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Background. The aim of this study was to compare shoulder movement measurements between a Kinect-based markerless ROM assessment device (POM-Checker) and a 3D motion capture analysis system (BTS SMART DX-400). Methods. This was a single-visit clinical trial designed to evaluate the validity and reliability of the POM-Checker. The primary outcome was to assess the equivalence between two measurement devices within the same set of participants, aiming to evaluate the validity of the POM-Checker compared to the gold standard device (3D Motion Analysis System). As this was a pilot study, six participants were included. Results. The intraclass correlation coefficient (ICC) and the corresponding 95% confidence intervals (CIs) were used to assess the reproducibility of the measurements. Among the 18 movements analyzed, 16 exhibited ICC values of >0.75, indicating excellent reproducibility. Conclusion. The results showed that the POM-checker is reliable and validated to measure the range of motion of the shoulder joint. [ABSTRACT FROM AUTHOR]

Tropical cyclones are the world's deadliest natural disasters, especially causing tree death by pulling out or breaking the roots of trees, which has a great impact on the forest ecosystem and forest owners. To minimize additional damage, an efficient approach is needed to quickly grasp information on the location and distribution of fallen trees. There are several studies that try to detect fallen trees in the past, but most of the research requires huge costs and is difficult to utilize. This research focuses on resolving those problems. Unmanned aerial vehicle (UAV) is widely used for ground detection for those who need a cost-effective way while pursuing high-resolution images. To take this advantage, this research collects data mainly using a UAV with an auxiliary high-resolution camera. The collected data is used for training the YOLOX model, an object detection algorithm, which can perform an accurate detection within a remarkably short time period. Also, by using YOLOX as a detection model, a wide-range versatility is obtained, which means, the solution driven by this research can be utilized for every scenario where inexpensive, but highly reliable object detection result is needed. This research implements a visualization application that displays detection results, calculated by a trained model, in a client-friendly way. Fallen trees are recognized in images or videos, and the analyzed results are provided as web-based visualizations. [ABSTRACT FROM AUTHOR]

In an aging society in the world, dementia that leads to pain in patients and their families has become a common disease in our lives. Among dementia, Alzheimer's disease (AD) is the most commonly shown disease. Various causes of the disease have been proposed and amyloid hypothesis insists that the toxic amyloid‐β (Aβ) species could be the major risk factor of the onset and progression of AD. In this perspective, clearance of Aβ species from the brain by regulating the activity of amyloid degrading enzymes (ADE), including neprilysin and matrix metalloproteinases, could be a potent treatment for AD. Therefore, the structures and functions of these enzymes along with biological molecules in the brain would be important to understand the pathogenesis of AD and develop an effective medication for the disease. In this review, multiple ADE with biological molecules which could affect the activities and/or expression of the enzymes are summarized. [ABSTRACT FROM AUTHOR]

Magnetic resonance imaging (MRI) plays a significant role in the diagnosis of lumbar disc disease. However, the use of MRI is limited because of its high cost and significant operating and processing time. More importantly, MRI is contraindicated for some patients with claustrophobia or cardiac pacemakers due to the possibility of injury. In contrast, computed tomography (CT) scans are much less expensive, are faster, and do not face the same limitations. In this paper, we propose a method for estimating lumbar spine MR images based on CT images using a novel objective function and a dual cycle-consistent adversarial network (DC 2 Anet) with semi-supervised learning. The objective function includes six independent loss terms to balance quantitative and qualitative losses, enabling the generation of a realistic and accurate synthetic MR image. DC 2 Anet is also capable of semi-supervised learning, and the network is general enough for supervised or unsupervised setups. Experimental results prove that the method is accurate, being able to construct MR images that closely approximate reference MR images, while also outperforming four other state-of-the-art methods. [ABSTRACT FROM AUTHOR]

High-throughput technologies enable the simultaneous evaluation of thousands of genes that could discriminate different subclasses of complex diseases. Ranking genes according to differential expression is an important screening step for follow-up analysis. Many statistical measures have been proposed for this purpose. A good ranked list should provide a stable rank (at least for top-ranked gene), and the top ranked genes should have a high power in differentiating different disease status. However, there is a lack of emphasis in the literature on ranking genes based on these two criteria simultaneously. To achieve the above two criteria simultaneously, we proposed to apply a previously reported metric, the modified area under the receiver operating characteristic cure, to gene ranking. The proposed ranking method is found to be promising in leading to a stable ranking list and good prediction performances of top ranked genes. The findings are illustrated through studies on both synthesized data and real microarray gene expression data. The proposed method is recommended for ranking genes or other biomarkers for high-dimensional omics studies. [ABSTRACT FROM AUTHOR]

The main purpose of this article is to explore the use of movies (i.e., cinematherapy) as a recreation therapy intervention tool. This paper begins with literature review regarding the concepts and origin of cinematherapy and introduces cinematherapy as a viable intervention option as in recreation therapy or other clinical settings. The authors provide detailed guidelines for the process of cinematherapy sessions and other practical recommendations and considerations for incorporating cinematherapy into recreation therapy practice. Guided sample questions for the debriefing stages are illustrated and lastly, examples of movies that can be used in cinematherapy suggested by recreation therapists. [ABSTRACT FROM AUTHOR]

