Miracle-dz/UniFAR-FTUs huggingface dataset:
Diagnosis of histological gastritis based on the Kyoto classification of gastritis in Japanese subjects – including evaluation of aging and sex difference of histological gastritis

Abstract Objectives The Kyoto classification of gastritis was established for diagnosing Helicobacter pylori (H. pylori) infection via endoscopic findings. We investigated the role of the Kyoto classification of gastritis in the diagnosis of H. pylori infection and histological gastritis in Japanese individuals. Moreover, the histological findings of gastritis in H. pylori infection were examined based on age and sex differences. Methods We selected 561 patients aged 20–79 years who underwent gastroduodenal endoscopy at our hospital between 2010 and 2018. Endoscopic biopsy specimens from the antrum and corpus were used to investigate H. pylori infection and histology. Endoscopic findings were based on the Kyoto classification of gastritis, and histological findings were based on the updated Sydney System. Results Endoscopic findings based on the Kyoto classification of gastritis (H. pylori positive, 303 patients; H. pylori negative, 258 patients, based on endoscopic findings) had 98.7% sensitivity and 98.4% specificity for histological gastritis. In addition, endoscopic findings in the three age groups (20–39, 40–59, and 60–79 years) had high sensitivity and specificity. Atrophy and intestinal metaplasia were found only in the H. pylori-positive group and progressed with age. Histological inflammation of pyloric mucosa in the younger age group of H. pylori-positive patients was significantly higher than that in the elderly group. Significant inflammation was observed in young women. Conclusions The Kyoto classification of gastritis can not only diagnose H. pylori infection but also detect histological gastritis. Histological gastritis has varying characteristics of inflammation, atrophy, and intestinal metaplasia, depending on age and sex.
Dynamical analysis of vibratory feeder and feeding parts considering interactions by an improved increment harmonic balance method

Vibratory feeder is known as one of major machines in various industries. The feeding parts in a vibratory feeder are experiencing repeated discontinuous friction that can be considered as a typical strong nonlinear dynamic problem. It is very significant to obtain the motion of parts under different alternating loads for the design of vibratory feeder. An analytical model of parts’ motion in sliding regime was constructed and verified with a simplified model based on discrete element method. An improved increment harmonic balance method was proposed to obtain the dynamic behaviors of vibratory feeder and the motion of feeding parts. In contrast to previous researches, we considered the interactions between vibratory feeder and parts in detail, not only containing the effects of the dynamics of vibratory feeder on the motion of parts but also the motion of parts on vibratory feeder. Finally, studying the interactions for various parts’ masses in different frequencies, the motion of parts had a significant effect on the dynamics of vibratory feeder. In reverse, the alterations of the dynamics of vibratory feeder influenced the motion of parts and conveying speed. In the design of vibratory feeder, the interactions between vibratory feeder and parts should not be neglected.
Video content analysis on body-worn cameras for retrospective investigation

In the security domain, cameras are important to assess critical situations. Apart from fixed surveillance cameras we observe an increasing number of sensors on mobile platforms, such as drones, vehicles and persons. Mobile cameras allow rapid and local deployment, enabling many novel applications and effects, such as the reduction of violence between police and citizens. However, the increased use of bodycams also creates potential challenges. For example: how can end-users extract information from the abundance of video, how can the information be presented, and how can an officer retrieve information efficiently? Nevertheless, such video gives the opportunity to stimulate the professionals’ memory, and support complete and accurate reporting. In this paper, we show how video content analysis (VCA) can address these challenges and seize these opportunities. To this end, we focus on methods for creating a complete summary of the video, which allows quick retrieval of relevant fragments. The content analysis for summarization consists of several components, such as stabilization, scene selection, motion estimation, localization, pedestrian tracking and action recognition in the video from a bodycam. The different components and visual representations of summaries are presented for retrospective investigation.
Relationships Between Age, Soluble Triggering Receptor Expressed on Myeloid Cells-1 (sTREM-1), and Mortality Among Critically Ill Adults: A Cohort Study

