Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of age, sex and treatment on weight loss dynamics in obese people.

Objective : Evaluation of how sex, age and the kind of followed treatment affect weight loss and to explain weight loss dynamics in obese men and women. Material and Methods: A hundred and twenty obese participants (18 – 50 years; Body Mass Index (BMI) >30 and <34.9 kg/m 2 ) were randomly assigned to four treatments, namely, strength training (S; n = 30), endurance training (E; n = 30), a combination of S and E (SE; n = 30), and diet and physical recommendations group (C; n = 30). Each of the different training groups exercised three times per week during twenty-four weeks while having diet restrictions. Then, body weight changes were evaluated every fifteen days for each participant. Several equation models were developed and evaluated to determine the function that better represents weight loss dynamics. Results: There were no significant differences from the statistical viewpoint, in terms of global body weight change, either on the carried out treatment or on individual’s age. However, significant differences on the weight loss tendency were found due to the participant sex. Discussion: The effectiveness of different treatments for weight loss varies by sex and, based on our experimental observations, the most accurate model to capture the weight loss dynamics can be obtained through a quadratic function.
KRDB Research Centre Technical Report : Co-Design with children : the State of the Art

This report is an overview on co-design in an instructional context with intergenerational teams of adults and children aged 7–11 year old. Adults and children become design partners in the design development process of new technology. I will start by introducing the main ideas of co-design. Then I will focus on the user research methods used in co-design sessions. For describing them concretely, I will conclude my presentation by reporting on existing projects that have used these methods in their experiments.
How 3D Interaction Metaphors Affect User Experience in Collaborative Virtual Environment

In this paper we presents the results of our experimental study which aims to understand the impact of three interaction 3D metaphors (ray casting, GoGo, and virtual hand) on the user experience in a semi-immersive collaborative virtual environment (the Braccetto System). For each session, participants are grouped in twos to reconstruct a puzzle by an assemblage of cubes. The puzzle to reconstruct corresponds to a gradient of colors. We found that there is a significant difference in the user experience by changing the interaction metaphor on the copresence, awareness, involvement, collaborative effort, satisfaction usability, and preference. These findings provide a basis for designing 3D navigation techniques in a CVE.
An On-Chip Test Clock Control Scheme for Multi-Clock At-Speed Testing

To test timing-related faults between synchronous clocks, an at-speed test clock and an automatic test pattern generation scheme are needed. However, previous work on designing on-chip at-speed test clock controllers for multi-clock has quadratic increasing area overhead along with linearly increasing clocks. This paper presents a clock-chain based test clock control scheme using an internal phase-locked-loop (PLL) as the at-speed test clock generator, which supports at-speed testing for inter-clock domain and intra-clock domain logic. Experimental results demonstrate that the proposed design has low area overhead when increasing the number of clocks.
Researches on Combinations of Auxiliary Problems in ASO (Alternating Structure Optimization) Algorithm

Recently, a semi-supervised learning algorithm called ASO (Alternating Structure Optimization) has been proposed, which belongs to linear structural learning. It utilizes a number of auxiliary problems (APs) with unlabelled data and then extracts common structural parameter of APs to improve the performances of the target problems (TPs). How to select the appropriate APs is the keystone of ASO algorithm. This paper proposes another principle of APs selection: combinations. It determines optimal ratios between multi-combinations when proper total amounts of APs are given. Besides, we also analyze how to select appropriate total amounts. Both theoretical analysis and experimental results indicate that the principle of combinations is credible. Comparing with the principle of diversity that we have proposed, this principle immensely reduces the computational complexity. While the performances keep invariable.
Orchestrating the Deployment of Computations in the Cloud with Conductor

When organizationsmove computation to the cloud, they must choose from a myriad of cloud services that can be used to outsource these jobs. The impact of this choice on price and performance is unclear, even for technical users. To further complicate this choice, factors like price fluctuations due to spot markets, or the cost of recovering from faults must also be factored in. In this paper, we present Conductor, a system that frees cloud customers from the burden of deciding which services to use when deploying MapReduce computations in the cloud. With Conductor, customers only specify goals, e.g., minimizing monetary cost or completion time, and the system automatically selects the best cloud services to use, deploys the computation according to that selection, and adapts to changing conditions at deployment time. The design of Conductor includes several novel features, such as a system to manage the deployment of cloud computations across different services, and a resource abstraction layer that provides a unified interface to these services, therefore hiding their low-level differences and simplifying the planning and deployment of the computation. We implemented Conductor and integrated it with the Hadoop framework. Our evaluation using AmazonWeb Services shows that Conductor can find very subtle opportunities for cost savings while meeting deadline requirements, and that Conductor incurs a modest overhead due to planning computations and the resource abstraction layer.
High-throughput pipeline for the de novo viral genome assembly and the identification of minority variants from Next-Generation Sequencing of residual diagnostic samples Running head De novo assembly and variants from NGS clinical samples Authors

