Miracle-dz/UniFAR-FTUs huggingface dataset:
How Does Socioeconomic Status Affect Chinese Adolescents’ Weight Status?: A Study of Possible Pathways

Abstract Although the prevalence of overweight and obesity among Chinese youth with higher socioeconomic status (SES) has been increasing, few studies have explored the mechanisms through which SES influences Chinese adolescents’ weight status. Using data from the 2004, 2006, 2009, and 2011 China Health and Nutrition Survey (CHNS), this study aims to explore possible pathways through which SES may affect Chinese adolescents’ risk of being overweight. Results from pathway analyses in a structural equation modeling framework indicate that indirect pathways, such as food intake and physical activities, partially explain the association between SES and Chinese adolescents’ weight status, while weight-related attitudes do not. The pathways identified in this study can aid targeted intervention programs to alleviate the prevalence of adolescent obesity in China.
A QoS-based approach for cloud-service matchmaking, selection and composition using the Semantic Web

PurposeCloud computing provides a dynamic, heterogeneous and elastic environment by offering accessible ‘cloud services’ to end-users. The tasks involved in making cloud services available, such as matchmaking, selection and composition, are essential and closely related to each other. Integration of these tasks is critical for optimal composition and performance of the cloud service platform. More efficient solutions could be developed by considering cloud service tasks collectively, but the research and academic community have so far only considered these tasks individually. The purpose of this paper is to propose an integrated QoS-based approach for cloud service matchmaking, selection and composition using the Semantic Web.Design/methodology/approachIn this paper, the authors propose a new approach using the Semantic Web and quality of service (QoS) model to perform cloud service matchmaking, selection and composition, to fulfil the requirements of an end user. In the Semantic Web, the authors develop cloud ontologies to provide semantic descriptions to the service provider and requester, so as to automate the cloud service tasks. This paper considers QoS parameters, such as availability, throughput, response time and cost, for quality assurance and enhanced user satisfaction.FindingsThis paper focus on the development of an integrated framework and approach for cloud service life cycle phases, such as discovery, selection and composition using QoS, to enhance user satisfaction and the Semantic Web, to achieve automation. To evaluate performance and usefulness, this paper uses a scenario based on a Healthcare Decision-Making System (HDMS). Results derived through the experiment prove that the proposed prototype performs well for the defined set of cloud-services tasks.Originality/valueAs a novel concept, our proposed integrated framework and approach for cloud service matchmaking, selection and composition based on the Semantic Web and QoS characterisitcs (availability, response time, throughput and cost), as part of the service level agreement (SLA) will help the end user to match, select and filter cloud services and integrate cloud-service providers into a multi-cloud environment.
Multiscale and Multi-Granularity Process Analytics: A Review

As Industry 4.0 makes its course into the Chemical Processing Industry (CPI), new challenges emerge that require an adaptation of the Process Analytics toolkit. In particular, two recurring classes of problems arise, motivated by the growing complexity of systems on one hand, and increasing data throughput (i.e., the product of two well-known “V’s” from Big Data: Volume × Velocity) on the other. More specifically, as enabling IT technologies (IoT, smart sensors, etc.) enlarge the focus of analysis from the unit level to the entire plant or even to the supply chain level, the existence of relevant dynamics at multiple scales becomes a common pattern; therefore, multiscale methods are called for and must be applied in order to avoid biased analysis towards a certain scale, compromising the benefits from the balanced exploitation of the information content at all scales. Also, these same enabling technologies currently collect large volumes of data at high-sampling rates, creating a flood of digital information that needs to be properly handled; optimal data aggregation provides an efficient solution to this challenge, leading to the emergence of multi-granularity frameworks. In this article, an overview is presented on multiscale and multi-granularity methods that are likely to play an important role in the future of Process Analytics with respect to several common activities, such as data integration/fusion, de-noising, process monitoring and predictive modelling, among others.
Comparison of Two High-Intensity Interval Training (HIIT) for Two Weeks on Fat Oxidation, Body Fat Percentage and Vo2max in Overweight Young Men