Supplemental Digital Content is available in the text ABSTRACT Background: Innate immune dysregulation may contribute to age-related differences in outcomes among critically ill adults. Soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) is an important innate immune marker with prognostic value in sepsis, but age-related differences have not been studied. Methods: This was a prospective cohort from a large tertiary care hospital enrolling adults from both medical and trauma-surgical intensive care units (ICUs). Plasma sTREM-1 was measured in participants within 24 h of ICU admission. We analyzed associations between age (≤50 and >50 years) and sTREM-1 using linear regression. We then examined associations between sTREM-1 and both 28-day mortality and persistent organ dysfunction (defined as need for dialysis, vasopressors, or invasive mechanical ventilation) 7 days following admission using relative risk regression. Results: Of 231 critically ill adults, older patients (n = 122) had higher prevalence of chronic disease and sepsis on enrollment than younger patients, but acute illness severity was similar. Age over 50 was associated with 27% higher sTREM-1 concentrations (95% CI 6%–53%), adjusted for sex and Charlson comorbidity index (CCI). Two-fold higher sTREM-1 was associated with 2.42-fold higher risk for mortality (95% CI 1.57, 3.73) and 1.86-fold higher risk for persistent organ dysfunction (95% CI 1.45, 2.39), adjusted for sex, CCI, and age. Conclusions: sTREM-1 was elevated among critically ill older adults, and strongly associated with both death and persistent organ dysfunction. Immune responses associated with sTREM-1 may contribute to age-related differences in ICU outcomes, warranting further study as a potential therapeutic target in older adults.
Cross‐sectional relation of long‐term glucocorticoids in hair with anthropometric measurements and their possible determinants: A systematic review and meta‐analysis

Long‐term glucocorticoids (HairGC) measured in scalp hair have been associated with body mass index (BMI), waist circumference (WC), and waist‐hip‐ratio (WHR) in several cross‐sectional studies. We aimed to investigate the magnitude, strength, and clinical relevance of these relations across all ages.
Obesogenic diets induce anxiety in rodents: A systematic review and meta‐analysis

Obesity and mood disorders have been linked in a positive feedback loop. However, due to the bidirectional relationship between obesity and mental health, it is not clear whether anxiety is correlated with or caused by consumption of obesogenic diets. Here, we present a meta‐analysis on the effects of dietary manipulation on rodent behavior in the elevated plus maze and open field test, the most common tests of anxiety‐like behavior in animal models. The main dataset examined effects of obesogenic diets on time spent in the open and movement around the mazes. Auxiliary datasets examined effects of caloric restriction and protein restriction. Obesogenic diets had a negative effect on the time spent in the open overall. Effects were stronger in males than females. No effect of diet on locomotion was found, indicating that increases in anxiety‐like behavior are not due to altered activity levels. No consistent effect of caloric restriction was observed, whereas protein restriction was associated with an increase in the time spent in the open. We show that obesogenic diets have a causative effect on anxiety‐like behaviors in rodents, and not via a change in activity. Further studies are required to determine why obesogenic diets induce these behavioral changes.
The postnatal window is critical for the development of sex-specific metabolic and gut microbiota outcomes in offspring

