Miracle-dz/UniFAR-FTUs huggingface dataset:
A note on the conservativeness of the confidence interval approach for the selection of non‐inferiority margin in the two‐arm active‐control trial

Compared with placebo‐control clinical trials, the interpretation of efficacy results from active‐control trials requires more caution. This is because efficacy results from such trials cannot be reliably interpreted without a thorough understanding of the efficacy evidence that formed the basis for the approval of the active control, especially when such drug efficacy is to be established on the basis of clinical evidence from the traditional two‐arm active‐control clinical equivalence studies as opposed to the multi‐arm active control. This is because in addition to over‐reliance on the quantification of a clinically irrelevant acceptable margin of inferiority from historical data, such interpretation also depends on cross‐trial inference for demonstration of experimental drug effect. We provide a brief overview of some design issues with the traditional two‐arm active‐control clinical trial and discuss regulators' concern regarding Type I error rate control (with the two most popular methods for the quantification of the non‐inferiority margin) in cross‐trial demonstration of experimental drug effect. Simulation results are presented to show that the point estimate method provides adequate control of the Type I error rate with ⩾75 per cent retention of known active‐control effect and that the confidence interval approach is uniformly ultra‐conservative. We also report (via a numerical example from real clinical trial data) a couple of potentially less stringent alternative approaches for establishing the non‐inferiority of a test drug over a control, which have been used in the past to provide additional efficacy evidence in NDA submission. Copyright © 2008 John Wiley & Sons, Ltd.
Identifying significant covariates for anti‐HIV treatment response: Mechanism‐based differential equation models and empirical semiparametric regression models

In this paper, the mechanism‐based ordinary differential equation (ODE) model and the flexible semiparametric regression model are employed to identify the significant covariates for antiretroviral response in AIDS clinical trials. We consider the treatment effect as a function of three factors (or covariates) including pharmacokinetics, drug adherence and susceptibility. Both clinical and simulated data examples are given to illustrate these two different kinds of modeling approaches. We found that the ODE model is more powerful to model the mechanism‐based nonlinear relationship between treatment effects and virological response biomarkers. The ODE model is also better in identifying the significant factors for virological response, although it is slightly liberal and there is a trend to include more factors (or covariates) in the model. The semiparametric mixed‐effects regression model is very flexible to fit the virological response data, but it is too liberal to identify correct factors for the virological response; sometimes it may miss the correct factors. The ODE model is also biologically justifiable and good for predictions and simulations for various biological scenarios. The limitations of the ODE models include the high cost of computation and the requirement of biological assumptions that sometimes may not be easy to validate. The methodologies reviewed in this paper are also generally applicable to studies of other viruses such as hepatitis B virus or hepatitis C virus. Copyright © 2008 John Wiley & Sons, Ltd.
Is Mendelian randomization ‘lost in translation?’: Comments on ‘Mendelian randomization equals instrumental variable analysis with genetic instruments’ by Wehby et al.

Wehby et al. suggest that researchers use the term ‘instrumental variable analysis with genetic instruments’ rather than ‘Mendelian randomization’ for studies that use genetic variants that proxy for modifiable risk factors to investigate the causal effects of these risk factors [1]. They state that ‘Using common language between disciplines applying IV analysis with genetic variants is essential to increasing collaborations and fostering the application of this method’ [1]. However, we would argue that truly translational research requires direct collaboration between individuals from different disciplines, clear definitions of discipline-specific terminology and the willingness to learn from each other. Any attempts to develop a common language must reflect this reality and may be less important than being able to translate between disciplines. In the limited context of ‘Mendelian randomization’ developing the necessary multidisciplinary approach clearly goes well beyond the term used to describe these studies. What is required is capitalizing on the insights that all disciplines can bring and not arguing over which discipline should be the one with terminological hegemony. It is notable, for example, that throughout their commentary Wehby et al. refer to ‘endogenous’ variables, without any explanation of this term in language that would be understood by clinicians, epidemiologists, geneticists, basic scientists or indeed many biomedical statisticians for whom this term will be unknown. Similarly, they use the term ‘direct’ where most epidemiologists and clinicians would specify ‘causal’ (the latter also having a clearer understanding for lay readers of research). Others have also suggested alternative terms for ‘Mendelian randomization’ including ‘Mendelian deconfounding’ [2] and ‘Mendelian triangulation’ [3], so which name should be given prominence? We are not particularly committed to the name ‘Mendelian randomization’ and have discussed the origin of this term in previous publications [4, 5]. However, it is now recognized
Joint modelling of longitudinal and competing risks data

Available methods for joint modelling of longitudinal and survival data typically have only one failure type for the time to event outcome. We extend the methodology to allow for competing risks data. We fit a cause‐specific hazards sub‐model to allow for competing risks, with a separate latent association between longitudinal measurements and each cause of failure.
How to evaluate the calibration of a disease risk prediction tool

