Miracle-dz/UniFAR-FTUs huggingface dataset:
Is cardiorespiratory fitness independently associated with the biochemical profile in overweight/obese adults with primary hypertension? The EXERDIET-HTA study

Abstract Cardiorespiratory fitness (CRF) is positively associated with enhanced cardiovascular health. This cross-sectional study aimed to determine associations between CRF and the biochemical profile of overweight/obese adults diagnosed with primary hypertension (HTN). Does cardiorespiratory fitness (exposure) positively affect the biochemical profile (outcome) in overweight/obese individuals suffering from HTN? Assessment with anthropometric, ambulatory blood pressure monitoring (24 h), CRF (peak oxygen uptake, V̇O2peak) and biochemical analysis was performed on 214 participants (138 men, 76 women). A series of linear and logistic regression analyses were conducted. Participants were divided into CRF tertiles (classified as low, moderate and high CRF). The CRF was independently and inversely associated with aspartate aminotransferase (AST; β = −0.328, p < .05) and alanine aminotransferase (ALT; β = −0.376, p < .01) concentrations. C-reactive protein, AST/ALT ratio, gamma-glutamyl transpeptidase, total cholesterol/high-density lipoprotein cholesterol ratio, glucose, insulin and insulin resistance index (HOMA-IR), were all associated, but not independently, with CRF in linear and/or unadjusted logistic regression models. However, independently, logistic regression revealed that glucose was associated with the moderate CRF group. Findings suggest that a lower CRF is associated with an unhealthy biochemical profile in non-physically active and overweight/obese individuals with HTN. As such, this population should look to increase physical activity in order to improve their CRF and biochemical profile.
Capripoxvirus antibodies detection: Relationship between the two methods alpha and beta of virus neutralisation test

Virus neutralisation test (VNT) of capripoxvirus (CaPVs) was studied to assess the post-vaccination (vaccine effectiveness) or post-infection antibodies level using two methods: alpha-VNT and beta-VNT which are generally carried out to measure the Neutralising Index (N.I.) and the serum Antibody titre (TAb) respectively. The authors have demonstrated that a positive correlation exists between N.I. and TAb values, this study aimed to add more evidence to this correlation by establishing a graph and its mathematical equations. We found that: N.I. = (1.489 Log TAb) + 1.331; this serves as a base to calculate N.I. using TAb values measured by beta-VNT without going through alpha-VNT and vice versa. At the end of this study, we evaluated the equation accuracy by two parameters; the deviation (d) and the error percentage, which were d = 0.2 and error (%) = 8%, respectively.
Fabrication-Tolerant AFSIW Filters Based on Quadruplet Through-Hole Mounted Inductive Posts

In this paper, air-filled substrate integrated waveguide (AFSIW) bandpass filters based on quadruplet through-hole mounted inductive posts are proposed and demonstrated. First, a comparison between the conventional inductive iris coupling and the inductive post coupling is introduced. Both geometries are compared in terms of performances and fabrication tolerance. A Monte Carlo analysis shows that printed circuit board (PCB) drilling process is more accurate than machining process. Then, a study on the internal coupling based on single inductive post is compared with its counterpart based on quadruplet inductive posts. For demonstration purposes, a fourth-order bandpass filter centered at 21 GHz with 1.4 % relative bandwidth is synthesized and fabricated. It achieves a −19 dB return loss with a −0.73 dB insertion loss. The calculated unloaded quality factor of the prototyped bandpass filter is 1594. This fabrication-tolerant topology is of high interest for future systems on substrate. The proposed low-cost and manufacturing tolerant filter structure is believed by the authors to contribute to the democratization of the millimetre-wave spectrum earth resource.
Biomedical authors’ awareness of publication ethics: an international survey

Objective The extent to which biomedical authors have received training in publication ethics, and their attitudes and opinions about the ethical aspects of specific behaviours, have been understudied. We sought to characterise the knowledge and attitudes of biomedical authors about common issues in publication ethics. Design Cross-sectional online survey. Setting and participants Corresponding authors of research submissions to 20 journals. Main outcome measure(s) Perceived level of unethical behaviour (rated 0 to 10) presented in five vignettes containing key variables that were experimentally manipulated on entry to the survey and perceived level of knowledge of seven ethical topics related to publishing (prior publication, author omission, self-plagiarism, honorary authorship, conflicts of interest, image manipulation and plagiarism). Results 4043/10 582 (38%) researchers responded. Respondents worked in 100 countries and reported varying levels of publishing experience. 67% (n=2700) had received some publication ethics training from a mentor, 41% (n=1677) a partial course, 28% (n=1130) a full course and 55% (n=2206) an online course; only a small proportion rated training received as excellent. There was a full range (0 to 10 points) in ratings of the extent of unethical behaviour within each vignette, illustrating a broad range of opinion about the ethical acceptability of the behaviours evaluated, but these opinions were little altered by the context in which it occurred. Participants reported substantial variability in their perceived knowledge of seven publication ethics topics; one-third perceived their knowledge to be less than ‘some knowledge’ for the sum of the seven ethical topics and only 9% perceived ‘substantial knowledge’ of all topics. Conclusions We found a large degree of variability in espoused training and perceived knowledge, and variability in views about how ethical or unethical scenarios were. Ethical standards need to be better articulated and taught to improve consistency of training across institutions and countries.
An Automated Image Analysis Pipeline Enables Genetic Studies of Shoot and Root Morphology in Carrot (Daucus carota L.)