ABSTRACT The Developmental Origins of Health and Disease (DOHaD) concept has been proposed to explain the influence of environmental conditions during critical developmental stages on the risk of diseases in adulthood. The aim of this study was to compare the impact of the prenatal vs. postnatal environment on the gut microbiota in dams during the preconception, gestation and lactation periods and their consequences on metabolic outcomes in offspring. Here we used the cross-fostering technique, e.g. the exchange of pups following birth to a foster dam, to decipher the metabolic effects of the intrauterine versus postnatal environmental exposures to a polyphenol-rich cranberry extract (CE). CE administration to high-fat high-sucrose (HFHS)-fed dams improved glucose homeostasis and reduced liver steatosis in association with a shift in the maternal gut microbiota composition. Unexpectedly, we observed that the postnatal environment contributed to metabolic outcomes in female offspring, as revealed by adverse effects on adiposity and glucose metabolism, while no effect was observed in male offspring. In addition to the strong sexual dimorphism, we found a significant influence of the nursing mother on the community structure of the gut microbiota based on α-diversity and β-diversity indices in offspring. Gut microbiota transplantation (GMT) experiments partly reproduced the observed phenotype in female offspring. Our data support the concept that the postnatal environment represents a critical window to influence future sex-dependent metabolic outcomes in offspring that are causally but partly linked with gut microbiome alterations.
Soil Structure Interaction Problems for Nuclear Containment Structures

The problems of soil amplification and soil structure interaction have been the subject of considerable research in recent years, particularly in relation to the seismic design of nuclear power plants. A number of sophisticated mathematical techniques and simpler engineering approximations have been developed to estimate their effects on structural forces, and more importantly, on the characteristics of the motion at different floor levels (amplified response spectra for the design of equipment). There is however some confusion and controversy on the mathematical accuracy of some of these methods and the physical significance of others. Sometimes elaborate techniques are judged appropriate even when based on incorrect assumptions, and often methods which can be shown to be mathematically equivalent are classified as different because of inconsistencies in their implementation. The various methods of analysis now available and their similarities and differences when based on consistent assumptions are examined. (auth)
A Design Study of Radial Inflow Turbines With Splitter Blades in Three-Dimensional Flow

An inverse design technique to design turbomachinery blading with splitter blades in three-dimensional flow is developed. It is based on the use of Clebsch transformation which allows the velocity field to be written as a potential part and a rotational part. It is shown that the rotational part can be expressed in terms of the mean swirl schedule (the circumferential average of the product of radius and tangential velocity) and the blade geometry that includes the main blade as well as the splitter blade. This results in an inverse design approach in which both the main and the splitter blade geometry are determined from a specification of the swirl schedule. Previous design study of a heavily-loaded radial inflow turbine, without splitter blades, for a rather wide variety of specified mean swirl schedules result in a blade shape with unacceptable non-radial blade filament; the resulting reduced static pressure distribution yields an “inviscid reverse flow region”1 covering almost the first half of the blade pressure surface. When the inverse design technique is applied to the design study of the turbine wheel with splitter blades, the results indicate that the use of splitter blades is an effective means for making the blade filament at an axial location more radial as well as a potential means for eliminating any “inviscid reverse flow” region that may exist on the pressure side of the blades.Copyright © 1994 by ASME
Knowledge‐based neural network approaches for modeling and estimating radon concentrations

Radon is a chemically inert, tasteless, and odorless gas, which causes lung cancer in people who are exposed to higher concentrations for extended periods of time. It is a byproduct of the decay of uranium in the soil. High concentrations are present in closed units, like houses, schools, etc. To identify houses with unacceptably high radon levels, the radon concentration for each zip code in Ohio needs to be measured. However, not all of the zip codes are surveyed, owing to reasons such as inapproachability. In places where data is unavailable, the concentrations need to be estimated using interpolation techniques. This article proposes the application of knowledge‐based neural network approaches, namely prior knowledge input method, source difference method, and space‐mapped neural network method for modeling and predicting radon concentrations. To this end, knowledge available in the form of uranium concentration data is exploited. Modeling accuracies of the proposed techniques are compared with those of the commonly used multilayer perceptron networks (employed in one of our recent work) and conventional interpolation techniques. © 2012 American Institute of Chemical Engineers Environ Prog, 32: 355‐364, 2013
Model-based representational similarity analysis of blood-oxygen-level-dependent fMRI captures threat learning in social interactions