To evaluate the calibration of a disease risk prediction tool, the quantity E/O, i.e. the ratio of the expected to the observed number of events, is usually computed. However, because of censoring, or more precisely because of individuals who drop out before the termination of the study, this quantity is generally unavailable for the complete population study and an alternative estimate has to be computed. In this paper, we present and compare four methods to do this. We show that two of the most commonly used methods generally lead to biased estimates. Our arguments are first based on some theoretic considerations. Then, we perform a simulation study to highlight the magnitude of biases. As a concluding example, we evaluate the calibration of an existing predictive model for breast cancer on the E3N–EPIC cohort. Copyright © 2009 John Wiley & Sons, Ltd.
Whole Genome Analysis by Array-Based Comparative Genomic Hybridization in Patients with Congenital Malformations

Whole Genome Analysis by Array-Based Comparative Genomic Hybridization in Patients with Congenital Malformations Congenital malformations present at delivery of an infant are due to genetic or non genetic factors and occur in 15-20% of stillborn children. Most can be diagnosed prenatally by ultrasound examination, but some can only be diagnosed after birth. Seven to 10% of infants with abnormal phenotype have numerical or structural chromosomal abnormalities that require identification for accurate diagnosis and genetic counseling. Molecular-cytogenetic and array-based techniques have enabled screening at higher resolution for congenital anomalies that result from genomic imbalances. We have examined four children with congenital anomalies, with or without mental retardation, of unclear etiology. In one child, we detected a deletion (about 28 Mb) of the region 18q21.1-18q23, in mosaic form. This abnormality was missed in a routine cytogenetic examination. We detected different polymorphic copy number variations (CNVs) in the other children. We conclude that array-based comparative genomic hybridization (CGH) is a powerful diagnostic tool for the detection of low level mosaicism.
Estimating regional centile curves from mixed data sources and countries

Regional or national growth distributions can provide vital information on the health status of populations. In most resource poor countries, however, the required anthropometric data from purpose‐designed growth surveys are not readily available. We propose a practical method for estimating regional (multi‐country) age‐conditional weight distributions based on existing survey data from different countries. We developed a two‐step method by which one is able to model data with widely different age ranges and sample sizes. The method produces references both at the country level and at the regional (multi‐country) level. The first step models country‐specific centile curves by Box–Cox t and Box–Cox power exponential distributions implemented in generalized additive model for location, scale and shape through a common model. Individual countries may vary in location and spread. The second step defines the regional reference from a finite mixture of the country distributions, weighted by population size. To demonstrate the method we fitted the weight‐for‐age distribution of 12 countries in South East Asia and the Western Pacific, based on 273 270 observations. We modeled both the raw body weight and the corresponding Z score, and obtained a good fit between the final models and the original data for both solutions. We briefly discuss an application of the generated regional references to obtain appropriate, region specific, age‐based dosing regimens of drugs used in the tropics. The method is an affordable and efficient strategy to estimate regional growth distributions where the standard costly alternatives are not an option. Copyright © 2009 John Wiley & Sons, Ltd.
Lead, Arsenic, and Cadmium Contamination and Its Impact on Children's Health in La Oroya, Peru

The large scale of nonferrous metal smelting has created a chronic public health issue in La Oroya, Peru. In this reconnaissance study, the distributions of lead, arsenic, and cadmium in drinking water, indoor dust, and soil were measured at five sites to estimate their impact on children's health. As expected, median soil metal levels dropped exponentially with distance from the smelting complex (3,177 ppm Pb, 1,658 ppm As, and 127 ppm Cd at La Oroya Antigua). Indoor dust metal concentrations were also elevated at La Oroya Antigua (2,574 ppm Pb, 1,071 ppm As, 28 ppm Cd), and drinking water As values were elevated relative to Pb and Cd (8.5 ppb As, 0.28 ppb Pb, and 0.05 ppb Cd), suggesting selective loss of Pb and Cd relative to As. Exposure and dose-response modeling (IEUBK) indicate soil Pb and As are serious health problems in need of remediation.
The handwriting problem [man-machine motion analogy in robotics]

Two approaches are proposed to model and control a human-like motion of robot arms. The first, which is based on the concept of distributed positioning (DP), is suggested as a good model of arm motion in the phase where fatigue does not appear. The prescribed motion of the end-effector is distributed to a redundant number of arm joints in accordance to their acceleration capabilities. For the phase where fatigue appears, the concept of virtual fatigue is proposed. This artificial variable, which is based on robot dynamics, emulates the progress of biological fatigue. The human handwriting task is chosen for the simulation. The DP concept is tested first by modeling nonfatigued motion. The justification of the usual inclination of letters is presented, and the relation between the inclination, legibility, and a secondary objective (finger involvement, energy consumption, motor thermal load) is discussed. It is found that, for some prescribed level of legibility, the individual optima of all the secondary cost functions are quite near to each other. Writing in the presence of fatigue is also analyzed, applying the method of the so-called "virtual fatigue".
Toward the Integration of Prevention Research and Expanded School Mental Health Programs