Carrot is a globally important crop, yet efficient and accurate methods for quantifying its most important agronomic traits are lacking. To address this problem, we developed an automated image analysis platform that extracts components of size and shape for carrot shoots and roots, which are necessary to advance carrot breeding and genetics. This method reliably measured variation in shoot size and shape, petiole number, petiole length, and petiole width as evidenced by high correlations with hundreds of manual measurements. Similarly, root length and biomass were accurately measured from the images. This platform also quantified shoot and root shapes in terms of principal components, which do not have traditional, manually measurable equivalents. We applied the pipeline in a study of a six-parent diallel population and an F2 mapping population consisting of 316 individuals. We found high levels of repeatability within a growing environment, with low to moderate repeatability across environments. We also observed co-localization of quantitative trait loci for shoot and root characteristics on chromosomes 1, 2, and 7, suggesting these traits are controlled by genetic linkage and/or pleiotropy. By increasing the number of individuals and phenotypes that can be reliably quantified, the development of a rapid, automated image analysis pipeline to measure carrot shoot and root morphology will expand the scope and scale of breeding and genetic studies.
Gradient-Coherent Strong Regularization for Deep Neural Networks

Regularization plays an important role in generalization of deep neural networks, which are often prone to overfitting with their numerous parameters. L1 and L2 regularizers are common regularization tools in machine learning with their simplicity and effectiveness. However, we observe that imposing strong L1 or L2 regularization with stochastic gradient descent on deep neural networks easily fails, which limits the generalization ability of the underlying neural networks. To understand this phenomenon, we first investigate how and why learning fails when strong regularization is imposed on deep neural networks. We then propose a novel method, gradient-coherent strong regularization, which imposes regularization only when the gradients are kept coherent in the presence of strong regularization. Experiments are performed with multiple deep architectures on three benchmark data sets for image recognition. Experimental results show that our proposed approach indeed endures strong regularization and significantly improves both accuracy and compression (up to 9.9x), which could not be achieved otherwise.
One-Shot Item Search with Multimodal Data

In the task of near similar image search, features from Deep Neural Network is often used to compare images and measure similarity. In the past, we only focused visual search in image dataset without text data. However, since deep neural network emerged, the performance of visual search becomes high enough to apply it in many industries from 3D data to multimodal data. Compared to the needs of multimodal search, there has not been sufficient researches. In this paper, we present a method of near similar search with image and text multimodal dataset. Earlier time, similar image search, especially when searching shopping items, treated image and text separately to search similar items and reorder the results. This regards two tasks of image search and text matching as two different tasks. Our method, however, explore the vast data to compute k-nearest neighbors using both image and text. In our experiment of similar item search, our system using multimodal data shows better performance than single data while it only increases minute computing time. For the experiment, we collected more than 15 million of accessory and six million of digital product items from online shopping websites, in which the product item comprises item images, titles, categories, and descriptions. Then we compare the performance of multimodal searching to single space searching in these datasets.
Six‐Month Assessment of a Hand Prosthesis with Intraneural Tactile Feedback

Hand amputation is a highly disabling event, which significantly affects quality of life. An effective hand replacement can be achieved if the user, in addition to motor functions, is provided with the sensations that are naturally perceived while grasping and moving. Intraneural peripheral electrodes have shown promising results toward the restoration of the sense of touch. However, the long‐term usability and clinical relevance of intraneural sensory feedback have not yet been clearly demonstrated.
Kinematics of hyper-redundant robot locomotion with applications to grasping

Simple schemes for analyzing the kinematics of hyper-redundant robot locomotion over solid terrain are considered. These schemes are based on the concepts of amplitude varying and traveling wave gaits, which are idealized models of inchworm and caterpillar locomotion. The kinematics of these gaits is formulated for hyper-redundant robots of both constant and variable length for locomotion over both flat and irregular terrain. Hyper-redundant locomotion concepts are applied to a novel grasping and fine manipulation scheme based on a grasping wave. <<ETX>>
170Wavelet Features based On-line Recognition of Handwritten

