Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Algorithm for Line Routing in Hierarchical Diagrams

Hierarchical diagrams are well-suited for visualizing the structure and decomposition of complex systems. With the advent of UML 2.0, in particular the new composite structure diagram, hierarchical models have entered the modeling mainstream. However, the current tools poorly support hierarchical modeling and visualization. Simple explosive zooming is the most common means for navigating through hierarchies; some tools even visualize the complete hierarchy in a single large diagram. The line routing algorithms used by the current tools are poorly suited to this task: for example, they produce lines that run across nodes or overlap with other lines. In this paper, we present a novel algorithm for line routing in hierarchical models which, together with our previous work on node positioning, yields visualizations of hierarchical models that can easily be browsed and edited. In particular, our algorithm (i) produces an esthetically appealing layout, (ii) routes in real-time, and (iii) preserves the secondary notation of the diagrams as far as possible.
A Novel Matrix Representation of Discrete Biomedical Signals

In this work we propose a novel symmetric square matrix representation of one or more digital signals of finite equal length. For appropriate window length and sliding paradigm this matrix contains useful information about the signals in a two dimensional image form. Then this representation can be treated either as an algebraic matrix or as a geometric image. We have shown applications of both on human multichannel intracranial electroencephalogram (iEEG). In the first application we have shown that for certain patients the highest eigenvalue of the matrix obtained from the epileptic focal channels goes up during a seizure. The focus of this paper is on an application of the second concept, by which we have come up with an automatic seizure detection algorithm on a publicly available benchmark data. Except for delay in detection in all other aspects the new algorithm outperformed the detection performance based on a support vector machine based algorithm. We have also indicated how this sparse random matrix representation of brain electrical signals can encode the activities of the brain.
Moderate Resolution Imaging Spectroradiometer Vegetation Indices in the Colorado Plateau , USA Final Report Cooperative Agreement No . H 1200040001 Task Agreement J 1344040053 Project No USU-03

The National Park Service (NPS) Vital Signs Monitoring program is an aggressive effort to track ecosystem status in the 270 park units. For large and remote parks, remote sensing may be used as an early warning system to detect anomalous vegetation conditions. Here, we evaluated the ability of the Moderate Resolution Imaging Spectroradiometer 250m Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and red, near infra-red, and blue channels to represent relative ground-measured vegetation conditions. Using an AccuPAR LP-80 PAR/LAI Ceptometer, LAI-2000 Plant Canopy Analyzer, and First Growth digital camera, we sampled plant area index (PAI) and green fractional cover (GFC) at 4 sites along a bioclimatic gradient representing semi-arid woodland, mixed grassland/shrubland, and grassland plant functional types. In 14 visits from June 2005 to October 2005, we intensively sampled each site at a spatial resolution directly comparable to 4 MODIS pixels. PAI was always less than 1.0 and often less than 0.4 and GFC was rarely greater than 5%. Likely due to such low plant cover and instrument noise, correlation coefficients between instruments were rarely significant. From both ground and MODIS data, the woodland site showed little evidence of phenological variability. For the other sites, all with a deciduous grassland component, the LP-80 was significantly and consistently related to NDVI (r 0.57 to 0.79, slope 0.76 to 0.89) and less consistently to EVI. In spite of minimal base and amplitude of PAI and NDVI, it appears that MODIS NDVI is capable of resolving extremely subtle changes in herbaceous plant canopies and is therefore a promising tool for use in the Vital Signs Monitoring program.
Dietary Quantity and Diversity among Anemic Pregnant Women in Madura Island, Indonesia

Dietary diversity and quantity are important for pregnant women, particularly anemic pregnant women. This study aimed to analyze the association between dietary quantity and diversity among anemic pregnant women. This cross-sectional study was conducted in 2017 at Madura Island, Indonesia, and involved 152 anemic pregnant women. Hemoglobin concentration was analyzed by the cyanmethemoglobin method. Dietary quantity was measured by the 2 × 24 h recall. Dietary diversity was determined by Minimum Dietary Diversity for Women of Reproductive Age (MDD-W). Spearman's rank association was performed to analyze the association between dietary diversity and quantity. The median of hemoglobin concentration was 10.1 g/dL, and 57.2% pregnant women had mild anemia. Most of the pregnant women had low adequacy levels of energy and macro- and micronutrients (except for iron). More than half (57.9%) of anemic pregnant women had reached minimum dietary diversity. Family size (p=0.048) and gestational age (p=0.004) had negative associations with dietary diversity. Dietary diversity had positive associations with energy (p=0.029), protein (p=0.003), vitamin A (p=0.001), vitamin C (p=0.004), and zinc (p=0.015) adequacy levels. Dietary diversity had no significant association with calcium (p=0.078) and iron adequacy level (p=0.206). High prevalence of mild and moderate anemia was found among pregnant women in their third trimester. Anemic pregnant women already consumed food with minimum dietary diversity but did not meet dietary quantity. Increasing dietary quantity is a priority for anemic pregnant women.
Uptake and choice of commercial weight loss products and services by adults in the UK

