Miracle-dz/UniFAR-FTUs huggingface dataset:
Fitting models for the joint action of two drugs using SAS(R)

Combinations of drugs are increasingly being used for a wide variety of diseases and conditions. A pre‐clinical study may allow the investigation of the response at a large number of dose combinations. In determining the response to a drug combination, interest may lie in seeking evidence of ‘synergism’, in which the joint action is greater than the actions of the individual drugs, or of ‘antagonism’, in which it is less. Two well‐known response surface models representing no interaction are Loewe additivity and Bliss independence, and Loewe or Bliss synergism or antagonism is defined relative to these. We illustrate an approach to fitting these models for the case in which the marginal single drug dose–response relationships are represented by four‐parameter logistic curves with common upper and lower limits, and where the response variable is normally distributed with a common variance about the dose–response curve. When the dose–response curves are not parallel, the relative potency of the two drugs varies according to the magnitude of the desired effect and the models for Loewe additivity and synergism/antagonism cannot be explicitly expressed. We present an iterative approach to fitting these models without the assumption of parallel dose–response curves. A goodness‐of‐fit test based on residuals is also described. Implementation using the SAS NLIN procedure is illustrated using data from a pre‐clinical study. Copyright © 2007 John Wiley & Sons, Ltd.
Perturbation analysis for denumerable Markov chains with application to queueing models

We study the parametric perturbation of Markov chains with denumerable state spaces. We consider both regular and singular perturbations. By the latter we mean that transition probabilities of a Markov chain, with several ergodic classes, are perturbed such that (rare) transitions among the different ergodic classes of the unperturbed chain are allowed. Singularly perturbed Markov chains have been studied in the literature under more restrictive assumptions such as strong recurrence ergodicity or Doeblin conditions. We relax these conditions so that our results can be applied to queueing models (where the conditions mentioned above typically fail to hold). Assuming ν-geometric ergodicity, we are able to explicitly express the steady-state distribution of the perturbed Markov chain as a Taylor series in the perturbation parameter. We apply our results to quasi-birth-and-death processes and queueing models.
Thermodynamic Analysis of the Dissociation of the Aldolase Tetramer Substituted at One or Both of the Subunit Interfaces

Abstract The fructose-1,6-bis(phosphate) aldolase isologous tetramer tightly associates through two different subunit interfaces defined by its 222 symmetry. Both single- and double-interfacial mutant aldolases have a destabilized quaternary structure, but there is little effect on the catalytic activity. These enzymes are however thermolabile. This study demonstrates the temperature-dependent dissociation of the mutant enzymes and determines the dissociation free energies of both mutant and native aldolase. Subunit dissociation is measured by sedimentation equilibrium in the analytical ultracentrifuge. At 25C the tetramerdimer dissociation constants for each single-mutant enzyme are similar, about 10 -6 M. For the double-mutant enzyme, sedimentation velocity experiments on sucrose density gradients support a tetramermonomer equilibrium. Furthermore, sedimentation equilibrium experiments determined a dissociation constant of 10-15 M3 for the double-mutant enzyme. By the same methods the upper limit for the dissociation constant of wild-type aldolase A is approximately 10-28 M3, which indicates an extremely stable tetramer. The thermodynamic values describing monomer-tetramer and dimer-tetramer equilibria are analyzed with regard to possible cooperative interaction between the two subunit interfaces.
The teacher ‘problem’: an analysis of the NSW education policy Great Teaching, Inspired Learning

ABSTRACT This paper seeks to understand the construction of teachers within one New South Wales education policy, querying this construction in relation to both local and international processes and factors. As such, it also looks to contribute to a growing body of international literature which grapples with the role and nature of neoliberal policy development in education more broadly. To accomplish this, the paper analyses Great Teaching, Inspired Learning (GTIL), a policy with wide-ranging and potentially significant ramifications for teachers. Ultimately it is argued that although aspects of neoliberal thinking are evident in the policy, particularities of context have mediated this push. It is suggested that this has led to a particular neoliberalisation of policy that variously targets and supports individual teachers and the systems and structures surrounding them, while the place of GT IL within both local state politics and the global imaginary is questioned.
UNSUPERVISED FILTERING OF COLOR SPECTRA

We describe a class of unsupervised systems that extract features from databases of reflectance spectra that sample color space in a way that reflects the properties of human color perception. The systems find the internal weight coefficients by optimizing an energy function. We describe several energy functions based on second- and fourth-order statistical moments of the computed output values. We also investigate the effects of imposing boundary conditions on the filter coefficients and the performance of the resulting systems for the databases with the reflectance spectra. The experiments show that the weight matrix for one of the systems is very similar to the eigenvector system, whereas the second type of system tries to rotate the eigenvector system in such a way that the resulting filters partition the spectrum into different bands. We also show how the system can be forced to use weight vectors with positive coefficients. Systems consisting of positive weight vectors are then approximated with Gaussian quadrature methods. In the experimental part of the paper we investigate the properties of three databases consisting of reflectance spectra. We compare the statistical structure of the different databases and investigate how these systems can be used to explore the structure of the space of reflectance spectra.
Social Structure and Social Participation

