Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Algorithms for Segmented Regression

We study the fixed design segmented regression problem: Given noisy samples from a piecewise linear function $f$, we want to recover $f$ up to a desired accuracy in mean-squared error. Previous rigorous approaches for this problem rely on dynamic programming (DP) and, while sample efficient, have running time quadratic in the sample size. As our main contribution, we provide new sample near-linear time algorithms for the problem that -- while not being minimax optimal -- achieve a significantly better sample-time tradeoff on large datasets compared to the DP approach. Our experimental evaluation shows that, compared with the DP approach, our algorithms provide a convergence rate that is only off by a factor of $2$ to $4$, while achieving speedups of three orders of magnitude.
Adaptive Parameters for Entity Recognition with Perceptron HMMs

We discuss the problem of model adaptation for the task of named entity recognition with respect to the variation of label distributions in data from different domains. We investigate an adaptive extension of the sequence perceptron, where the adaptive component includes parameters estimated from unlabelled data in combination with background knowledge in the form of gazetteers. We apply this idea empirically on adaptation experiments involving two newswire datasets from different domains and compare with other popular methods such as self training and structural correspondence learning.
XMM-Newton observations of the young open cluster Blanco 1. I. X-ray spectroscopy and photometry

We present an X-ray study of the high metallicity young open cluster Blanco 1 based on XMM-Newton data. X-ray spectroscopy of cluster members is presented for the first time as well as new X-ray distribution functions of late-type stars. We detected all known dF and dG stars in the EPIC field and 80% and 90% of dK and dM stars, respectively. The X-ray spectral analysis of the X-ray brightest cluster stars and X-ray color analysis of a larger sample show that a model with two temperatures (at about 0.3 and 1 keV) explains the quiescent activity phase spectra. We discuss also the nature of unidentified X-ray sources in the observed region and their X-ray spectral properties.
A unified learning framework for auto face annotation by mining web facial images

Auto face annotation plays an important role in many real-world multimedia information and knowledge management systems. Recently there is a surge of research interests in mining weakly-labeled facial images on the internet to tackle this long-standing research challenge in computer vision and image understanding. In this paper, we present a novel unified learning framework for face annotation by mining weakly labeled web facial images through interdisciplinary efforts of combining sparse feature representation, content-based image retrieval, transductive learning and inductive learning techniques. In particular, we first introduce a new search-based face annotation paradigm using transductive learning, and then propose an effective inductive learning scheme for training classification-based annotators from weakly labeled facial images, and finally unify both transductive and inductive learning approaches to maximize the learning efficacy. We conduct extensive experiments on a real-world web facial image database, in which encouraging results show that the proposed unified learning scheme outperforms the state-of-the-art approaches.
DBA's Perspective on Use of Information Visualization in Electronic Health Records

DBA's perspective for Information Visualization (IV) assists in providing a detailed insight about patient history in Electronic Health Records (EHR). These data visualizations are used by different stake holders in public hospitals such as Doctors, Database Administrators (DBA) and visual designers in order to improve health services for patients. This is not possible without the contribution of DBAs, who are directly involved in launching efficient query system and required data retrieval for resulting visualization. EHR database is comprising of different forms of data i.e., numbers, texts, pictures and graphs resulting in a challenge for creating a meaningful visualization for single or multiple patients. DBAs have EHR knowledge gaps, lesser exposure to the transformation process of data into effective visualization and understanding about IV limitations result in poor and less efficient IV tools. This study highlights the challenging factors that affect DBAs in understanding, developing and controlling EHR visualization. These factors are selected after a literature review and further analysis by a questionnaire based study on DBAs in two different government hospitals. This will help in highlighting the limitations of DBAs skills and experience and assist in determining the contribution of their role in the development of future IV applications. This work is a second phase of our ongoing research for designing a model, CARE 1.0, as a future IV solution in multiple EHR.
Primes in Elliptic Divisibility Sequences