On-line character recognition systems, usually, extract features like direction, curvature trajectory of the characters, pen-ups, velocity of the pen, etc., from the handwritten characters for recognition. Whereas, if wavelet features of characters are extracted, they represent combination of many of the conventional features and act as a simple novel candidate for character recognition. This paper reports the details of an on-line character recognition system developed by the authors, for the handwritten characters/words of Kannada, a National language of India, which employs the wavelet features of the character contour for recognition. The results obtained are most encouraging.
Gene Therapy for Cystic Fibrosis Lung Disease: Overcoming the Barriers to Translation to the Clinic

Cystic fibrosis (CF) is a progressive, chronic and debilitating genetic disease caused by mutations in the CF Transmembrane-Conductance Regulator (CFTR) gene. Unrelenting airway disease begins in infancy and produces a steady deterioration in quality of life, ultimately leading to premature death. While life expectancy has improved, current treatments for CF are neither preventive nor curative. Since the discovery of CFTR the vision of correcting the underlying genetic defect – not just treating the symptoms – has been developed to where it is poised to become a transformative technology. Addition of a properly functioning CFTR gene into defective airway cells is the only biologically rational way to prevent or treat CF airway disease for all CFTR mutation classes. While new gene editing approaches hold exciting promise, airway gene-addition therapy remains the most encouraging therapeutic approach for CF. However, early work has not yet progressed to large-scale clinical trials. For clinical trials to begin in earnest the field must demonstrate that gene therapies are safe in CF lungs; can provide clear health benefits and alter the course of lung disease; can be repeatedly dosed to boost effect; and can be scaled effectively from small animal models into human-sized lungs. Demonstrating the durability of these effects demands relevant CF animal models and accurate and reliable techniques to measure benefit. In this review, illustrated with data from our own studies, we outline recent technological developments and discuss these key questions that we believe must be answered to progress CF airway gene-addition therapies to clinical trials.
Exploring and improving NOAA AVHRR NDVI image quality for African drylands

The accuracy of NOAA AVHRR NDVI maximum value composites can be poor due to interference from several sources, including cloud cover. The objectives of this paper are; 1. to accurately quantify noise in this imagery over Africa using geostatistics, and 2. to test four compositing techniques that may be able to reduce this noise. The nugget of the variogram model is used to compute standardized noise for five sites across Africa over 4 seasons. After removing trend and anisotropy in the NDVI sub-scenes, standardized noise estimates range from 18.5% in West Zambia to 68.2% in northern Congo. Four automated compositing methods are also tested over the West African Sahel for 13-day periods in order to improve image quality: the MVC, Maximum Value Temperature (MVT), a two-criteria algorithm that compares the two highest NDVI values for a period thereafter retaining the value with the smallest scan angle (MVCMISC), and a temperature-based algorithm similar to MVCMISC (MVTMISC). Results show that the MVT performs best for minimising cloud contamination, while the MVC is better for removing extreme scan angles. For the dual criteria algorithms, the MVTMISC performs best. The MVCMISC is better able to reduce scan angle bias for all land cover classes during the dry season, with the MVTMISC giving superior performance over the vegetative season. This work has implications for interpreting NDVI data in the context of famine early warning and developing biophysical descriptors of the African land surface at broad scales.
SAMHD1 inhibits epithelial cell transformation in vitro and affects leukemia development in xenograft mice

ABSTRACT Sterile alpha motif and HD domain-containing protein 1 (SAMHD1) is a mammalian dNTP hydrolase (dNTPase) and functions as a negative regulator in the efficacy of cytarabine treatment of acute myeloid leukemia (AML). We have reported that SAMHD1 knockout (KO) increased the activity of phosphoinositide 3-kinase (PI3K) in AML-derived THP-1 cells and attenuated their ability to form subcutaneous tumors in xenografted immunodeficient mice. However, the functional significance of SAMHD1 in controlling AML leukemogenesis remains unclear. Previous studies show that in vitro transformation of Madin-Darby canine kidney (MDCK) epithelial cells by the Jaagsiekte sheep retrovirus (JSRV) envelope protein requires activation of the PI3K/Akt oncogenic signaling pathway. Using this cell transformation model, we demonstrated that ectopic expression of wild-type human SAMHD1 or a dNTPase-defective SAMHD1 mutant (HD/AA) significantly inhibited MDCK cell transformation, but did not affect cell proliferation. To visualize and quantify THP-1 cell growth and metastasis in xenografted immunodeficient mice, we generated luciferase-expressing stable SAMHD1 KO THP-1 cells and control THP-1 cells, which were injected intravenously into immunodeficient mice. Bioluminescence imaging and quantification analysis of xenografted mice revealed that SAMHD1 KO cell-derived tumors had similar growth and metastatic potential compared with control cells at 35 days post-injection. However, mice xenografted with SAMHD1 KO cells showed greater survival compared with mice injected with control cells. Our data suggest that exogenous SAMHD1 expression suppresses in vitro cell transformation independently of its dNTPase activity, and that endogenous SAMHD1 affects AML tumorigenicity and disease progression in vivo.
User Support for the Combinator Logic Synthesizer Framework