Objectives: 1) To assess the use and reasons of choice of commercial weight loss products and services (CWLPS), 2) Critically assess the effectiveness of CWLPS. Methods: A mixed method study design was used to assess the use and reasons of choice of CWLPS (survey and Q-method) and investigate the effectiveness of CWLPS (systematic review). Results: Weight loss group based programmes such as Slimming World were the most popular type of CWLPS used. The Q-method study identified four different groups of participants who had similar needs for their preferred CWLPS, which mapped onto the different types of CWLPS available. The systematic review showed that CWLPS result in weight loss, although attrition rates are often quite high. Slimming groups such as Weight Watchers appeared the most effective. Discussion and conclusion: It is clear that most CWLPS are used, preferred,and effective for some people, at least for a short period of time. However,different users have different needs for their preferred CWLPS. The cost of a CWLPS is not a critical factor in its use, popularity, or effectiveness.
Parallel Manipulator of a Class RoboMech with Two End-Effectors

In this paper, the methods of structural and parametric synthesis of a RoboMech class parallel manipulator with two end-effectors are presented. This parallel manipulator is formed by connecting the two moving output objects with the fixed base by two passive, one active and two negative closing kinematic chains. Geometrical parameters of the active and negative closing kinematic chains are determined by the Chebyshev and least-square approximations. Index Terms Parallel manipulator, end-effector, structuralparametric synthesis.
Understanding System Integration in Healthcare-The View of Hospital Nurses

REQUIRED) The healthcare industry is undergoing an IT-enabled transformation via the adoption of integrated HIT systems. The transformation is partially a result of government mandate rather than a nature evolution of technology. Thus, the effectiveness of system integration in the healthcare industry may deviate from what we have observed in other industries. The current research attempts to enrich our understanding of how HIT users, hospital nurses in particular, perceive system integration in their workplace. A field study is conducted. The results reveal a lack of association among different aspects of system integration, suggesting that HIT users may not view system integration as a holistic feature of modern HIT systems.
Is "manovra" Really "del popolo"? Linguistic Insights into Twitter Reactions to the Annual Italian Budget Law

English. Relying on linguistic cues obtained by means of structural topic modelling as well as descriptive lexical analyses, this study contributes to the general understanding of the Twitter users’ response to the annual Italian budget law approved at the end of December 2018. Some topics contained in the dataset of tweets are procedural or generic, but besides those, it often emerges that Twitter users expressed their concern with respect to the provisions of this law. Supportive attitudes seem to be less frequent. This paper also advocates that findings from inductive studies on Twitter data should be interpreted with caution, since the nature of tweets might not be adequate for drawing far-reaching generalisations.
The Extent of Social Contribution of Venture Capital Organisations to Funded Financed Companies

The major objective lying behind the conduction of the present work lies in investigating the social advantages likely to be brought about by the venture capitalist to the funded firm. More specially, it treats the venturer’s financial contribution as based on a number of human resources management related practices. Overall, the reached results, relevant to a sample involving 150 companies proved to indicate that the financial participation of this mode of financial intermediation turns out to be partially associated with a social contribution. In effect, it has been discovered that a number of the advanced practices, suggested as social contribution relating measures, do not prove to stand as part of the changes targeted by the venture capitalist to take place in a bid to enhance the firm’s social performance, nor were they intended to further improve the added values already achieved. Actually, such a strategy could well reflect some special features characterize the Tunisian venture capital mode of financing.
Maxillary cyst pathological analysis and the ideas of non-surgical drug treatment

To analyze the nature of maxillary cysts and non-surgical treatment options ideas from the part of pathological. Methods: According to the cites of different cysts , 34 cases of maxillary sinus cysts were divided into three parts to receive different surgical operation treatment based on natural caliber Road, inferior meatus window pathway, the maxillary sinus approach, and the cysts were inspected by pathological analysis. Results: the pathological results: Among the 34 cases pathological examination, 30 cases were diagnosed as mucous cyst, and the others were retention cysts. Conclusions: the analysis of pathological method after the maxillary cyst operations provides new innovations and ideas for drug of choice for non-surgical treatment.
Current issues in epidemiogical studies of autism

