared between the groups (OR: 2.13; 95% CI: 1.09, 4.15). Conclusion: The result of this meta-analysis showed no advantage of NITs over NGTs in the management of patients with SBO.
Risk Coupling Analysis for Components of a Consumer Product Use Scenario Based on N-K Model

This paper innovatively applies N-K model to assessment of consumer product safety risks. Based on a good understanding of how to build a risk coupling model for components of a consumer product use scenario, the paper analyzes characteristics of each component, builds an N-K model-based risk coupling model for such components and calculates the coupling measure of the model. Compared with the traditional correlation analysis, the quantitative model algorithm established in this paper is more feasible and scientific.
Experience: Enhancing Address Matching with Geocoding and Similarity Measure Selection

Given a query record, record matching is the problem of finding database records that represent the same real-world object. In the easiest scenario, a database record is completely identical to the query. However, in most cases, problems do arise, for instance, as a result of data errors or data integrated from multiple sources or received from restrictive form fields. These problems are usually difficult, because they require a variety of actions, including field segmentation, decoding of values, and similarity comparisons, each requiring some domain knowledge. In this article, we study the problem of matching records that contain address information, including attributes such as Street-address and City. To facilitate this matching process, we propose a domain-specific procedure to, first, enrich each record with a more complete representation of the address information through geocoding and reverse-geocoding and, second, to select the best similarity measure per each address attribute that will finally help the classifier to achieve the best f-measure. We report on our experience in selecting geocoding services and discovering similarity measures for a concrete but common industry use-case.