Past research has shown that attributions of intentions to other's actions determine how we experience these actions and their consequences. Yet, it is unknown how such attributions affect our learning and memory. Addressing this question, we combined neuroimaging with an interactive threat learning paradigm in which two interaction partners (confederates) made choices that had either threatening (shock) or safe (no shock) consequences for the participants. Importantly, participants were led to believe that one partner intentionally caused the delivery of shock, whereas the other did not (i.e. unintentional partner). Following intentional versus unintentional shocks, participants reported an inflated number of shocks and a greater increase in anger and vengeance. We applied a model-based representational similarity analysis to blood-oxygen-level-dependent (BOLD)-MRI patterns during learning. Surprisingly, we did not find any effects of intentionality. The threat value of actions, however, was represented as a trial-by-trial increase in representational similarity in the insula and the inferior frontal gyrus. Our findings illustrate how neural pattern formation can be used to study a complex interaction.
DIB: Piled Man-made Object Detection and Pose Estimation in Point Cloud Blocks

Object detection and pose estimation are fundamental modules in robotic applications, many of these objects are man-made like mechanical parts. Although have been researched widely in recent designs, detecting objects from a cluttered pile is still challenging. In this paper, a robust method for the detection and pose estimation of randomly piled man-made objects in blocks of point cloud is presented which increases the detection efficacy significantly. The approach begins with building blocks from the point cloud, each of which contains one object. Then object detection and pose estimation are performed in the blocks using 3D primitive shapes. We evaluate the performance of our approach in comparison with state-of-the-art methods. Experiments show that the proposed system detects objects efficiently and accurately in the presence of noise and occlusion.
PHANTOM GHOSTDAG: a scalable generalization of Nakamoto consensus: September 2, 2021

In 2008 Satoshi Nakamoto invented the basis for blockchain-based distributed ledgers. The core concept of this system is an open and anonymous network of nodes, or miners, which together maintain a public ledger of transactions. The ledger takes the form of a chain of blocks, the blockchain, where each block is a batch of new transactions collected from users. One primary problem with Satoshi's blockchain is its highly limited scalability. The security of Satoshi's longest chain rule, more generally known as the Bitcoin protocol, requires that all honest nodes be aware of each other's blocks very soon after the block's creation. To this end, the throughput of the system is artificially suppressed so that each block fully propagates before the next one is created, and that very few "orphan blocks" that fork the chain be created spontaneously. In this paper we present PHANTOM, a proof-of-work based protocol for a permissionless ledger that generalizes Nakamoto's blockchain to a direct acyclic graph of blocks (blockDAG). PHANTOM includes a parameter k that controls the level of tolerance of the protocol to blocks that were created concurrently, which can be set to accommodate higher throughput. It thus avoids the security-scalability tradeoff which Satoshi's protocol suffers from. PHANTOM solves an optimization problem over the blockDAG to distinguish between blocks mined properly by honest nodes and those created by non-cooperating nodes who chose to deviate from the mining protocol. Using this distinction, PHANTOM provides a robust total order on the blockDAG in a way that is eventually agreed upon by all honest nodes. Implementing PHANTOM requires solving an NP-hard problem, and to avoid this prohibitive computation, we devised an efficient greedy algorithm GHOSTDAG that captures the essence of PHANTOM. The GHOSTDAG protocol has been implemented as the underlying technology of the Kaspa cryptocurrency. The Kaspa network allows us to produce statistics about the performance of GHOSTDAG in real world scenarios. We provide an analysis of confirmation times obtained by observing the Kaspa network. We provide a formal proof of the security of GHOSTDAG, namely, that its ordering of blocks is irreversible up to an exponentially negligible factor. We discuss the properties of GHOSTDAG and how it compares to other DAG based protocols.
Insights into Informal Benchmarking