Epidemiological surveys have increased in number and complexity. This paper focuses on a few selected issues that persist in the field of autism epidemiology today. Recent surveys have improved case ascertainment by including a regular school survey component, and they have consistently identified cases which were undiagnosed. However, the logistic of these surveys is complex, and the data analysis of these complex survey designs can lead to serious overand sometimes under-estimation of overall population prevalence. Other issues discussed concern techniques used to confirm and validate caseness in surveys. Surveys relying on mechanical use of diagnostic algorithms or single questionnaire answers are plagued with measurement error. The impact of the repeated changes in nosographical systems and the recent changes of DSM-5 are discussed. Issues specific to surveys of adults and preschoolers are briefly reviewed. Finally, contributions from international studies and the need for further cross-cultural comparisons are considered.
Typologies of Computation and Computational Models

We need much better understanding of information processing and computation as its primary form. Future progress of new computational devices capable of dealing with problems of big data, internet of things, semantic web, cognitive robotics and neuroinformatics depends on the adequate models of computation. In this article we first present the current state of the art through systematization of existing models and mechanisms, and outline basic structural framework of computation. We argue that defining computation as information processing, and given that there is no information without (physical) representation, the dynamics of information on the fundamental level is physical/ intrinsic/ natural computation. As a special case, intrinsic computation is used for designed computation in computing machinery. Intrinsic natural computation occurs on variety of levels of physical processes, containing the levels of computation of living organisms (including highly intelligent animals) as well as designed computational devices. The present article offers a typology of current models of computation and indicates future paths for the advancement of the field; both by the development of new computational models and by learning from nature how to better compute using different mechanisms of intrinsic computation.
Concentric set schematization

Sets can be visualized in various ways and settings. An important distinction between techniques is based on whether the elements have a spatial location that is to be used for the visualization; for example, the elements are cities on a map. Strictly adhering to such location may severely limit the visualization and force overlay, intersections and other forms of clutter. On the other hand, completely ignoring the spatial dimension omits information and may hide spatial patterns in the data. In this abstract, we present ongoing research on a method that is in between spatial and nonspatial visualizations. The main idea is to schematize (move) the spatial locations onto concentric circles, to improve the visualization of the set system while roughly maintaining spatial structure.
Making Predictive Coding Networks Generative

Predictive coding (PC) networks are a biologically interesting class of neural networks. Their layered hierarchy mimics the reciprocal connectivity pattern observed in the mammalian cortex, and they can be trained using local learning rules that approximate backpropagation [Bogacz, 2017]. However, despite having feedback connections that enable information to flow down the network hierarchy, discriminative PC networks are not generative. Clamping the output class and running the network to equilibrium yields an input sample that typically does not resemble the training input. This paper studies this phenomenon, and proposes a simple solution that promotes the generation of input samples that resemble the training inputs. Simple decay, a technique already in wide use in neural networks, pushes the PC network toward a unique minimum 2-norm solution, and that unique solution provably (for linear networks) matches the training inputs. The method also vastly improves the samples generated for nonlinear networks, as we demonstrate on MNIST.
New Dynamics and Trajectories of Agrarian Change in Bolivia: Regimes of Dispossession and the Rise of Brazil

New dynamics of agrarian change have emerged in Bolivia as a result of its insertion into what appears to be a transitioning ‘polycentric global food and agro-commodity regime’ (Borras et al 2012). With the onset and convergence of multiple crises (financial, food, climate, peak oil), coupled with the emerging economies of BRICS and MICs as new hubs of global capital accumulation, there has been a significant ‘rising global interest in farmland’ particularly for large-scale ‘flex crop’ plantations (Deininger and Byerlee 2011, Borras et al. 2012). These changing dynamics in the global political economy are resulting in a “spatial restructuring process” (McMichael 2013) of the global food regime, reshaping patterns of production, distribution, and consumption worldwide. With the rise of Brazil as a key factor in this process, Bolivian territory and its peoples have become subject to forms dispossession at the hand of capital accumulation in the agrarian sector. Dispossession in this context does not refer exclusively to physical displacement or expulsion of people from the land, but rather that which deprives people of their current and future access to and control over resources. Including one’s future access adds the necessary component of time, “acknowledging the sometimes long periods between acts of enclosure and dispossession and accumulation” (Kelly 2011:695).
A Survey on Knowledge Graph Embeddings with Literals: Which model links better Literal-ly?