Morgan Ward pursued the study of elliptic divisibility sequences initiated by Lucas, and Chudnovsky and Chudnovsky suggested looking at elliptic divisibility sequences for prime appearance. The problem of prime appearance in these sequences is examined here from a theoretical and a practical viewpoint. We exhibit calculations, together with a heuristic argument, to suggest that these sequences contain only finitely many primes.
Solving Cold Start WithLebiD 2

Abstract—Cold-Start is one of the most difficult problems faced by web companies today in the domain of recommendation system. Cold-Start problem refers to predicting the behavior of a new user having no history. Common algorithms used to predict user’s behavior fail at addressing the cold-start problem because the algorithms are based on the user history with the company. But in this paper, we successfully solve the cold-start problem by applying the model based paradigm to the trust based methodology. In this paper, we explain our method in detail.
PHASE DIAGRAM OF NEUTRAL QUARK MATTER AT MODERATE DENSITIES

We discuss the phase diagram of moderately dense, locally neutral three-flavor quark matter using the framework of an effective model of quantum chromodynamics with a local interaction. The phase diagrams in the plane of temperature and quark chemical potential as well as in the plane of temperature and lepton-number chemical potential are discussed.
Real-Time Bladder Lesion Registration and Navigation: A Phantom Study

Background Bladder cancer is the fourth most common malignancy in men, with a recurrence rate of 33–64%. Tumor documentation during cystoscopy of the bladder is suboptimal and might play a role in these high recurrence rates. Objective In this project, a bladder registration and navigation system was developed to improve bladder tumor documentation and consequently increase reproducibility of the cystoscopy. Materials/Methods The bladder registration and navigation system consists of a stereo-tracker that tracks the location of a newly developed target, which is attached to the endoscope during cystoscopy. With this information the urology registration and navigation software is able to register the 3D position of a lesion of interest. Simultaneously, the endoscopic image is captured in order to combine it with this 3D position. To enable navigation, navigational cues are displayed on the monitor, which subsequently direct the cystoscopist to the previously registered lesion. To test the system, a rigid and a flexible bladder phantom was developed. The system's robustness was tested by measuring the accuracy of registering and navigating the lesions. Different calibration procedures were compared. It was also tested whether system accuracy is limited by using a previously saved calibration, to avoid surgical delay due to calibration. Urological application was tested by comparing a rotational camera (fixed to the rotating endoscope) to a non-rotational camera (dangling by gravity) used in standard urologic practice. Finally, the influence of volume differences on registering and navigating was tested. Results/Conclusion The bladder registration and navigation system has an acceptable accuracy for bladder lesion registration and navigation. Limitations for patient determinants included changes in bladder volume and bladder deformation. In vivo studies are required to measure the effect of these limitations and functionality in urological practice as a tool to increase reproducibility of the cystoscopy.
Passivity Analysis of Uncertain Neutral Fuzzy Systems

In this paper, the passivity analysis of neutral fuzzy systems with delays and bounded uncertainties is considered. Based on Lyapunov-Krasovskii functional, the LMI approach and the descriptor system approach, sufficient conditions for passivity are obtained. Finally, a simulation example is provided to demonstrate effectiveness and applicability of the theoretical results.
Coffee and Caffeine Ingestion Have Little Effect on Repeated Sprint Cycling in Relatively Untrained Males