Expanded school mental health (ESMH) programs provide comprehensive mental health care (assessment, treatment, case management) to youth in special and regular education in schools. These programs are growing progressively throughout the United States related to increasing disenchantment with traditional forms of mental health service delivery to youth (e.g., providing care at "centers" away from neighborhoods) and growing recognition of the advantages of providing services directly within schools (e.g., outreach to youth with internalizing disturbances). However, for the most part, prevention within ESMH programs remains underdeveloped. The integration of prevention research and ESMH offers considerable promise to ongoing efforts to reform and improve education and mental health care for youth. This article reviews barriers to this integration and strategies to overcome them.
Field and service applications - Automating the marking process for exhibitions and fairs - The Making of Harry Platter

Trade fairs and exhibitions have been around for centuries. They provide an important meeting point for sellers and potential buyers, be it for cars or clothes. Some fair organizers partition the exhibition space into predefined units, which may limit the flexibility. A free layout of the space allows for any shape or size of the stands and gives the exhibitor a better chance at creating something spectacular that will attract attention. Providing full flexibility, and thus a free layout, means that every new fair will be different. In addition to each individual stand having a varying size, the shape is not constrained to be rectangular, but might be, e.g., triangular or elliptic. All of this puts high demands on the production of the fairs. For example, the location and outline of every stand has to be determined and marked on the floor before the construction phase. This article gives a real world example of how robot technology can be used to automate the marking process for exhibitions and fairs in a way that both reduces the marking time and improves the working conditions. A mobile robot system equipped with a laser scanner and an ink jet printer is presented. The focus of the article is the description of the marking process and the system design. In addition, the requirements for such a system are outlined as well as results from over three years of operation and an analysis for commercialization.
Radiofrequency ablation of the great saphenous vein, comparing one versus two treatment cycles for the proximal vein segment

Objective To evaluate the results of radiofrequency ablation (RFA) of the great saphenous vein (GSV) using one versus two 20 s energy cycle treatment in the proximal 7 cm segment of the GSV. Methods All patients who underwent RFA of the GSV from 1 May 2013 to 30 September 2013 in eight of our vein centers were included. Duplex ultrasound scans (DUSs) were performed prior to treatment on all patients and 2–3 days, and 1 month after procedure. Demographic data, GSV diameters, and other relevant data were recorded. Clinical, Etiologic, Anatomic, Pathologic (CEAP) classification and Venous Clinical Severity Scores (VCSSs) were determined prior to ablation and one month later. Patients who developed endovenous heat induced thrombosis (EHIT) were followed till resolution. Results A total of 205 patients had one cycle treatment (group A) and 204 had two cycle treatment (group B). The two groups were comparable in their demography, CEAP classification, and VCSS scores. The rate of failure of ablation and incidence of EHIT were also not significantly different. The incidence of complications was low, <5% in both groups and all were minor. Conclusion Two cycle treatment of the proximal GSV for vein ablation does not improve the success rate of vein closure in the short term, compared to one cycle treatment. It also does not increase the risks of DVT, EHIT, major bleeding, and other complications. However, we do not know at what diameter two cycles may be superior to one cycle.
A comparison of laboratory-based kayak testing protocols.

PURPOSE To compare the differences in peak oxygen uptake (VO2peak) and lactate threshold (LT2) between the 7 × 4-min incremental step test (7-ST) and the maximal accumulated oxygen deficit (MAOD) test protocols in sprint kayak athletes. METHODS Nine highly trained kayak athletes performed the 2 laboratory test protocols. The 7-ST involved six 4-min submaximal incremental stages, each separated by a 1-min recovery, before a 4-min all-out effort. The MAOD test involved four 4-min submaximal incremental stages (also with each stage separated by a 1-min recovery), followed by 20-min recovery and a 4-min all-out effort. RESULTS No statistically significant differences in VO2peak were recorded between the 2 protocols (P > .05). However, distance covered, power output, stroke rate, and speed were almost certainly greater in the MAOD test (magnitude-based inference: 99-100% positive), while blood lactate (BLa), heart rate (HR), and rating of perceived exertion (RPE) were likely lower (magnitude-based inference: 78-92% negative). The derived measures of LT2 (excluding HR) were not different between the 2 protocols. CONCLUSION The results of this study suggest that both the 7-ST and MAOD test protocols are comparable with regard to the measurement of VO2peak and LT2 in highly trained sprint kayak athletes. However, since differences in the measures of distance traveled, power, stroke rate, HR, BLa, and RPE were reported in the maximal stage of the these 2 test protocols, their interchangeable use in a laboratory setting is not ideal if the data output is to be compared and contrasted over time.
Comments on ‘A note on the power prior’ by Neuenschwander B, Branson M and Spiegelhalter DJ. Statistics in Medicine; DOI: 10.1002/sim.3722

