Miracle-dz/UniFAR-FTUs huggingface dataset:
Many birds with one stone: multi-objective approximation algorithms

We study network-design problems with multiple design objectives. In particular, we look at two cost measures to be minimized simultaneously: the total cost of the network and the maximum degree of any node in the network. Our main result can be roughly stated as follows: given an integer $b$, we present approximation algorithms for a variety of network-design problems on an $n$-node graph in which the degree of the output network is $O(b \log (\frac{n}{b}))$ and the cost of this network is $O(\log n)$ times that of the minimum-cost degree-$b$-bounded network. These algorithms can handle costs on nodes as well as edges. Moreover, we can construct such networks so as to satisfy a variety of connectivity specifications including spanning trees, Steiner trees and generalized Steiner forests. The performance guarantee on the cost of the output network is nearly best-possible unless $NP = \tilde{P}$. We also address the special case in which the costs obey the triangle inequality. In this case, we obtain a polynomial-time approximation algorithm with a stronger performance guarantee. Given a bound $b$ on the degree, the algorithm finds a degree-$b$-bounded network of cost at most a constant time optimum. There is no algorithm that does as well in the absence of triangle inequality unless $P = NP$. We also show that in the case of spanning networks, we can simultaneously approximate within a constant factor yet another objective: the maximum cost of any edge in the network, also called the bottleneck cost of the network. We extend our algorithms to find TSP tours and $k$-connected spanning networks for any fixed $k$ that simultaneously approximate all these three cost measures.
Modelling the behaviour of a class of dynamical systems with Continuous Petri Nets

This work is concerned with the problem of translating an ordinary differential equation (ODE) with an attractor into a Timed Continuous Petri Net (TCPN) with product semantics. The proposed translation methodology starts by shifting the ODE attractor to a suitable value such that the system evolution is confined to the first orthant (i.e. the evolution will be positive). In the proposed methodology, a state x<sub>i</sub> is represented by a place p<sub>i</sub>. When the derivative of a state x<sub>i</sub> depends on positive or negative terms of x<sub>i</sub>, then input or output transitions are added to p<sub>i</sub> to represent the positive or negative terms respectively. If the derivative of x<sub>i</sub> depends on positive terms of other state variable x<sub>j</sub> then a transition going from p<sub>j</sub> to p<sub>i</sub> is added. If the derivative of x<sub>i</sub> depends on negative terms of other state variable x<sub>j</sub>, then a subnet removing the appropriate marking from p<sub>i</sub> is added. In order to illustrate this methodology, we show how the well known chaotic Rossler system is translated into a TCPN.
Model Cortical Association Fields Account for the Time Course and Dependence on Target Complexity of Human Contour Perception

Can lateral connectivity in the primary visual cortex account for the time dependence and intrinsic task difficulty of human contour detection? To answer this question, we created a synthetic image set that prevents sole reliance on either low-level visual features or high-level context for the detection of target objects. Rendered images consist of smoothly varying, globally aligned contour fragments (amoebas) distributed among groups of randomly rotated fragments (clutter). The time course and accuracy of amoeba detection by humans was measured using a two-alternative forced choice protocol with self-reported confidence and variable image presentation time (20-200 ms), followed by an image mask optimized so as to interrupt visual processing. Measured psychometric functions were well fit by sigmoidal functions with exponential time constants of 30-91 ms, depending on amoeba complexity. Key aspects of the psychophysical experiments were accounted for by a computational network model, in which simulated responses across retinotopic arrays of orientation-selective elements were modulated by cortical association fields, represented as multiplicative kernels computed from the differences in pairwise edge statistics between target and distractor images. Comparing the experimental and the computational results suggests that each iteration of the lateral interactions takes at least ms of cortical processing time. Our results provide evidence that cortical association fields between orientation selective elements in early visual areas can account for important temporal and task-dependent aspects of the psychometric curves characterizing human contour perception, with the remaining discrepancies postulated to arise from the influence of higher cortical areas.
Genetic Susceptibility to Type 2 Diabetes Is Associated with Reduced Prostate Cancer Risk