The present study investigated the effect of ingesting caffeine-dose-matched anhydrous caffeine or coffee on the performance of repeated sprints. Twelve recreationally active males (mean ± SD age: 22 ± 2 years, height: 1.78 ± 0.07 m, body mass: 81 ± 16 kg) completed eighteen 4 s sprints with 116 s recovery on a cycle ergometer on four separate occasions in a double-blind, randomised, counterbalanced crossover design. Participants ingested either 3 mg·kg−1 of caffeine (CAF), 0.09 g·kg−1 coffee, which provided 3 mg·kg−1 of caffeine (COF), a taste-matched placebo beverage (PLA), or a control condition (CON) 45 min prior to commencing the exercise protocol. Peak and mean power output and rating of perceived exertion (RPE) were recorded for each sprint. There were no significant differences in peak power output (CAF: 949 ± 199 W, COF: 949 ± 174 W, PLA: 971 ± 149 W and CON: 975 ± 170 W; p = 0.872; ηP2 = 0.02) or mean power output (CAF: 873 ± 172 W, COF: 862 ± 44 W, PLA: 887 ± 119 W and CON: 892 ± 143 W; p = 0.819; ηP2 = 0.03) between experimental conditions. Mean RPE was similar for all trials (CAF: 11 ± 2, COF: 11 ± 2, PLA: 11 ± 2 and CON: 11 ± 2; p = 0.927; ηP2 = 0.01). Neither the ingestion of COF or CAF improved repeated sprint cycling performance in relatively untrained males.
A statistical classification approach to question answering using Web data

In this paper we treat question answering (QA) as a classification problem. Our motivation is to build systems for many languages without the need for highly tuned linguistic modules. Consequently, word tokens and Web data are used extensively but no explicit linguistic knowledge is incorporated. A mathematical model for answer retrieval, answer classification and answer length prediction is derived. The TREC 2002 QA task is used for system development where 33% of questions are answered correctly. Performance is then evaluated on the factoid questions of the TREC 2003 QA task where 23% of questions were answered correctly, which would rank the system in the top 10 of contemporary QA systems on the same task
Traffic light recognition using image processing compared to learning processes

In this paper we introduce a real-time traffic light recognition system for intelligent vehicles. The method proposed is fully based on image processing. Detection step is achieved in grayscale with spot light detection, and recognition is done using our generic “adaptive templates”. The whole process was kept modular which make our TLR capable of recognizing different traffic lights from various countries.
Audio-based automatic management of TV commercials

Although TV commercial identification and clustering are suitable applications for automatic multimedia indexing technology, they remain as problems still unsolved. Most current systems either require a big computational load and therefore can not be executed online, or just perform a detection, without clustering nor identification. In this paper two advertisement indexing approaches are presented: an off-line detection and clustering system and an online identification system, both based only on audio features for computational reasons. For the off-line clustering two metrics are evaluated, and an initial commercial boundary detection algorithm, based on identifying drop energy points which are also acoustic change boundaries, is presented. For the on-line system we analyze the response-time/identification scores constraints. Experiments performed on real data validate both off-line and on-line implementations as well as that audio only features are enough discriminant to detect and classify TV commercials.
Characterisation of Two Oxidosqualene Cyclases Responsible for Triterpenoid Biosynthesis in Ilex asprella

Ilex asprella, a plant widely used as a folk herbal drug in southern China, produces and stores a large amount of triterpenoid saponins, most of which are of the α-amyrin type. In this study, two oxidosqualene cyclase (OSC) cDNAs, IaAS1 and IaAS2, were cloned from the I. asprella root. Functional characterisation was performed by heterologous expression in the yeast Saccharomyces cerevisiae. Analysis of the resulting products by gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS) showed that both genes encode a mixed amyrin synthase, producing α-amyrin and β-amyrin at different ratios. IaAS1, which mainly produces α-amyrin, is the second triterpene synthase so far identified in which the level of α-amyrin produced is ≥80% of total amyrin production. By contrast, IaAS2 mainly synthesises β-amyrin, with a yield of 95%. Gene expression patterns of these two amyrin synthases in roots and leaves of I. asprella were found to be consistent with the content patterns of total saponins. Finally, phylogenetic analysis and multiple sequence alignment of the two amyrin synthases against several known OSCs from other plants were conducted to further elucidate their evolutionary relationship.
Joint power optimization of data center network and servers with correlation analysis