Neuenschwander et al. [1] provide an important note on properly calculating the posterior distribution of a0, the weight used to discount historical data in the analysis of a clinical trial. The authors claim that some of the literature calculates this posterior incorrectly because of its use of the wrong normalizing constant. The authors demonstrate their idea using a binomial model on combined current and historical data. They were able to show that improper application leads to posterior distributions of a0 with lower means and more narrow 95 per cent credible intervals. Interestingly, Lunn et al. [2] recently evaluated the widely successful Bayesian software BUGS. It appears that another notch on the belt of BUGS is its ability to properly calculate the posterior distribution a0. Consider the WinBUGS code shown in Figure for Scenario 1 from Reference [1]. After 1000 burn-in and 10 000 post burn-in samples we have reproduced the last column of Table I from Reference [1] with almost exact agreement (Figure 1).
Model predictive driver assistance control for cooperative cruise based on hybrid system driver model

This paper presents a driver assisting system for cooperative cruising of multiple cars. In order to account for personal difference of individual drivers, each driver's vehicle following skill on expressways is identified as a PrARX model, a continuous approximation of hybrid dynamical system. The PrARX model describes the driver's logical decision making as well as continuous maneuvering in a uniform manner. The assisting acceleration is computed in the framework of model predictive control, where the plant model is a platoon of cars coupled with PrARX driver models. For computing assisting outputs in real time, a fast computation method for nonlinear model predictive control based on the continuation technique is employed. The proposed assisting system is tested in numerical simulations and on a driving simulator with a real human driver. The high speed calculation of the Homotopy method is also proved by comparison to the conventional method. Finally, the advantage of global optimization for cooperative safety is confirmed by comparing its control performance with the local optimization for individual safety.
How good is bad weather?

Accurately identifying key parameters in complex systems demands sufficient excitation, so that the resulting data will be informative enough to reveal hidden parameter values. In many situations, however, users choose inputs that attempt to optimize the system response, not necessarily those that yield more informative data. This leads to the classic tradeoff between exploitation and exploration in learning problems. Farmers face a similar issue. Although they would like to identify key soil parameters affecting the growth of their crops, market pressures force them to manage their product to maximize yield, resulting in less informative data. This suggests that weather, and bad weather in particular, may play a critically important role in creating informative data for crop systems by driving them into low-yield regimes that no farmer would otherwise choose to explore. This paper investigates these issues using a standard computational model for corn and real weather data. Two model-based measures characterizing any year's weather pattern are introduced. The first measure characterizes how well a particular year's weather pattern produces corn, according to the model. The second measure characterizes how well a particular year's weather pattern distinguishes the way different soil types affect corn growth. We then use these measures to show that, from the perspective of corn, bad weather can indeed be very good for distinguishing soil type.
Dose‐response analyses using restricted cubic spline functions in public health research

Taking into account a continuous exposure in regression models by using categorization, when non‐linear dose‐response associations are expected, have been widely criticized. As one alternative, restricted cubic spline (RCS) functions are powerful tools (i) to characterize a dose‐response association between a continuous exposure and an outcome, (ii) to visually and/or statistically check the assumption of linearity of the association, and (iii) to minimize residual confounding when adjusting for a continuous exposure. Because their implementation with SAS® software is limited, we developed and present here an SAS macro that (i) creates an RCS function of continuous exposures, (ii) displays graphs showing the dose‐response association with 95 per cent confidence interval between one main continuous exposure and an outcome when performing linear, logistic, or Cox models, as well as linear and logistic‐generalized estimating equations, and (iii) provides statistical tests for overall and non‐linear associations. We illustrate the SAS macro using the third National Health and Nutrition Examination Survey data to investigate adjusted dose‐response associations (with different models) between calcium intake and bone mineral density (linear regression), folate intake and hyperhomocysteinemia (logistic regression), and serum high‐density lipoprotein cholesterol and cardiovascular mortality (Cox model). Copyright © 2010 John Wiley & Sons, Ltd.
Humanoid robotics

With a physical form similar to that of a human, humanoid robots can be used as proxies or assistants to perform tasks in a real-world environment on behalf of humans. Various humanoid robots have been developed worldwide, and currently, humanoid robots are able to work in our daily life environment. This paper introduces some of the ongoing research and development of humanoid, and discusses the problems, approaches and applications for the next generation humanoid.