Penalized logistic regression is useful for classification that not only provides class probability estimates but also can overcome overfitting problem. Traditionally, supervised classifier learning has required a lot of labeled data. Due to technical innovation, it is easy to collect large amounts of unlabeled data, while labeling is usually expensive and difficult. Active learning aims to select the most informative subjects for labeling to decrease the amount of labeling requests. Recently, active learning using experimental design techniques have attracted considerable attention. The typical criteria attempt to reduce the generalization error of a model by minimizing either its estimation variance or estimation bias. However, they fail to take into account both components simultaneously. In this article, we introduce a new algorithm of active learning using penalized logistic regression. The most informative subjects are selected as those with the smallest mean squared estimation error. This criterion, integrated with the idea of sequential design, is exploited in our algorithms to guide a procedure for a new subject selection. Experiments on extensive real-world data sets demonstrate the effectiveness and efficiency of the proposed method compared to several state-of-the-art active-learning alternatives. [ABSTRACT FROM AUTHOR]

A class of optimal covariate-adjusted response adaptive procedures is developed for phase III clinical trials when the treatment response is a survival time and there is random censoring. The basic aim is to develop an allocation design by combining the ethical aspects with statistical precision in a reasonable way under the presence of covariate information. Considering minimisation of total hazards as the ethical requirement, the proposed procedure is assessed in terms of the assignment to the better treatment and the efficiency (i.e. power) to detect a small departure in treatment effectiveness. The applicability of the proposed methodology is also illustrated using a real data set. [ABSTRACT FROM AUTHOR]

Covariate-adjusted response-adaptive (CARA) design becomes an important statistical tool for evaluating and comparing the performance of treatments when targeted medicine and adaptive therapy become important medical innovations. Due to the nature of the adaptive therapies of interest and how subjects accrue to a sampling procedure, it is of interest how to control the sample size sequentially such that the estimates of treatment effects have satisfactory precision in addition to its asymptotic properties. In this paper, we apply a multiple-stage sequential sampling method to CARA design in such a way that the control of the sample size is more feasible. The theoretical properties of the proposed method, including the estimates of regression parameters and the allocation probabilities under this randomly stopped sampling procedure, are discussed. The numerical results based on synthesized data and a real example are presented. [ABSTRACT FROM AUTHOR]

In this study, we investigated the potential utility of fish skin, usually discarded during processing, as a cost-effective protein source. We evaluated the effects on juvenile black rockfish ( Sebastes schlegeli) of an 8-week feeding trial in which 0%, 5%, 10% or 20% of the casein (purified protein) in their diets was replaced with flounder skin meal. The fish that received flounder skin meal, particularly the 20% group, showed significantly higher growth performance and feeding efficiency. They had lower levels of body lipids, elevated levels of high-density lipoprotein cholesterol, and increased body and muscle protein contents. They recovered more rapidly from stress induced by anaesthesia or exposure to air. Supplementation with flounder skin meal confirms the functionality of flounder skin meal as a high collagen component of fish diets. [ABSTRACT FROM AUTHOR]

The area under the receiver operating characteristic (ROC) curve (AUC) is a popularly used index when comparing two ROC curves. Statistical tests based on it for analyzing the difference have been well developed. However, this index is less informative when two ROC curves cross and have similar AUCs. In order to detect differences between ROC curves in such situations, a two-stage nonparametric test that uses a shifted area under the ROC curve (sAUC), along with AUCs, is proposed for paired designs. The new procedure is shown, numerically, to be effective in terms of power under a wide range of scenarios; additionally, it outperforms two conventional ROC-type tests, especially when two ROC curves cross each other and have similar AUCs. Larger sAUC implies larger partial AUC at the range of low false-positive rates in this case. Because high specificity is important in many classification tasks, such as medical diagnosis, this is an appealing characteristic. The test also implicitly analyzes the equality of two commonly used binormal ROC curves at every operating point. We also apply the proposed method to synthesized data and two real examples to illustrate its usefulness in practice. [ABSTRACT FROM PUBLISHER]

Response-adaptive designs have become popular for allocation of the entering patients among two or more competing treatments in a phase III clinical trial. Although there are a lot of designs for binary treatment responses, the number of designs involving covariates is very small. Sometimes the patients give repeated responses. The only available response-adaptive allocation design for repeated binary responses is the urn design by Biswas and Dewanji [Biswas A and Dewanji AA. Randomized longitudinal play-the-winner design for repeated binary data. ANZJS 2004; 46: 675–684; Biswas A and Dewanji A. Inference for a RPW-type clinical trial with repeated monitoring for the treatment of rheumatoid arthritis. Biometr J 2004; 46: 769–779.], although it does not take care of the covariates of the patients in the allocation design. In this article, a covariate-adjusted response-adaptive randomisation procedure is developed using the log-odds ratio within the Bayesian framework for longitudinal binary responses. The small sample performance of the proposed allocation procedure is assessed through a simulation study. The proposed procedure is illustrated using some real data set. [ABSTRACT FROM PUBLISHER]