Objective: To examine the collective effects of type 1 (T1D) and type 2 diabetes (T2D) risk alleles on prostate cancer (PCa) risk. Methods: Using data on 14 and 18 single nucleotide polymorphisms (SNPs) that effect T1D and T2D risk, respectively, we generated risk scores (a ‘risk allele count’ and a ‘genetic relative risk’) for both T1D and T2D for 1,171 non-Hispanic white, PSA-screened PCa cases and 1,101 matched controls from the Cancer Genetic Markers of Susceptibility study. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for associations between the diabetes risk scores and PCa risk. Results: Both T2D risk scores, but neither T1D score, showed an inverse association with PCa (p < 0.01). These associations remained significant after excluding HNF1B SNP rs4430796 (a known PCa risk factor) from the analysis. The highest quartile of the T2D allele count (>20 risk alleles) was associated with reduced PCa risk (OR = 0.77; CI: 0.60–0.99) compared to the lowest category (<17 risk alleles). Conclusions: These results suggest that individuals with increased genetic susceptibility to T2D have decreased risk for PCa. This association is consistent with the observation that individuals with T2D are at decreased risk for PCa; however, data on T2D status was not available for this analysis.
Influence of enzymes on the oil extraction processes in aqueous media

The methods of oil aqueous extraction process (AEP) assisted by enzymes are, over the last 50 years, an alternative designed to replace traditional methods of extraction using organic solvents. To extract the oil using an AEP, the use of specific enzymes, able to hydrolyze some or all components of seeds, can significantly increase the yields of extraction. Hydrolyzing the different constituents of cell walls (cellulose, hemicellulose, pectins, proteins, etc.), enzymes are able to enhance the liberation of the oil. A number of physico-chemical parameters must also be considered for the better expression of the enzymatic mixture, while maintaining the quality of oils and meals. This article presents the various factors influencing the release of oil in aqueous media and the main results obtained by this process on various substrates.
Decentralization and the Quality of Government By Daniel Treisman November 20 , 2000

How does the degree of political decentralization in a country affect the quality of its government? Greater political decentralization might make governments more honest and efficient by bringing officials “closer to the people”, forcing them to compete for mobile capital, and facilitating the satisfaction of diverse local tastes. On the other hand, it might create coordination problems or roadblocks to reform and exacerbate incentives to predate and shirk on public good provision. Empirical work has been inconclusive, in part because different types of decentralization are examined. I define five types of decentralization, and outline five arguments about how specific types may affect government quality. Statistical tests, using newly collected data on up to 154 countries, suggest that states which have more tiers of goverment tend to have higher perceived corruption, and may do a worse job of providing public health services. Federal states appear less effective at providing public health services and (at least among developing countries) at lowering adult illiteracy. The Tieboutian idea that decreasing the size of government units will strengthen competition between governments for capital, thus stimulating greater efficiency and honesty, is not supported. Countries with smaller first-tier jurisdictions tended to be perceived as more corrupt.
New Classes of Mind Bomb-Interacting Proteins Identified from Yeast Two-Hybrid Screens

Notch signaling pathway defines an evolutionarily conserved mechanism in cell-fate determination in a broad spectrum of developmental processes through local cell interactions. mind bomb (mib) encodes an E3 ubiquitin ligase that is involved in Notch activation through Delta ubiquitylation and internalization. To further dissect the function of Mib, two yeast two-hybrid screens for zebrafish Mib/Mib2-binding proteins with different strategies have been performed. 81 putative interesting proteins were discovered and classified into six groups: ubiquitin proteasome pathway, cytoskeleton, trafficking, replication/transcription/translation factors, cell signaling and others. Confirmed by coimmunoprecipitation (Co-IP), Mib interacted with four tested proteins: ubiquitin specific protease 1 (Usp1), ubiquitin specific protease 9 (Usp9), tumor-necrosis-factor-receptor-associated factor (TRAF)-binding domain (Trabid)/zinc finger, RAN-binding domain containing 1 (Zranb1) and hypoxia-inducible factor 1, alpha subunit inhibitor (Hif1an)/factor inhibiting HIF 1 (Fih-1). Usp1, Usp9, Trabid and Fih-1 also bound to zebrafish Mib2, a Mib homolog with similar structural domains and functions. Both Mib and Mib2 can ubiquitylate Trabid and Fih-1, indicating a potential regulating role of Mib and Mib2 on Trabid and Fih-1 and, furthermore, the possible involvement of Notch signaling in hypoxia-regulated differentiation, tumorigenesis and NF-κB pathway. Finally, functions of confirmed Mib/Mib2-interacting proteins are collated, summarized and hypothesized, which depicts a regulating network beyond Notch signaling.
A Matrix Iteration for Dynamic Network Summaries