Motivation: The underlying genomic variation of a large number of pathogenic viruses can give rise to drug resistant mutations resulting in treatment failure. Next generation sequencing (NGS) enables the identification of viral quasi-species and the quantification of minority variants in clinical samples; therefore, it can be of direct benefit by detecting drug resistant mutations and devising optimal treatment strategies for individual patients. Results: The ICONIC (InfeCtion respONse through vIrus genomiCs) project has developed an automated, portable and customisable high-throughput computational pipeline to assemble not peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was . http://dx.doi. org/10.1101/035154 doi: bioRxiv preprint first posted online Dec. 24, 2015;
A novel automatic method for vessel tortuosity evaluation

Tortuosity evaluation of retinal or conjunctival vessels is one of the significant steps in early treatment of diabetic retinopathy. Despite the importance of this field, a few techniques have been proposed. In this paper, we proposed a new automatic algorithm for measuring vessel tortuosity based on Non Subsampled Contourlet Transform (NSCT). Major vessels and their directional information are extracted using NSCT in the first step. Then local vessel curvature is computed using obtained NSCT information and entire vessel network tortuosity is computed by combination of these local curvature values. Accuracy of our algorithm is evaluated by spearman correlation of our result and a set of images which are ordered by an ophthalmologist in ascending manner of tortuosity. We have shown that our algorithm achieves high accuracy in evaluation of vessels network tortuosity beside less computational time by reducing major steps of traditional tortuosity evaluation algorithm.
CRF-based active learning for Chinese named entity recognition

Conditional Random Fields (CRFs) have been used for many sequence labeling tasks and got excellent results. Further, the supervised model strongly depends on the huge training data. Active learning is a different way rather than relying on a large amount random sampling. However, random sampling constructively participates in the optimal choosing training examples. Based on different query strategies, active learning can combine with other machine learning methods to reduce the annotation cost while maintaining the accuracy. This paper proposes a new active learning strategy based on Information Density (ID) integrated with CRFs for Chinese Named Entity Recognition (NER). On Sighan bakeoff 2006 MSRA NER corpus, an F1 score of 77.2% is achieved by using only 10,000 labeled training sentences chosen by the proposed active learning strategy.
Realizing Non-Foster Reactive Elements Using Negative-Group-Delay Networks

An intimate relation is established between non-Foster reactive elements and loss-compensated negative-group-delay (NGD) networks. It is shown that any possible network configuration containing a class of non-Foster elements operates as an NGD network. Likewise, it is demonstrated that a loss-compensated NGD network represents a reactive network with a non-Foster behavior. Consequently, these two properties can be intimately linked together and NGD networks can be utilized to implement non-Foster elements, such as negative capacitors and inductors. This result introduces another perspective in realizing non-Foster reactive elements, leading to new designs that are well behaved and more predictable in terms of stability and operation than traditional designs using negative impedance inverters and negative impedance converters. Based on this concept, loss-compensated NGD networks are proposed for realizing high-quality non-Foster reactive elements. Furthermore, entirely passive non-Foster elements with a limited quality ( Q) factor are proposed for which the minimum Q factor and the maximum achievable bandwidth are inversely related. It is shown that the design of non-Foster reactive elements using NGD networks can lead to the realization of standalone unilateral non-Foster reactive elements in a certain bandwidth. Examples of such non-Foster reactive elements and networks are demonstrated experimentally and shown to be stable.
Morphological scale-space to differentiate microstructures of food products