From 1996 onward, a pandemic spread of Vibrio parahaemolyticus infections due to one clone has been reported in several Asian countries. During a population-based study that relied on passive surveillance, 548 cases of V. parahaemolyticus infection were detected between 1997 and 1999 in the Khanh Hoa province of Vietnam. Detection of cases of V. parahaemolyticus infection abruptly stopped in November 1999, although Vibrio species other than V. parahaemolyticus continued to be isolated throughout 2000. Of the infections, 90% occurred in individuals >5 years old; 53% of the patients presented with watery stools, and 6% reported blood in their stools. All patients had recovered by the time of discharge. A surprising risk factor for V. parahaemolyticus infections was high socioeconomic status. Like the interruption of the transmission of V. cholerae infections that had been observed earlier, the transmission of V. parahaemolyticus came to a halt without meteorological changes or changes in water supply and sanitation. [ABSTRACT FROM AUTHOR]

We consider the problem of estimating the standard deviation of the Fisher-transformed Spearman's rank correlation coefficient between two random variables X and Y when both or either of them is serially correlated. When X or Y is not i.i.d., Efron's bootstrap (EB) and the jackknife fail to capture the autocorrelation structure in the data. The circular block bootstrap (CBB) and the stationary bootstrap (SB) can be applied as alternative nonparametric resampling schemes for stationary time series. When we can assume a time series regression model, we can apply the parametric bootstrap (PB) and the bootstrap of residuals from the model (RB) to estimate the standard deviation. We compare these six methods—EB, the jackknife, CBB, SB, PB, and RB—of estimating the standard deviation, using the simulated data which have a highly correlated first order autoregression model. As we expect, the conventional bootstrap and the jackknife perform most poorly, and the PB and RB taking into account the time series model structure are the best in bias and mean squared errors. When estimating the standard deviation of the untransformed Spearman's rank correlation, we observe a very similar result. [ABSTRACT FROM AUTHOR]

Magnetic resonance (MR) imaging plays a highly important role in radiotherapy treatment planning for the segmentation of tumor volumes and organs. However, the use of MR is limited, owing to its high cost and the increased use of metal implants for patients. This study is aimed towards patients who are contraindicated owing to claustrophobia and cardiac pacemakers, and many scenarios in which only computed tomography (CT) images are available, such as emergencies, situations lacking an MR scanner, and situations in which the cost of obtaining an MR scan is prohibitive. From medical practice, our approach can be adopted as a screening method by radiologists to observe abnormal anatomical lesions in certain diseases that are difficult to diagnose by CT. The proposed approach can estimate an MR image based on a CT image using paired and unpaired training data. In contrast to existing synthetic methods for medical imaging, which depend on sparse pairwise-aligned data or plentiful unpaired data, the proposed approach alleviates the rigid registration of paired training, and overcomes the context-misalignment problem of unpaired training. A generative adversarial network was trained to transform two-dimensional (2D) brain CT image slices into 2D brain MR image slices, combining the adversarial, dual cycle-consistent, and voxel-wise losses. Qualitative and quantitative comparisons against independent paired and unpaired training methods demonstrated the superiority of our approach. [ABSTRACT FROM AUTHOR]

In biomedical research, researchers frequently use statistical procedures such as the t-test, standard analysis of variance (ANOVA), or the repeated measures ANOVA to compare means between the groups of interest. There are frequently some misuses in applying these procedures since the conditions of the experiments or statistical assumptions necessary to apply these procedures are not fully taken into consideration. In this paper, we demonstrate the correct use of repeated measures ANOVA to prevent or minimize ethical or scientific problems due to its misuse. We also describe the appropriate use of multiple comparison tests for follow-up analysis in repeated measures ANOVA. Finally, we demonstrate the use of repeated measures ANOVA by using real data and the statistical software package SPSS (SPSS Inc., USA).

From 1996 onward, a pandemic spread of Vibrio parahaemolyticus infections due to one clone has been reported in several Asian countries. During a population-based study that relied on passive surveillance, 548 cases of V. parahaemolyticus infection were detected between 1997 and 1999 in the Khanh Hoa province of Vietnam. Detection of cases of V. parahaemolyticus infection abruptly stopped in November 1999, although Vibrio species other than V. parahaemolyticus continued to be isolated throughout 2000. Of the infections, 90% occurred in individuals >5 years old; 53% of the patients presented with watery stools, and 6% reported blood in their stools. All patients had recovered by the time of discharge. A surprising risk factor for V. parahaemolyticus infections was high socioeconomic status. Like the interruption of the transmission of V. cholerae infections that had been observed earlier, the transmission of V. parahaemolyticus came to a halt without meteorological changes or changes in water supply and sanitation.