Results of two global surveys show that informal benchmarking ranking the top 20% of the most popular organization improvement tools. The results also indicate that informal benchmarking is not as effective as it is popular, therefore there is room to enhance its performance. The focus of this paper is twofold. Firstly, it illustrates the conception of a preliminary model of informal benchmarking by the review of benchmarking, informal learning, organization learning and knowledge management, augmented by ideas on quantum thinking, innovation and positive deviance. Discussions with benchmarking practitioners were also held to strengthen the model. Secondly, it outlines a mixed methods approach to obtain data (not yet completed) on informal benchmarking practices in organizations via quantitative surveys and qualitative semi-structured interviews. The data will then be used to refine the conceptual model, prepare an assessment framework, and design a road- map for implementing an effective organization-wide approach of informal benchmarking. This will set the stage for a quantum leap in the understanding and effectiveness of informal benchmarking as a business improvement tool. The research also provide a platform for an extension of its theory in organizational improvement.
Experimental investigation of supersonic boundary-layer tripping with a spanwise pulsed spark discharge array

Abstract In this paper, a pulsed spark discharge plasma actuator array is deployed to control laminar–turbulent transition in a Mach 3.0 flat-plate boundary layer, and the subtle flow structures are visualized by nanoparticle planar laser scattering (NPLS) technique. Results show that the onset location of turbulence can be brought upstream by plasma actuation, corresponding to forced boundary-layer transition. Hairpin vortex packets evolved from the thermal bulbs play a vital role in the breakdown of laminar flow. With the help of a machine learning tool, all the relevant structures induced by plasma actuation are extracted from NPLS images, and a conceptual model of the hairpin vortex generation is proposed, including three stages: production and lift-up of the high-vorticity region, formation of the $\varLambda$ vortex and evolution of the hairpin vortex.
Considerations for Post-processing Parameters in Mixed-Method 3D Analyses

ABSTRACT The production of three-dimensional (3D) digital meshes of surface and computed tomographic (CT) data has become widespread in morphometric analyses of anthropological and archaeological data. Given that processing methods are not standardized, this leaves questions regarding the comparability of processed and digitally curated 3D datasets. The goal of this study was to identify those processing parameters that result in the most consistent fit between CT-derived meshes and a 3D surface model of the same human mandible. Eight meshes, each using unique thresholding and smoothing parameters, were compared to assess whole-object deviations, deviations along curves, and deviations between specific anatomical features on the surface model when compared with the CT scans using a suite of comparison points. Based on calculated gap distances, the mesh that thresholded at “0” with an applied smoothing technique was found to deviate least from the surface model, although it is not the most biologically accurate. Results have implications for aggregated studies that employ multimodal 3D datasets, and caution is recommended for studies that enlist 3D data from websites and digital repositories, particularly if processing parameters are unknown or derived for studies with different research foci.
The Experimental Study and Numerical Simulation of Turbulent Flow in Pumping Forebay

The experiment study was made to optimize the design of a pumping forebay. The Combined-sills were made in the forebay to eliminate the circulation and vortices of the diffusing flow successfully. The Numerical simulation of three-dimensional turbulent flow is applied on the complicate fore-and-aft flow of sills. The computational results are compared with the measurement results of physical model. The calculated results are in good agreement with the experimental data. The flow pattern is obviously improved. The study results have been applied in the project which gives a uniform approach flow to the pumping sump. © 2009 ASME
Establishing a Multibeam Sonar Evaluation Test Bed near Sidney, British Columbia

The Canadian Hydrographic Service (CHS), Naval Oceanographic Office (NAVOCEANO) and the Ocean Mapping Group of the University of New Brunswick (OMG) collaborated on establishing a multibeam sonar test bed in the vicinity of the Institute of Ocean Sciences in Sidney, British Columbia Canada. This paper describes the purpose of the sonar evaluation test bed, the trials and tribulations of two foreign governments collaborating on projects of mutual interest, the evaluation areas and their characteristics for sonar testing, and sample results of sonar evaluations using this test bed. Some target detection comparisons of several systems over a range of artificial sonar targets will also be given.