Data center power optimization has recently received a great deal of research attention. For example, server consolidation has been demonstrated as one of the most effective energy saving methodologies. Likewise, traffic consolidation has also been recently proposed to save energy for data center networks (DCNs). However, current research on data center power optimization focuses on servers and DCN separately. As a result, the optimization results are often inferior, because server consolidation without considering the DCN may cause traffic congestion and thus degraded network performance. On the other hand, server consolidation may change the DCN topology, allowing new opportunities for energy savings. In this paper, we propose PowerNetS, a power optimization strategy that leverages workload correlation analysis to jointly minimize the total power consumption of servers and the DCN. The design of PowerNetS is based on the key observations that the workloads of different servers and DCN traffic flows do not peak at exactly the same time. Thus, more energy savings can be achieved if the workload correlations are considered in server and traffic consolidations. In addition, PowerNetS considers the DCN topology during server consolidation, which leads to less inter-server traffic and thus more energy savings and shorter network delays. We implement PowerNetS on a hardware testbed composed of 10 virtual switches configured with a production 48-port OpenFlow switch and 6 servers. Our empirical results with Wikipedia, Yahoo! , and IBM traces demonstrate that PowerNetS can save up to 51.6% of energy for a data center. PowerNetS also outperforms two state-of-the-art baselines by 44.3% and 15.8% on energy savings, respectively. Our simulation results with 72 switches and 122 servers also show the superior energy efficiency of PowerNetS over the baselines.
Measures of postural steadiness: differences between healthy young and elderly adults

Measures of postural steadiness are used to characterize the dynamics of the postural control system associated with maintaining balance during quiet standing. The objective of this study was to evaluate the relative sensitivity of center-of-pressure (COP)-based measures to changes in postural steadiness related to age. A variety of time and frequency domain measures of postural steadiness were compared between a group of twenty healthy young adults (21-35 years) and a group of twenty healthy elderly adults (66-70 years) under both eyes-open and eyes-closed conditions. The measures that identified differences between the eyes-open and eyes-closed conditions in the young adult group were different than those that identified differences between the eye conditions in the elderly adult group. Mean velocity of the COP was the only measure that identified age-related changes in both eye conditions, and differences between eye conditions in both age groups. The results of this study will be useful to researchers and clinicians using COP-based measures to evaluate postural steadiness.
An Efficient Control Strategy for Traffic-Driven Epidemic Spreading by Deleting Edges

The vast majority of traditional control strategies aim at the scenario that th e propagation is driven by reaction processes from nodes to all neighbours. A novel and effective control strategy for restraining epidemic spreading in the situation that epidemic pathways are defined and driven by traffic flows is proposed in this pap er. It is performed by deleting edges in proper order according to their weights. The advantages of our control strategy are of facility and practical importance that such a strategy can better retain the integrity of networks. Simulation results show that the control strategy aiming at deleting edges according to the product of the degrees of two nodes of the edge is proved to be more effective. Moreover, we analyze the curve of critical epidemic threshold on deleting more and more edges and find that there is a sharp transition at the critical point after kicking out a certain fraction of edges.
Pathogenesis of axial spondyloarthropathy in a network perspective

Complex chronic diseases are usually not caused by changes in a single causal gene but by an unbalanced regulating network resulting from the dysfunctions of multiple genes or their products. Therefore, network based systems approach can be helpful for the identification of candidate genes related to complex diseases and their relationships. The Axial spondyloarthropathy (SpA) is a group of chronic inflammatory joint diseases that mainly affects the spine and the sacroiliac joints, yet, the pathogenesis of SpA remains largely unknown. In this paper, we conducted a networked systems study on the pathogenesis of SpA. We integrated data related to SpA, from the OMIM database, proteomics and microarray experiments of SpA, to prioritize SpA candidate disease genes in the context of human protein interactome. Based on the top ranked SpA related genes, we constructed a PPI network and identified potential pathways associated with SpA. The PPI network and pathways reflect the well-known knowledge of SpA, i.e., immune mediated inflammation, as well as imbalanced bone modeling caused new bone formation and bone loss. This study may facilitate our understanding of the SpA pathogenesis from the perspective of network systems.
On the Ability to Search the Space of Programs of Standard, One-point and Uniform Crossover in Genetic Programming