T HIS paper reports the initial findings of a study of participation in the policy formation process at the community level carried out in Valley City I and Valley City II. ' The design of the study involved the development of a scale for measuring community participation and the administering of a basic schedule to a random sample of the adult population in each community in order to identify some of the factors associated with community participation. While this study originated in an interest in social participation as it relates to the policy formation process at the local level, it subsequently became clear that the analysis of participation offers a strategic approach to the study of social structure. The immediate problem with which this paper is concerned is: Who participates to what extent in community affairs and what factors are associated with such participation? However, the more basic problem is concerned with the structural patterns of communities.
Association of serum total cholesterol with coronary disease and all-cause mortality: multivariate correction for bias due to measurement error.

Measurement error in the exposure under investigation is an important but often ignored source of bias in observational studies. The authors examined the impact of measurement error in the association between total serum cholesterol and 16-year coronary heart disease and all-cause mortality in a cohort of 6,137 middle-aged men of Japanese descent in the Honolulu Heart Program (1973-1988). A Cox regression model that enables modeling of survival time with correction for measurement errors in multiple covariates was employed. After controlling for age, body mass index, systolic blood pressure, smoking status, alcohol consumption, dietary cholesterol, and total calorie intake, a difference of one standard deviation (38 mg/dL) in total cholesterol was associated with a significant increase in the risk of coronary disease death (uncorrected hazard ratio = 1.35). After correction for measurement errors in total cholesterol and covariates (except smoking and age), the estimated hazard ratio increased to 1.65 (a 22% increase). A U-shaped relation was observed between total cholesterol levels and the risk of all-cause mortality. This association was then examined with a quadratic model and with a two-slope or V-shaped regression model. In the quadratic fit, the magnitude of the quadratic total cholesterol term increased threefold after the adjustment for measurement error. In the V fit, the hazard ratio of all-cause death corresponding to a change in one standard deviation above 214 mg/dL (the nadir of the V) was 1.15, and increased to 1.49 (by 29%) after the correction. The corresponding hazard ratio of a change in one standard deviation below 214 mg/dL was 1.11, and increased to 1.37 (by 23%) after the correction. The authors conclude that the impact of elevated total cholesterol on the risk of coronary disease and all-cause mortality may be greater than previously estimated with standard methods of analysis. In addition, the correction for measurement error in total cholesterol and covariates did not explain the excess mortality associated with low total cholesterol. More research is needed to elucidate the fundamental issues underlying the U-shaped association, i.e., confounding versus causal implications.
Coordination Games on Dynamical Networks

We propose a model in which agents of a population interacting according to a network of contacts play games of coordination with each other and can also dynamically break and redirect links to neighbors if they are unsatisfied. As a result, there is co-evolution of strategies in the population and of the graph that represents the network of contacts. We apply the model to the class of pure and general coordination games. For pure coordination games, the networks co-evolve towards the polarization of different strategies. In the case of general coordination games our results show that the possibility of refusing neighbors and choosing different partners increases the success rate of the Pareto-dominant equilibrium.
The stability of LDPC codes with higher order modulation schemes

In this paper, we derive stability conditions for low-density-parity-check (LDPC) codes with Gray mapped M-ary phase-shift keying (M-PSK) and M-ary quadrate-amplitude-modulation (M-QAM) constellations. The stability of the LDPC decoder with higher order modulation schemes is examined on both additive-white-Gaussian-noise (AWGN) and block Rayleigh fading channels and threshold stability conditions under iterative decoding are obtained using density evolution techniques. It is shown that both on block Rayleigh fading channel when the ideal channel state information (CSI) of the fading process is known, and on AWGN channel, the stability condition of the underlying code is bounded by the Bhattacharya noise parameter. We show that the derived stability condition is both sufficient and necessary condition for iterative belief propagation decoding assuming cycle free massage passing between variable and check nodes. The evolution of stability condition is assessed as the modulation order is increased for both M-PSK and M-QAM constellations. This study provides an analytical framework to evaluate the performance bounds of LDPC coded systems that extend over higher order modulation schemes.
Functional Interaction between Opioid and Cannabinoid Receptors in Drug Self-Administration