We propose a new algorithm for summarizing properties of large-scale time-evolving networks. This type of data, recording connections that come and go over time, is generated in many modern applications, including telecommunications and online human social behavior. The algorithm computes a dynamic measure of how well pairs of nodes can communicate by taking account of routes through the network that respect the arrow of time. We take the conventional approach of downweighting for length (messages become corrupted as they are passed along) and add the novel feature of downweighting for age (messages go out of date). This allows us to generalize widely used Katz-style centrality measures that have proved popular in network science to the case of dynamic networks sampled at nonuniform points in time. We illustrate the new approach on synthetic and real data.
Where You Sit Is Where You Stand

In his challenge to equity theory, Leventhal argued that individuals consider other forms of fairness in social interactions, especially procedural justice. Leventhal then suggested that perceptions of procedural justice may vary according to one’s role in the organization. Within this context, this article considers if there are differences between managers’ and employees’ perceptions of procedural justice, and how any differences result in different organizational attitudes. Overall, the findings indicate that managers as a group exhibit significantly higher perceptions of procedural justice compared with employees, but differences in organizational outcomes are inconsistent and deserve further study.
A Behavioral Choice Model Analysis of the Budget Allocation Behavior of Academic Deans

A model of behavioral choice based on expectancy theory was tested in the context of budget allocation decision making by academic deans. Hypotheses dealing with both the direction and magnitude of the criterion behavior received moderate support. Two methods of scaling outcome affect led to similar results. Weighting expectancy by affect did not account for greater criterion variance.
Molecular analysis of the mouse S100A9 gene and evidence that the myeloid specific transcription factor C/EBPepsilon is not required for the regulation of the S100A9/A8 gene expression in neutrophils *

The genomic locus of the mouse S100A9 (MRP14) gene, a myeloid expressed gene belonging to the S100 family, is split in three exons and two introns. Insertions of B1 like and LINE elements as well as several sequence repeat structures are scattered over the gene suggesting that this region of the S100 gene cluster has been the subject of a high mutational activity in mouse evolution. The insertions may represent molecular footprints of a recently postulated inversion event, which resulted in a rearrangement of the S100 gene cluster in mouse compared to man. Deletion analysis of the promoter reveals, that a 1200 bp fragment is able to direct a cell type‐specific expression of a reporter gene in granulocytic 32D cells. Unexpectedly, the myeloid‐specific transcription factor C/EBPepsilon is not needed for the transcriptional upregulation of the S100A9 and S100A8 genes in neutrophils. The data described here provide further insights into the evolution of the S100 gene cluster and into the myeloid‐specific regulation of the murine S100A9 gene expression. J. Cell. Biochem. 80:606–616, 2001. © 2001 Wiley‐Liss, Inc.
Study of Therapy Resistance in Cancer Cells with Functional Proteome Analysis