In this paper we study and compare the search properties of different crossover operators in genetic programming (GP) using probabilistic models and experiments to assess the amount of genetic material exchanged between the parents to generate the offspring. These operators are: standard crossover, one-point crossover and a new operator, uniform crossover. Our analysis suggests that standard crossover is a local and biased search operator not ideal to explore the search space of programs effectively. One-point crossover is better in some cases as it is able to perform a global search at the beginning of a run, but it suffers from the same problems as standard crossover later on. Uniform crossover largely overcomes these limitations as it is global and less biased.
Increased formation and decreased resorption of bone in mice with elevated vitamin D receptor in mature cells of the osteoblastic lineage

The microarchitecture of bone is regulated by complex interactions between the bone‐forming and resorbing cells, and several compounds regulate both actions. For example, vitamin D, which is required for bone mineralization, also stimulates bone resorption. Transgenic mice overexpressing the vitamin D receptor solely in mature cells of the osteoblastic bone‐forming lineage were generated to test the potential therapeutic value of shifting the balance of vitamin D activity in favor of bone formation. Cortical bone was 5% wider and 15% stronger in these mice due to a doubling of periosteal mineral apposition rate without altered body weight or calcium homeostatic hormone levels. A 20% increase in trabecular bone volume in transgenic vertebrae was also observed, unexpectedly associated with a 30% reduction in resorption surface rather than greater bone formation. These findings indicate anabolic vitamin D activity in bone and identify a previously unknown pathway from mature osteoblastic cells to inhibit osteoclastic bone resorption, counterbalancing the known stimulatory action through immature osteoblastic cells. A therapeutic approach that both stimulates cortical anabolic and inhibits trabecular resorptive pathways would be ideal for treatment of osteoporosis and other osteopenic disorders. —Gardiner, E. M. , Baldock, P. A. , Thomas, G. P., Sims, N. A. , Henderson, N. K. , Hollis, B. , White, C. P., Sunn, K. L. , Morrison, N. A. , Walsh, W. R. , Eisman, J. A. Increased formation and decreased resorption of bone in mice with elevated vitamin D receptor in mature cells of the osteoblastic lineage. FASEB J. 14, 1908–1916 (2000)
Activin A Modulates CRIPTO-1/HNF4α+ Cells to Guide Cardiac Differentiation from Human Embryonic Stem Cells

The use of human pluripotent stem cells in basic and translational cardiac research requires efficient differentiation protocols towards cardiomyocytes. In vitro differentiation yields heterogeneous populations of ventricular-, atrial-, and nodal-like cells hindering their potential applications in regenerative therapies. We described the effect of the growth factor Activin A during early human embryonic stem cell fate determination in cardiac differentiation. Addition of high levels of Activin A during embryoid body cardiac differentiation augmented the generation of endoderm derivatives, which in turn promoted cardiomyocyte differentiation. Moreover, a dose-dependent increase in the coreceptor expression of the TGF-β superfamily member CRIPTO-1 was observed in response to Activin A. We hypothesized that interactions between cells derived from meso- and endodermal lineages in embryoid bodies contributed to improved cell maturation in early stages of cardiac differentiation, improving the beating frequency and the percentage of contracting embryoid bodies. Activin A did not seem to affect the properties of cardiomyocytes at later stages of differentiation, measuring action potentials, and intracellular Ca2+ dynamics. These findings are relevant for improving our understanding on human heart development, and the proposed protocol could be further explored to obtain cardiomyocytes with functional phenotypes, similar to those observed in adult cardiac myocytes.