Introduction: The purpose of this study was to Comparison the effects of six sessions high intensity interval training (HIIT) on fat oxidation and VO2max and body fat percentage in sedentary overweight young men. Methods: Sixteen inactive overweight young men voluntarily participated in this study and randomly divided into two Groups: Group A (n: 8, age: 24.21±2.01, height: 174.22±3.91, weight: 79.27±7.59, BMI: 26/54±2/6) and Group B (n: 8, age: 24.23±1.41, height: 176.22±3.88, weight: 81.27±6.23, BMI: 26/32±2/9). Two groups performed three HIIT sessions per week for two weeks. Group A (4×1 min/4 min R) and Group B (4×30s/2min R) performed maximal sprint running within a 20 m area. Respiratory gas was collected 24 hours before and after exercise protocol in fasting state. Data were analyzed by dependent t test for between groups and paired T test for within groups. Results: Statistical analysis showed that, Six sessions of HIIT, lead to increasing 43 % of fatty oxidation in Group A in during exercise test, that these changes were significant compared to the Group B (with increasing 11/5% fatty oxidation). changes in weight and present of body fat were significant only in group A. present study showed, a significant increase in VO2max in Group A (5/19%) and Group B (4%). Conclusion: According to the results of this study, it appears six sessions HIIT lead to improvement of fatty oxidation and store glycogen. In conclusion, it appears that HIIT In addition to reduce the body fat and increase the aerobic fitness, is a time efficient means for decrease weight and improving oxidation capacity in sedentary overweight young men.
THE TROPHIC ECOLOGY OF FRESHWATER GAMMARUS SPP. (CRUSTACEA:AMPHIPODA): PROBLEMS AND PERSPECTIVES CONCERNING THE FUNCTIONAL FEEDING GROUP CONCEPT

Gammarus spp. are widespread throughout a diverse range of freshwater habitats and can be the dominant part of many benthic macroinvertebrate assemblages, in terms of both numbers and/or biomass. Although the vast majority of studies have emphasized the herbivorous nature of Gammarus spp. and their ‘shredder’ functional feeding group (FFG) classification, we show that a far wider food base is exploited than has been previously acknowledged. This ‘plasticity’ as herbivore/predator is linked to the success of Gammarus spp. in persisting in and colonizing/invading disturbance‐prone ecosystems. Intraguild predation and cannibalism are more common than previously realized. This behaviour appears to be a causal mechanism in many amphipod species replacements. Additionally, Gammarus spp. are major predators of other members of the macroinvertebrate community. Furthermore, while many studies have emphasized fish predation on Gammarus spp. , we illustrate how this fish: amphipod, predator: prey interaction may be a two‐way process, with Gammarus spp. themselves preying upon juvenile and wounded/trapped fish. We urge that a new realism be adopted towards the trophic ecology of Gammarus spp. and their role as predators and prey and that previously established FFG assumptions of both the food and the feeder be questioned critically.
An Algorithmic Scheme for Statistical Thesaurus Construction in a Morphologically Rich Language

ABSTRACT Corpus-based automatic thesaurus construction uses linguistic methods, such as Part-of-Speech taggers and parsers, which often perform poorly on MRLs. Therefore, in this paper, we focused on the complex task of adapting corpus-based thesaurus construction methods for MRLs. We investigated two statistical approaches for thesaurus construction; a) a first-order co-occurrence-based approach and b) a second-order distributional-based approach. We explored alternative levels of morphological term representations complemented by grouping the morphological variants. We then introduced and adopted a generic algorithmic scheme for thesaurus construction in MRLs for both first-order and second-order approaches. Our scheme investigated alternative representation levels and offered alternative configurations. We demonstrated the empirical benefits of our methodology for a diachronic Hebrew thesaurus construction. We used morphological analysis tools, defined and applied a new annotation scheme, and demonstrated its optimal configuration, which outperforms the baseline for both first and second order corpus-based thesaurus construction approaches.
Nitrogen and Lignin Control of Hardwood Leaf Litter Decomposition Dynamics

The effects of initial nitrogen and lignin contents of six species of hardwood leaves on their decomposition dynamics were studied at the Hubbard Brook Experimental Forest. Rate con- stants (k) for annual leaf mass loss ranged from -0.08 to -0.47. The rate constants (k) had a negative linear correlation (r2 = .89) with the ratio of initial lignin concentration to initial nitrogen concentra- tion. Decomposition dynamics of the litter materials were described by inverse linear relationships between the percentage of original mass remaining and the nitrogen concentration in the residual material. Initial lignin concentration was highly correlated (r2 = .93) with the slope of the inverse linear relationship for each of the litter types.
The Logic Model, Participatory Evaluation and Out Of School Art Programs

The logic model and participatory evaluation are two popular methods of conducting program evaluation. Although both methods have their strengths, each has distinct weaknesses which can be ameliorated by combining them both together. The combined method is used to evaluate an out of school art program at a museum. Using both the logic model and participatory evaluation yielded beneficial results with more accurate representation of program outcomes
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Swizzle Inventor: Data Movement Synthesis for GPU Kernels