Abstract Different types of cancer are naturally resistant to many anticancer drugs. Additionally, these tumours develop acquired drug resistance, which includes the classical multidrug resistance (MDR) accompanied by the synthesis of P-glycoprotein, a member of the superfamily of ATP-binding cassette (ABC) transporters. Furthermore, atypical MDR is mediated by several different, some unkown, mechanisms. To overcome chemoresistance problems, antineoplastic drugs are often combined with other modes of therapy, e.g. hyperthermia, where good response has been reported in several experimental tumour models and in advanced cancer patients. The success of this combined anticancer treatment may be limited by an increase in chemoresistance and thermoresistance. A model system to study resistance phenomena is the use of chemoresistant and thermoresistant cancer cell lines. We have established chemoresistant cancer cell lines (gastric and pancreatic carcinoma, fibrosarcoma, melanoma) and now thermoresistant cell lines derived from gastric and pancreatic carcinoma cells and their counterparts that were resistant towards daunorubicin (classical MDR) and mitoxantrone (atypical MDR). Using proteomics, in this paper we evaluate the drug resistance of chemoresistant melanoma cells (parental cell line MeWo and sublines exhibiting drug resistance towards etoposide, cisplatin, fotemustine and vindesine) as a paradigm for analysis of drug resistance phenomena. Additionally, we investigate heat resistance and the interaction of chemoresistance and thermoresistance to identify common pathways using the parental and drug resistant stomach cancer cell lines EPG85-257, EPG85-257RNOV, EPG85-257RDB and their thermoresistant counterparts. Possible implications of differential protein expression will be discussed.
Field Experiences Using iPads

The purpose of this phenomenological case study was to investigate the lived experiences of preservice music teachers using iPads to engage secondary general music students in creating and performing music during field teaching experiences. Two questions guided this research study: (a) What are these preservice teachers’ perceptions of their experiences using iPads to create music and to teach? (b) How do these experiences influence their perceptions of the technology’s effectiveness as a teaching tool? Data were reflections of nine preservice teachers collected over 5 weeks. The essence of the experience was the preservice teachers’ struggle to resolve tensions that emerged while using technology to create and teach music. Tensions caused some to examine cherished beliefs and practices and influenced their development of TPACK (technological pedagogical and content knowledge). Three themes support the essence: (a) tensions, (b) innovation and adaptation, and (c) influence of experiences on perceptions of technology.
Semimechanistic Pharmacokinetic/Pharmacodynamic Model for Assessment of Activity of Antibacterial Agents from Time-Kill Curve Experiments

ABSTRACT Dosing of antibacterial agents is generally based on point estimates of the effect, even though bacteria exposed to antibiotics show complex kinetic behaviors. The use of the whole time course of the observed effects would be more advantageous. The aim of the present study was to develop a semimechanistic pharmacokinetic (PK)/pharmacodynamic (PD) model characterizing the events seen in a bacterial system when it is exposed to antibacterial agents with different mechanisms of action. Time-kill curve experiments were performed with a strain of Streptococcus pyogenes exposed to a wide range of concentrations of the following antibiotics: benzylpenicillin, cefuroxime, erythromycin, moxifloxacin, and vancomycin. Bacterial counts were monitored with frequent sampling during the experiment. A simultaneous fit of all data was accomplished. The degradation of the drugs was monitored and corrected for in the model, and a link model was used to account for an effect delay. In the final PK/PD model, the total bacterial population was divided into two subpopulations: one growing drug-susceptible population and one resting insusceptible population. The drug effect was included as an increase of the killing rate of bacteria in the susceptible state, according to a maximum-effect (Emax) model. An internal model validation showed that the model was robust and had good predictability. In conclusion, for all drugs, the final PK/PD model successfully described bacterial growth and killing kinetics when the bacteria were exposed to different antibiotic concentrations. The semimechanistic model that was developed might, after further refinement, serve as a tool for the development of optimal dosing strategies for antibacterial agents.
, in Incomplete Spinal Cord Injury Patients Effects of High-Frequency Repetitive Transcranial Magnetic Stimulation on Motor and Gait Improvement