We will construct a morphological scale-space using closings at logarithmically sampled scales. From this, we derive a measure for the pore-size distribution. We will apply this method to images of food products, acquired using confocal microscopy, to demonstrate how it can be used to differentiate the microstructure of these products. The microstructures are responsible for important macroscopic properties (firmness, foaming characteristics and mouth-feel). Two applications will be discussed: analysis of monoglycerides, and detection of subtle changes in the microstructure of a dairy product due to different treatments.
Isolation of cDNA clones coding for IgE autoantigens with serum IgE from atopic dermatitis patients

Recently we demonstrated that a high percentage of atopic dermatitis (AD) patients displayed specific immunoglobulin E reactivity to human proteins. Here we show that IgE autoreactivity is found predominantly in AD patients with severe skin manifestations and reveal the molecular nature of four IgE autoantigens. An expression cDNA library constructed from a human epithelial cell line (A 431) was screened with serum IgE from two AD patients. DNA sequence analysis of three IgE‐reactive clones identified the α‐chain of the nascent polypeptide‐associated complex, cytokeratin type II, and the BCL7B oncogen as atopy‐related IgE autoantigens (ara). The fourth cDNA coded for an IgE autoantigen containing a typical calcium binding motif that occurred in histogenetically different cells and tissues (keratinocytes, muscle, brain). Recombinant Escherichia coli‐expressed IgE autoantigens bound IgE from AD but not from patients with other immunologically mediated disorders (graft vs. host disease, systemic lupus erythematosus) and elicited immediate type skin reactions in AD patients. In serum samples collected from an AD patient over a period of 5 years, IgE anti‐ara NAC antibody levels peaked during disease exacerbation. Our finding that ara BCL7B was detected in serum bound to IgE antibodies suggests that intracellular IgE autoantigens can become released after tissue damage and may occur as IgE immune complexes. Via binding to antigen presenting cells as well as to effector cells, IgE autoantigen immune complexes may contribute to exacerbation and/or perpetuation of severe atopic diseases even in the absence of exogenous allergens. —Natter, S. , Seiberler, S. , Hufnagl, P., Binder, B. R. , Hirschl, A. M. , Ring, J., Abeck, D. , Schmidt, T. , Valent, P., Valenta, R. Isolation of cDNA clones coding for IgE autoantigens with serum IgE from atopic dermatitis patients. FASEB J. 12, 1559– 1569 (1998)
Kernel Data Structure-based Runtime Monitoring

In this paper, a kernel data structure-based runtime monitor is presented for commodity systems in microkernel architecture. Inside the monitor, the protection specification of the kernel data structure has been introduced to check system runtime consistency. The specification that consists of a set of consistency constraints and corresponding repair actions provides the normal behavior regulations for kernel objects. During its runtime deployment, once inconsistency has been detected, the monitor will use related actions to recover the system.The evaluation experiment results indicate our prototype system could correctly detect the presence of security attacks and system anomaly behavior. Moreover the monitor system is fully softwarebased without introducing any specific hardware. And the monitor also requires no modifications to the ABI between the application program and guest OS, so that legacy applications could be reused.
Building Effective Mentorship Dyads with the Use of Attachment Theory

Summary: Utilizing Bowlby and Ainsworth’s Attachment Theory to pair mentorship dyads, addressing personality differences the number one reason reported as to why formalized mentor relationships fail. Review of mentorship as an evidence based practice and a sample formalized program will also be demonstrated. Learning Activity: LEARNING OBJECTIVES EXPANDED CONTENT OUTLINE 1. Learners will be able to identify personality differences as the number one reason given for the failure of formalized mentor relationships and possible consequences for the mentor and protégé if the relationship fails. Data will be presented from numerous studies on the consequences for both mentors and protege if a mentorship relationship fails. The number one reason given for the failure of mentor relationships is personality differences. Literature Review on personality tests was completed to provide a recommended instrument. 2. Learners will be able to defend application of Attachment Theory concepts to mentorship and how these will contribute to strategies that enhance mentor relationships and healthy work environments. Application Theory developed by John Bowlby and Mary Ainsworth is discussed with application of the Adult Attachment Tool to a formalized mentorship program to specifically address the issues identified in the literature. Abstract Text: Scope of AbstractText: Scope of Abstract New nurse educators often characterize their transition into the professional faculty role as being fraught with anxiety, uncertainty, and a general lack of confidence (Ferguson, 2011). A frequently identified factor that hinders the role transition is a lack of formal pedagogical education (Schoening, 2013) One evidencebased solution to combat this emotionally tumultuous challenge is through the use of formalized mentoring programs (Ferguson, 2011). According to Brody et al. (2016), 82% of mentored nurse educators report a willingness to mentor others, and 95.5% of the mentored nurse educators would recommend mentorship to new nurse educators. Unfortunately, despite the many benefits of formalized mentorship programs they are not common in nursing education and faculty culture.
Dynamic Quantizer Design for Hidden Markov State Estimation Via Multiple Sensors With Fusion Center Feedback