The present study was designed to explore the relationship between the cannabinoid and opioid receptors in animal models of opioid-induced reinforcement. The acute administration of SR141716A, a selective central cannabinoid CB1 receptor antagonist, blocked heroin self-administration in rats, as well as morphine-induced place preference and morphine self-administration in mice. Morphine-dependent animals injected with SR141716A exhibited a partial opiate-like withdrawal syndrome that had limited consequences on operant responses for food and induced place aversion. These effects were associated with morphine-induced changes in the expression of CB1 receptor mRNA in specific nuclei of the reward circuit, including dorsal caudate putamen, nucleus accumbens, and septum. Additionally, the opioid antagonist naloxone precipitated a mild cannabinoid-like withdrawal syndrome in cannabinoid-dependent rats and blocked cannabinoid self-administration in mice. Neither SR141716A nor naloxone produced any intrinsic effect on these behavioral models. The present results show the existence of a cross-interaction between opioid and cannabinoid systems in behavioral responses related to addiction and open new strategies for the treatment of opiate dependence.
Analysis of serial measurements in medical research.

however, it is best that the concentrated necrotising venom is allowed to diffuse freely away from the region. Deaths due to the svstemic effects of the venom are extremely rare, with onlv a couple recorded in published work. Infection often occurs with this type of injury. It should be remembered that marine bacteria comprise a wide range of organisms, and many are resistant to common antibiotics and also may require saline media for culture. It follows that debridement should be assisted by washing the wound well with fresh or preferably sterile water. The drug of first choice is trimethoprim-sulphamethazole. Tetanus prophvlaxis should also receive attention.
Body frame dimensions are related to obesity and fatness: Lean trunk size, skinfolds, and body mass index

We explore relationships between BMI and skinfolds and anthropometric variables reflecting variation in lean body frame. Data on the middle class adult Australian women (n = 1260) collected in 2002 during a National Body Size and Shape Survey were used. Standard measurements of stature, weight, skeletal dimensions (shoulder width, hip width, chest width, and depth, limb lengths), circumferences of head, trunk, limbs and triceps, subscapular and abdominal skinfolds were taken. Techniques for measurements of skeletal frame minimized the inclusion of adipose tissue thickness. Analysis of variance and parametric and nonparametric correlations were used. Vertical dimensions show weak correlations with fatness, while body frame circumferences and transverse dimensions are consistently, significantly, and substantially correlated with fatness, each explaining from 3 to 44% of variation in skinfold thickness. Skeletal dimensions explain up to 50% of variation in skinfold thickness (multiple regression). Especially high correlations with skinfold thickness occur for chest width, depth, and hip width (r range from 0.42 to 0.66). Body frame dimensions reflect largely trunk volume and the trunk/limb proportions. Larger lean trunk size is associated with greater fatness. Since the size of the abdominal cavity, and thus the gastrointestinal system (GI), is reflected in the trunk size, we speculate that larger frame may predispose to obesity in two ways: (1) larger stomachs require greater bulk of food to produce feeling of satiety as mediated through antral distension, (2) larger GIs may absorb more nutrients. Frame size may help to detect the risk of obesity among young adults. Am. J. Hum. Biol. 2010. © 2009 Wiley‐Liss, Inc.
Rectified linear neural networks with tied-scalar regularization for LVCSR

It is known that rectiﬁed linear deep neural networks (RL-DNNs) can consistently outperform the conventional pre-trained sigmoid DNNs even with a random initialization. In this paper, we present another interesting and useful property of RL-DNNs that we can learn RL-DNNs with a very large batch size in stochastic gradient descent (SGD). Therefore, the SGD learning can be easily parallelized among multiple computing units for much better training efﬁciency. Moreover, we also propose a tied-scalar regularization technique to make the large-batch SGD learning of RL-DNNs more stable. Experimental results on the 309-hour Switchboard (SWB) task have shown that we can train RL-DNNs using batch sizes about 100 times larger than those used in the previous work, thus the learning of RL-DNNs can be accelerated by over 10 times when 8 GPUs are used. More importantly, we have achieved a word error rate of 13.8% with a 6-hidden-layer RL-DNN trained by the frame-level cross-entropy criterion with the tied-scalar regularization. To our knowledge, this is the best reported performance on this task under the same experimental settings.
Protein instability during HIC: Hydrogen exchange labeling analysis and a framework for describing mobile and stationary phase effects

Unfolding of marginally stable proteins is a significant factor in commercial application of hydrophobic interaction chromatography (HIC). In this work, hydrogen‐deuterium isotope exchange labeling has been used to monitor protein unfolding on HIC media for different stationary phase hydrophobicities and as a function of ammonium sulfate concentration. Circular dichroism and Raman spectroscopy were also used to characterize the structural perturbations experienced by solution phase protein that had been exposed to media and by protein adsorbed on media. As expected, greater instability is seen on chromatographic media with greater apparent hydrophobicity. However, increased salt concentrations also led to more unfolding, despite the well‐known stabilizing effect of ammonium sulfate in solution. A thermodynamic framework is proposed to account for the effects of salt on both adsorption and stability during hydrophobic chromatography. Using appropriate estimates of input quantities, analysis with the framework can explain how salt effects on stability in chromatographic systems may contrast with solution stability. Biotechnol. Bioeng. 2007;96: 80–93. © 2006 Wiley Periodicals, Inc.
Towards Automatic Stereoscopic Video Synthesis from a Casual Monocular Video