Utilizing memory and register bandwidth in modern architectures may require swizzles --- non-trivial mappings of data and computations onto hardware resources --- such as shuffles. We develop Swizzle Inventor to help programmers implement swizzle programs, by writing program sketches that omit swizzles and delegating their creation to an automatic synthesizer. Our synthesis algorithm scales to real-world programs, allowing us to invent new GPU kernels for stencil computations, matrix transposition, and a finite field multiplication algorithm (used in cryptographic applications). The synthesized 2D convolution and finite field multiplication kernels are on average 1.5--3.2x and 1.1--1.7x faster, respectively, than expert-optimized CUDA kernels.
High-Dimensional Multiple Bubbles Prediction Based on Sparse Constraints

Many bubble test methods do not have the ability to predict multiple bubbles in a high dimensional space now. Therefore, we propose a data-driven, self-adaptive evolutionary bubble prediction algorithm named WSADF. First, according to the invariance principle, we speculate that if there are inherent degrees of freedom for high dimensional time series, then comovement causality analysis (CCA) can be improved to select the decisive high dimensional time series that must reflect the prominent comovement causality. The optimization problem of the high dimensional space can be solved in the low dimensional space and maintain the inherent relationships among the time series by using CCA. Second, the learning parameters of hidden neurons have the ability of self-adaptive differential evolution. The neurons in the network are used to model the individuals’ signals from the perspective of evolution. Third, a self-adaptive evolutionary neural network can be used to simulate the operation of the entire market’s signals. The generalized sup augmented Dickey–Fuller test is improved to suit changing market environmental conditions. Thus, the WSADF algorithm has the ability to predict multiple bubbles in high dimensional space. An empirical application of the methodology is conducted on different types of markets (e.g., the USDCNH and CSI300 closing prices), which has successfully identified and forecasted multiple bubbles from 2015 to 2017.
A Novel Method for Router-to-AS Mapping Based on Graph Community Discovery

The last decades have witnessed the progressive development of research on Internet topology at the router or autonomous systems (AS) level. Routers are essential components of ASes, which dominate their behaviors. It is important to identify the affiliation between routers and ASes because this contributes to a deeper understanding of the topology. However, the existing methods that assign a router to an AS, based on the origin AS of its IP addresses do not make full use of the information during the network interaction procedure. In this paper, we propose a novel method to assign routers to their owners’ AS, based on community discovery. First, we use the initial AS information along with router-pair similarities to construct a weighted router level graph; secondly, with the large amount of graph data (more than 2M nodes and 19M edges) from the CAIDA ITDK project, we propose a fast hierarchy clustering algorithm with time and space complexity, which are both linear for graph community discovery. Finally, router-to-AS mapping is completed, based on these AS communities. Experimental results show that the effectiveness and robustness of the proposed method. Combining with AS communities, our method could have the higher accuracy rate reaching to 82.62% for Routers-to-AS mapping, while the best accuracy of prior works is plateaued at 65.44%.
Debugging and monitoring of applicationprograms in the BagrOS-4000 real-time operation system based on the Elbrus architecture

The article is concerned with the problems of monitoring and debugging of operating system processes, the effectiveness of which in the hard real-time operating system version does not allow any stopping to analyze the state of software and/ or hardware. The paper describes the concept of a debugging and monitoring system developed taking into account this feature in the Sukhoi design bureau for the BagrOS-4000 hard real-time operating system on the Elbrus architectural platform together with the specialists of MCST JSC. The method of non-stop monitoring and data collection in hard realtime processes in the multiprocess multimodular systems is discussed. An approach to the management of debugging targets in terms of source code using the DWARF debugging information specification is presented. The transition from the instrumental machine to the system server built into the target computer is described. Given the rationale for the use of client-server architecture in the debugging and monitoring system for BagrOS-4000. A comparative analysis of the key functionality of the debugging and monitoring system with the existing debugging systems has been carried out; the key aspects of the DMS architecture have been considered. The design of a machine-dependent interface required for the integration of the independent hardware platforms into the BagrOS-4000 system when implementing the system on an integrated avionics module of the onboard complex is discussed. The results of testing of the debugging and monitoring systems are analyzed in terms of efficiency versus the classical method of using the debug console prints when debugging a real-time operating system. Most of the above solutions are universal and have been successfully tested using other microprocessor platforms on multi-threaded application programs of real-time operating systems running on multi-core processors, including the MIPS, Power PC, Intel platforms.
Ripplet Transform based Medical Image Compression