Usability is crucial for the adoption of software development technologies. This is especially true in development stages, where build processes fail, because software is not yet complete or was incompletely modified. We present early work that aims to improve usability of the Combinatory Logic Synthesizer (CL)S framework, especially in these stages. (CL)S is a publicly available type-based development tool for the automatic composition of software components from a user-specified repository. It provides an implementation of a type inhabitation algorithm for Combinatory Logic with intersection types, which is fully integrated into the Scala programming language. Here, we specifically focus on building a web-based IDE to make potentially incomplete or erroneous input specifications for and decisions of the algorithm understandable for non-experts. A main aspect of this is providing graphical representations illustrating the step-wise search process of the algorithm. We also provide a detailed discussion of possible future work to further improve the understandability of these representations.
Exploring Imaginative Capability and Learning Motivation Difference Through Picture E-Book

As advanced technology emerges into learning, learning behavior has changed from printed books to e-books with diversified teaching plans, such as picture E-books. Although past research regards picture E-books as successful and effective for children, some studied have reported that the electronic feature may negatively affect children. Briefly, as children are attracted by the games or sounds in electronic books, this paper intends to fill the gap with the augmented reality (AR) technology. The imaginative capability is an important factor to stimulate potential and inspire creativity. The research field of imaginative capability is a critical element of the effect student creativity development in the future; however, to the best of our knowledge, little attention has been focused on imaginative capability with technology, to say nothing of learning in ubiquitous learning environments. To cope with this problem, this paper aims to present a picture E-book based on the AR technology and learning theories to build a learner-centered u-learning environment, and examines how to inspire students’ imaginative capability in three ways: text-based traditional learning, picture-based traditional learning, and picture E-books with the AR technology–in order to determine the differences of students’ learning motivations and imaginative capabilities.
Silicon Nitride in Silicon Photonics

The silicon nitride (Si3N4) planar waveguide platform has enabled a broad class of low-loss planar-integrated devices and chip-scale solutions that benefit from transparency over a wide wavelength range (400–2350 nm) and fabrication using wafer-scale processes. As a complimentary platform to silicon-on-insulator (SOI) and III–V photonics, Si3N4 waveguide technology opens up a new generation of system-on-chip applications not achievable with the other platforms alone. The availability of low-loss waveguides (<1 dB/m) that can handle high optical power can be engineered for linear and nonlinear optical functions, and that support a variety of passive and active building blocks opens new avenues for system-on-chip implementations. As signal bandwidth and data rates continue to increase, the optical circuit functions and complexity made possible with Si3N4 has expanded the practical application of optical signal processing functions that can reduce energy consumption, size and cost over today’s digital electronic solutions. Researchers have been able to push the performance photonic-integrated components beyond other integrated platforms, including ultrahigh Q resonators, optical filters, highly coherent lasers, optical signal processing circuits, nonlinear optical devices, frequency comb generators, and biophotonic system-on-chip. This review paper covers the history of low-loss Si3N4 waveguide technology and a survey of worldwide research in a variety of device and applications as well as the status of Si3N4 foundries.
The application of ILP based on source formulation in WBS networks

The ILP based on source formulation is newly proposed in recent literatures. This paper firstly applies the ILP based on source formulation into the current popular Waveband switching (WBS) network. Our research shows that the ILP based on source formulation can effectively improve the network performance. Two optimized WBS network scenarios are discussed in this paper, including the networks constructed with multi-granular OXCs (MG-OXC) and the networks which is not limited to MG-OXCs but constrained by the condition that all wavebands only contain lightpaths to the same destination. Numeric results show that source-formulation ILP can require less computational effort compared to flow-formulation ILP.
Finite state machine trace analysis program

We describe a novel approach to verify finite state machines. We describe the finite stale machine (FSM) trace analysis tool that analyzes run time traces of finite state machines while the FSMs are being simulated and reports to the user information about state transitions and arcs traversed. During the flow this tool creates a separate Verilog monitor routine for each FSM in the design and these monitor routines print out the necessary information. Therefore, this tool is useful for all Verilog FSM designers because they do not have to include arc monitoring in their Verilog code when writing the FSMs. The FSM analysis tool is integrated well into the Verilog/Synopsys design methodology. <<ETX>>