Objective. Incomplete spinal cord injury (SCI) patients have the potential to regain some ambulatory function, and optimal reorganization of remaining circuits can contribute to this recovery. We hypothesized that repetitive transcranial magnetic stimulation (rTMS) may promote active recovery of motor function during gait rehabilitation. Methods. A total of 17 incomplete SCI patients were randomized to receive active rTMS or sham stimulation coupled with rehabilitation therapy; 3 patients who began in the sham group crossed over to the active rTMS group after a washout period of more than 3 weeks. Active rTMS consisted of 15 daily sessions over the leg motor area (at 20 Hz). We compared lower-extremity motor score (LEMS), 10-m walking test for walking speed, timed up and go, Walking Index for SCI Scale, Modified Ashworth Scale, and Spinal Cord Injury Spasticity Evaluation Tool at baseline, after the last session, and 2 weeks later in the active rTMS and sham stimulation groups. Results. A significant improvement was observed after the last rTMS session in the active group for LEMS, walking speed, and spasticity. Improvement in walking speed was maintained during the follow-up period. Sham stimulation did not induce any improvement in LEMS, gait assessment, and spasticity after the last session and neither during follow-up. Conclusion. In incomplete SCI, 15 daily sessions of high-frequency rTMS can improve motor score, walking speed, and spasticity in the lower limbs. The study provides evidence for the therapeutic potential of rTMS in the lower extremities in SCI rehabilitation.
City Research Online Title: Measuring Inhibitory Processes for Alcohol-related Attentional Biases: Introducing a Novel Attentional Bias Measure Measuring Inhibitory Processes for Alcohol-related Attentional Biases: Introducing a Novel Attentional Bias Measure

Introduction: Attentional biases for alcohol related information (AB) have often been reported for heavy drinkers. These attentional biases have been found to have predictive value regarding relapse in abstaining alcoholics. Similarly impaired inhibitory processes have also been found to be associated with heavy drinkers. This paper describes a new experimental paradigm that can be utilised to investigate attentional bias towards alcoholrelated visual stimuli, specifically the ability to inhibit the orientation of initial and sustained attention, towards peripherally appearing stimuli. In this way we hope to study a novel aspect of attentional biases and so how they relate to substance abuse. Methods: We used a novel eye-tracking task which aims to measure inhibitory processes for AB. The experiment utilised a gaze contingency paradigm to measure the compulsion to process or attend to alcohol stimuli. 86 undergraduate participants were recruited (31 males; 55 females), aged 18–49 years (m=20.88;sd=4.52). A eak f e ue variable was computed for each participant. This was number of times participants tried to look at peripheral stimuli. We argue that this variable is a direct measure of how distracting peripheral stimuli were. Results: It was found that reported alcohol use was associated with the eye-tracking break frequency measure of inhibitory control. Thus, heavy drinking may be associated with decreased inhibitory control and increased attentional bias. Conclusions: Results suggest that attentional bias is not just a process of stimuli becoming prioritised, but also stimuli becoming compulsory to attend and process.
A kernel-based extreme learning modeling method for speed decision making of autonomous land vehicles

This paper presents a kernel-based extreme learning machine (KELM) modeling method for speed decision making of autonomous land vehicles (ALVs) on rural roads. The model is obtained offline via the KELM algorithm using a small number of typical samples collected by an ALV platform on rural roads from experienced drivers. Compared with other typical machine learning algorithms such as support vector regression and extreme learning machine, the KELM method has the advantages of fast training speed and higher modeling precision. Real-vehicle experiments have been carried out to test the model on an ALV platform on rural roads online. The experimental results demonstrate the effectiveness of the proposed speed decision-making model.
The Dwarf Spheroidal Galaxies in the Galactic Halo

In the first part of this contribution the observed velocity dispersions in Galactic halo dwarf spheroidal (dSph) galaxies are reviewed , and the consequences for dark matter content outlined. The results are suggestive of a dSph dark matter mass of ∼2×10 7 solar masses, independent of the luminosity of the dSph. Alternatives to the dark matter interpretation are also briefly discussed. In the second part of the contribution the emphasis is on the stellar populations of Galactic dSphs. Recent results for the ages of the oldest populations are presented. These data, together with similar recent results for Galactic halo and LMC globular clusters, indicate that regardless of the subsequent star formation history, the initial epoch of star formation was well synchronized throughout the entire proto-Galactic halo. The implications of the first high dispersion studies of element abundance ratios in Galactic dSph red giants are also discussed. For the Sagittarius dSph in particular, the observed abundance ratios show good agreement with expectations for an episodic star formation history, and such a history is in fact deduced from colour-magnitude diagram studies.