Hospitals produce a number of images per diagnosis and this can lead to produce the 5GB to 15 GB data. It increases the difficulties for a hospital storage system to store, manage and to transmit these images. Among the proposed compression methods, much interest has been focused on achieving good compression ratios and high Peak Signal to Noise Ratio (PSNR), and little work has been done on resolving 2D singularities along image edges with efficient representation of images at different scales and different directions. Grounded on this fact, this paper proposes a compression method for medical images by representing singularities along arbitrarily shaped curves without sacrificing the amount of compression. This method uses a recently introduced family of directional transforms called Ripplet transform. Usually the coarser version of an input image is represented using base, but discontinuities across a simple curve affect the high frequency components and affect all the transform coefficients on the curve. Hence these transforms do not handle curve discontinuities well. By defining the scaling law in a more broader scope and more flexible way, Ripplet Transform is formed as a generalisation of Curvelet transform, by adding two tunable parameters i.e support of Ripplets and degree of Ripplets . The inherent properties of Ripplet transform in conjunction with the coding of coefficients using Huffman Encoder provide efficient representation of edges in images and thereby achieving a high quality
Image Stream Similarity Search in GPU Clusters

Images are an important part of today’s society. They are everywhere on the internet and computing, from news articles to diverse areas such as medicine, autonomous vehicles and social media. This enormous amount of images requires massive amounts of processing power to process, upload, download and search for images. The ability to search an image, and find similar images in a library of millions of others empowers users with great advantages. Different fields have different constraints, but all benefit from the quick processing that can be achieved. Problems arise when creating a solution for this. The similarity calculation between several images, performing thousands of comparisons every second, is a challenge. The results of such computations are very large, and pose a challenge when attempting to process. Solutions for these problems often take advantage of graphs in order to index images and their similarity. The graph can then be used for the querying process. Creating and processing such a graph in an acceptable time frame poses yet another challenge. In order to tackle these challenges, we take advantage of a cluster of machines equipped with Graphics Processing Units (GPUs), enabling us to parallelize the process of describing an image visually and finding other images similar to it in an acceptable time frame. GPUs are incredibly efficient at processing data such as images and graphs, through algorithms that are heavily parallelizable. We propose a scalable and modular system that takes advantage of GPUs, distributed computing and fine-grained parallellism to detect image features, index images in a graph and allow users to search for similar images. The solution we propose is able to compare up to 5000 images every second. It is also able to query a graph with thousands of nodes and millions of edges in a matter of milliseconds, achieving a very efficient query speed. The modularity of our solution allows the interchangeability of algorithms and different steps in the solution, which provides great adaptability to any needs.
Engineering Streptomyces diastatochromogenes 1628 to increase the production of toyocamycin

Toyocamycin (TM) shows antifungal activity and can be used to treat plant diseases. TM is produced by Streptomyces diastatochromogenes 1628, but the production rate is always very low. Recently, the gene toyG was cloned; however, nothing was known about the influence of toyG on TM production. In this study, the rational combined co‐expression of toyG with frr encoding a ribosome recycling factor and vgb encoding Vitreoscilla hemoglobin was performed. Introduction of these genes in double‐ or triple‐combination into strain S. diastatochromogenes 1628 led to greatly increased TM production. Transcription analysis revealed that higher TM production in the constructed recombinant strains resulted from an increase in transcriptional levels of toyG gene. At the end, among all these different recombinant strains, the strain S. diastatochromogenes 1628‐VGF, harboring vgb, frr, and toyG placed under the control of PermE*, exhibited the largest increase in TM production. Notably, TM produced by S. diastatochromogenes 1628‐VGF reached the highest level of 319.2 mg/L at 72 h, while TM yield of the original strain 1628 was 147.1 mg/L at 84 h. The high‐yield, energy‐saving strain 1628‐VGF constructed in this study shall be beneficial for the industrial production of TM.
Phosphorus and carbon budgets: mycorrhizal contribution in Hyacinthoides non-scripta (L.) Chouard ex Rothm. under natural conditions

summary The extent of host benefit from arbuscular mycorrhiza (AM) in terms of phosphorus (P) assimilation under natural conditions has rarely been demonstrated or quantified. An apparently obligately mycorrhizal host, Hyacinthoides non-scripta (L.) Chouard ex Rothm. , was selected and, throughout the season September-July 1989–90, entire clones were collected from a field site at frequent intervals without experimental modification of the host, its mycosymbiont or their environment. In a concurrent glasshouse experiment, sand-cultured non-mycorrhizal plants given a nutrient solution containing a supply of P were unable to assimilate sufficient to maintain tissue P content. We provide correlative evidence of mycorrhizal behaviour in an undisturbed, natural ecosystem by demonstrating the temporal coincidence of root colonization by mycorrhizal fungi and the inflow of phosphorus in adult H. non-scripta. Annual carbon (biomass) and phosphorus budgets are described. Carbon was reallocated from the resting bulb, first for root production and, later, to developing leaves and inflorescences. A similar pattern was observed in P allocation. A substantial amount of P was lost in seed, leaves, roots and scapes shed at the end of a season, when bulb biomass had increased, but P content had not.