Automatically synthesizing 3D content from a causal monocular video has become an important problem. Previous works either use no geometry information, or rely on precise 3D geometry information. Therefore, they cannot obtain reasonable results if the 3D structure in the scene is complex, or noisy 3D geometry information is estimated from monocular videos. In this paper, we present an automatic and robust framework to synthesize stereoscopic videos from casual 2D monocular videos. First, 3D geometry information (e.g., camera parameters, depth map) are extracted from the 2D input video. Then a Bayesian-based View Synthesis (BVS) approach is proposed to render high-quality new virtual views for stereoscopic video to deal with noisy 3D geometry information. Extensive experiments on various videos demonstrate that BVS can synthesize more accurate views than other methods, and our proposed framework also be able to generate high-quality 3D videos.
Revisiting an Old Question with a New Technology: Gender Differences on a Neuro-Cognitive Temporal Tracking Task

Gender differences exist, but the strength and importance of those differences is debatable. This study examined differences in performance among men (n = 64) and women (n = 56) on 14 neuro-cognitive temporal tasks. No adult norms exist for these tasks. Therefore, the goals were to 1) record and compare scores achieved by men and women, and 2) investigate differences in terms of performance (grade point average and physical fitness score) during Army Health Care Specialist Advanced Individual Training (AIT). Descriptive statistics and t-tests identified and compared scores by gender, while IM scores and performance relationships were explored with Pearson product-moment correlations and regression analysis. Men's temporal responses were closer to the reference beat than women's on 14.3% of tasks (p < 0.05). There were no significant relationships between temporal responses and physical fitness performance scores and only two correlations between temporal responses and grade point average (right hand tapping, Task Average and Super Right On (percent within ±15ms of the target beat) (r = 0.189, p = 0.04; and r = 0.20, p = 0.03). While this research upheld findings of differences between men and women in temporal abilities, the differences did not impact functional performance during AIT.
A Statistics-Based Approach to Fast Performance Evaluation

Although iterative optimization is an effective approach to achieve portable high performance on modern architectures, it takes a lot of time on evaluating the performances of various code versions. This paper proposes a statistics-based approach to accelerate this evaluation process, by testing multiple versions within each execution, so that more points within the target optimization space can be tested in a fixed amount of time. Experimental results are presented to demonstrate the feasibility of this statistics-based approach. It shows that only a few (four to six) samples are needed to accurately evaluate the performance of a given point.
nCap: wire-speed packet capture and transmission

With the increasing network speed, it is no longer possible to capture and transmit network packets at wire-speed using general-purpose operating systems. Many companies tried to tackle this problem by manufacturing costly network adapters able to keep up at high network speeds. This paper describes a new approach to wire-speed packet capture and transmission named nCap based on commercial network adapters rather than on custom network adapters and software.
Enabling Training Personalization by Predicting the Sessioon Rate of Perceived Exertion

In order to achieve optimal gains from training while reducing the risk of negative effects, athletes must perceive an ideal Internal Training Load. This load is invoked by the training content and individual characteristics. Training sessions are often team-based, although each athlete has his/her own characteristics, making it hard for coaching staff to optimize the training load for each athlete individually. In this paper, we propose a methodology for a decision support system that predicts three different sRPE scores: an average group score and an individualized score prior to and after training. This system can be used to personalize training sessions and to follow-up the training in a real-time fashion. We report results on a dataset collected from association football (soccer) players of a Belgian club. The reported results are better than current state-of-the-art from literature in the Australian football domain, with a smaller dataset and less invasive features.
Parenting styles, maternal efficacy, and impact of a childhood disability on the family in mothers of children with disabilities

DISABILITY ON THE FAMILY IN MOTHERS OF CHILDREN WITH DISABILITIES by GWENDOLYN ANNE PUGH (Under the Direction of Zolinda Stoneman) ABSTRACT The purpose of the study was to examine how maternal efficacy and the impact of a childhood disability on the family were related to the mother’s parenting styles. Sixty-eight mothers of children with disabilities were recruited from intervention and educational programs for children with disabilities. Efficacy was positively related to positive parenting styles: induction and nurturance, but was not related to parenting style: power assertion. Efficacy was negatively related to negative cognitive appraisals of the impact of the childhood disability. Positive cognitive appraisals were positively related to parenting style: induction, but were not related to parenting style: nurturance and power assertion. Negative cognitive appraisals were not related to parenting. The results of the study allow professionals working with populations of children with disabilities and their mothers to better understand various contributors of parenting styles.