This paper considers the state estimation of hidden Markov models by sensor networks. The objective is to minimize the long term average of the mean square estimation error for the underlying finite state Markov chain. By employing feedback from the fusion center, a dynamic quantization scheme for the sensor nodes is proposed and analyzed by a stochastic control approach. Dynamic rate allocation is also considered when the sensor nodes generate mode dependent measurements
JAVA APPLICATIONS COMPREHENSION BY DISCOVERING CLUSTERS OF RELATED CLASSES

Software maintenance is an important phase of software lifecycle consuming the majority of effort. Program comprehension is the most time consuming activity during software maintenance. Data mining techniques have been used to support program comprehension for large software systems. This paper presents an approach to extract useful knowledge from Java source/byte code, and apply clustering to discover groups of closely related classes. The groups of classes can assist programmers to know the high level structure of large software systems without prior knowledge, and programmers can learn the classes in the same group together. The groups of classes are formed based on different types of coupling between classes, and having common characteristics, such as having the same superclass. A prototype system has been developed and evaluated using a medium sized Java application.
Graph-Transformation Based Support for Model Evolution

During model-driven software development, we are inevitably confronted with design models that contain a wide variety of design defects. Interactive tool support for improving the model quality by resolving these defects in an automated way is therefore indispensable. In this paper, we report on the development of such a tool, based on the underlying formalism of graph transformation. Due to the fact that the tool is developed as a front-end of the AGG Engine, a general purpose graph transformation engine, it can exploit some of its interesting built-in mechanisms such as critical pair analyis and the ability to reason about sequential dependencies. We explore how this can help to improve the process of quality improvement, and we compare our work with related research. Copyright notice This document is for educational use only. it is meant to serve as reading material for the SegraVis Advanced School on Visual Modelling Techniques. The document is based on a co-authored paper that has been submitted for publication elsewhere. The main difference is that the current versions contains many annotations. About this document At the end of each section, optional exercises are added to enable the reader to gain a deeper understanding of the underlying mechanisms. For some of the exercises, the AGG GUI will need to be used. It can be downloaded from the website http://tfs.cs. tu-berlin.de/agg/. Other exercices may require the use of the SIRP tool that is reported on in this paper. It can be downloaded from the SegraVis school website. Additional reading material related to this paper can be found in [1–3].
Anthropomorphism From Self-Extension and Self-Expansion Processes: an Assemblage Theory Approach to Interactions Between Consumers and Smart Devices

We use an assemblage theory framework to evaluate anthropomorphism experiences from self-extension and self-expansion processes when consumers and smart devices interact. Results show that overall, anthropomorphism is greater when the consumer has less compared to more control. Additionally, device complexity moderates whether anthropomorphism occurs through a self-extension or self-expansion process.
Neuroprotective Effect of Steamed and Fermented Codonopsis lanceolata

Codonopsis lanceolata has been used as an herbal medicine for several lung inflammatory diseases, such as asthma, tonsillitis, and pharyngitis. Previously, we showed the neuroprotective effect of steamed and fermented C. lanceolata (SFC) in vitro and in vivo. In the current study, the treatment of HT22 cells with SFC decreased glutamate-induced cell death, suggesting that SFC protected HT22 cells from glutamate-induced cytotoxicity. Based on these, we sought to elucidate the mechanisms of the neuro-protective effect of SFC by measuring the oxidative stress parameters and the expression of Bax and caspase-3 in HT22 cells. SFC reduced contents of ROS, Ca2+ and NO. Moreover, SFC restored contents of glutathione and glutathione reductase as well as inhibited Bax and caspase-3 activity in HT22 cells. These results indicate that steamed and fermented C. lanceolata (SFC) extract protected HT22 cells by anti-oxidative effect and inhibition of the expression of Bax and caspase-3.