Knowledge Graphs (KGs) are composed of structured information about a particular domain in the form of entities and relations. In addition to the structured information KGs help in facilitating interconnectivity and interoperability between different resources represented in the Linked Data Cloud. KGs have been used in a variety of applications such as entity linking, question answering, recommender systems, etc. However, KG applications suffer from high computational and storage costs. Hence, there arises the necessity for a representation able to map the high dimensional KGs into low dimensional spaces, i.e., embedding space, preserving structural as well as relational information. This paper conducts a survey of KG embedding models which not only consider the structured information contained in the form of entities and relations in a KG but also its unstructured information represented as literals such as text, numerical values, images, etc. Along with a theoretical analysis and comparison of the methods proposed so far for generating KG embeddings with literals, an empirical evaluation of the different methods under identical settings has been performed for the general task of link prediction.
Characterization of the genome of Oryctes baculovirus, a viral biocide of the insect pest Oryctes rhinoceros

Oryctes baculovirus is a viral biocide exploited for the control of the insect pest Oryctes rhinoceros. We have recently established a physical map of the genome of the Indian isolate of Oryctes baculovirus (OBV-KI). Here we examine the genomic relatedness between OBV-KI and OBV-PV505, the type isolate (originally from the Philippines), by DNA reassociation kinetics and by the use of restriction endonucleases. On the basis of differences in restriction-enzyme profiles between the two genomes, and previously reported differences in protein profiles and antigenic makeup, we propose the taxonomic status of a variant of Oryctes baculovirus for the Indian isolate.
On osteoporosis in elderly women

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Alibaba-AIC : Submission to Multi-Moments in Time Challenge 2019 ∗

This technical report describes the detail solution for Multi-Moments in Time Challenge 2019. We exploit and evaluate spatiotemporal feature learning model, such as C3D, (2+1)D convolution. And to learn the action class association in data, we use focal loss combined with label correlation loss as the loss function. Furthermore, we also explore the auditory modality to predict action categories. Our final submission to the challenge is an ensemble of the visual RGB model, Flow model and Audio model, achieving a mAP 67.0% on validation set.
Edge Affinity-based Management of Applications in Fog Computing Environments

Fog computing overcomes the limitations of executing Internet of Things (IoT) applications in remote Cloud datacentres by extending the computation facilities closer to data sources. Since most of the Fog nodes are resource constrained, accommodation of every IoT application within Fog environments is very challenging. Hence, we need to efficiently identify which set of applications should be deployed in Fog. It becomes even more complicated when the application characteristics in terms of urgency, size and flow of inputs are considered simultaneously. The necessity of time-optimized execution further intensifies the application management problem. In this work, we propose a policy for Fog environments that distributes application management tasks across the gateway and the infrastructure level. It classifies and places applications according to their Edge affinity. Edge affinity of an application denotes the relative intensity of different attributes coherent with its characteristics such as user-defined deadline, amount of data per input and sensing frequency of IoT devices, which are required to be addressed within Fog environments to meet its Quality of Service (QoS). The proposed policy also minimizes the service delivery time of applications in Fog infrastructure. Its performance is compared with existing application management policies in both iFogSim-simulated and FogBus-based real environments. The experiment results show that our policy outperforms others in combined QoS enhancement, network relaxation and resource utilization.
Fundamental Toxicological Sciences

Obesity is caused by a chronic positive energy balance, which not only increases the amount of lipid in adipose tissue, but also, in non-adipose tissue. Excessive accumulation of lipids in tissues may lead to cell dysfunction or cell death, a phenomenon known as lipotoxicity. The aim of this study was to investigate the effects of high-fat diet (HFD) feeding on the sciatic nerves of both male and female mice. HFD feeding induced increased mRNA levels of Bax and Bcl2 in HFD group of males only, although the accumulation of fatty acids in the sciatic nerves was induced by HFD feeding in the both sexes. To determine whether estrogen was involved in the inhibitory effects of HFD feeding-induced increased expression of apoptosis-related genes, ovariectomized (OVX) females were fed a normal diet (ND) or HFD with or without daily ethinylestradiol treatment for 1 week. In OVX mice, the mRNA levels of Bax and Bcl2 in HFD group were higher than in ND group. In contrast, in OVX mice treated with ethinylestradiol, there was no significant between ND and HFD groups. In conclusion, HFD induced apoptosis in the sciatic nerves of males, but not females, and estrogen had inhibitory effects on HFD-induced apoptosis in the sciatic nerves of females. Long-term feeding studies are needed to investigate the pathological effects on sciatic nerves of mice fed HFD as pathological findings were not observed under our study condition.