Miracle-dz/UniFAR-FTUs huggingface dataset:
Predictive Performance of the Simplified Acute Physiology Score (SAPS) II and the Initial Sequential Organ Failure Assessment (SOFA) Score in Acutely Ill Intensive Care Patients: Post-Hoc Analyses of the SUP-ICU Inception Cohort Study

Purpose Severity scores including the Simplified Acute Physiology Score (SAPS) II and the Sequential Organ Failure Assessment (SOFA) score are used in intensive care units (ICUs) to assess disease severity, predict mortality and in research. We aimed to assess the predictive performance of SAPS II and the initial SOFA score for in-hospital and 90-day mortality in a contemporary international cohort. Methods This was a post-hoc study of the Stress Ulcer Prophylaxis in the Intensive Care Unit (SUP-ICU) inception cohort study, which included acutely ill adults from ICUs across 11 countries (n = 1034). We compared the discrimination of SAPS II and initial SOFA scores, compared the discrimination of SAPS II in our cohort with the original cohort, assessed the calibration of SAPS II customised to our cohort, and compared the discrimination for 90-day mortality vs. in-hospital mortality for both scores. Discrimination was evaluated using areas under the receiver operating characteristics curves (AUROC). Calibration was evaluated using Hosmer-Lemeshow’s goodness-of-fit Ĉ-statistic. Results AUROC for in-hospital mortality was 0.80 (95% confidence interval (CI) 0.77–0.83) for SAPS II and 0.73 (95% CI 0.69–0.76) for initial SOFA score (P<0.001 for the comparison). Calibration of the customised SAPS II for predicting in-hospital mortality was adequate (P = 0.60). Discrimination of SAPS II was reduced compared with the original SAPS II validation sample (AUROC 0.80 vs. 0.86; P = 0.001). AUROC for 90-day mortality was 0.79 (95% CI 0.76–0.82; P = 0.74 for comparison with in-hospital mortality) for SAPS II and 0.71 (95% CI 0.68–0.75; P = 0.66 for comparison with in-hospital mortality) for the initial SOFA score. Conclusions The predictive performance of SAPS II was similar for in-hospital and 90-day mortality and superior to that of the initial SOFA score, but SAPS II’s performance has decreased over time. Use of a contemporary severity score with improved predictive performance may be of value.
Suppressed autophagy flux in skeletal muscle of an amyotrophic lateral sclerosis mouse model during disease progression

Accumulation of abnormal protein inclusions is implicated in motor neuron degeneration in amyotrophic lateral sclerosis (ALS). Autophagy, an intracellular process targeting misfolded proteins and damaged organelles for lysosomal degradation, plays crucial roles in survival and diseased conditions. Efforts were made to understand the role of autophagy in motor neuron degeneration and to target autophagy in motor neuron for ALS treatment. However, results were quite contradictory. Possible autophagy defects in other cell types may also complicate the results. Here, we examined autophagy activity in skeletal muscle of an ALS mouse model G93A. Through overexpression of a fluorescent protein LC3‐RFP, we found a basal increase in autophagosome formation in G93A muscle during disease progression when the mice were on a regular diet. As expected, an autophagy induction procedure (starvation plus colchicine) enhanced autophagy flux in skeletal muscle of normal mice. However, in response to the same autophagy induction procedure, G93A muscle showed significant reduction in the autophagy flux. Immunoblot analysis revealed that increased cleaved caspase‐3 associated with apoptosis was linked to the cleavage of several key proteins involved in autophagy, including Beclin‐1, which is an essential molecule connecting autophagy and apoptosis pathways. Taking together, we provide the evidence that the cytoprotective autophagy pathway is suppressed in G93A skeletal muscle and this suppression may link to the enhanced apoptosis during ALS progression. The abnormal autophagy activity in skeletal muscle likely contributes muscle degeneration and disease progression in ALS.
The Needfinding Machine

Robotics and automation technologies have begun to extend ubiquitous computing to include interactive objects with physical and social agency. My thesis, the Needfinding Machine, explores using social robots as design tools for understanding people and creating rich adaptive user experiences. In essence, the Needfinding Machine enables a conversation between a designer and a person \textit{through} a social robot. This conversation can support designers during needfinding and enable future social robots to elicit meaningful information from users.
Influence Analysis in the Blogosphere

In this paper we analyze influence in the blogosphere. Recently, influence analysis has become an increasingly important research topic, as online communities, such as social networks and e-commerce sites, playing a more and more significant role in our daily life. However, so far few studies have succeeded in extracting influence from online communities in a satisfactory way. One of the challenges that limited previous researches is that it is difficult to capture user behaviors. Consequently, the influence among users could only be inferred in an indirect and heuristic way, which is inaccurate and noise-prone. In this study, we conduct an extensive investigation in regard to influence among bloggers at a Japanese blog web site, BIGLOBE. By processing the log files of the web servers, we are able to accurately extract the activities of BIGLOBE members in terms of writing their blog posts and reading other member's posts. Based on these activities, we propose a principled framework to detect influence among the members with high confidence level. From the extracted influence, we conduct in-depth analysis on how influence varies over different topics and how influence varies over different members. We also show the potentials of leveraging the extracted influence to make personalized recommendation in BIGLOBE. To our best knowledge, this is one of the first studies that capture and analyze influence in the blogosphere in such a large scale.
Nonlinear Local Metric Learning for Person Re-identification

Person re-identification aims at matching pedestrians observed from non-overlapping camera views. Feature descriptor and metric learning are two significant problems in person re-identification. A discriminative metric learning method should be capable of exploiting complex nonlinear transformations due to the large variations in feature space. In this paper, we propose a nonlinear local metric learning (NLML) method to improve the state-of-the-art performance of person re-identification on public datasets. Motivated by the fact that local metric learning has been introduced to handle the data which varies locally and deep neural network has presented outstanding capability in exploiting the nonlinearity of samples, we utilize the merits of both local metric learning and deep neural network to learn multiple sets of nonlinear transformations. By enforcing a margin between the distances of positive pedestrian image pairs and distances of negative pairs in the transformed feature subspace, discriminative information can be effectively exploited in the developed neural networks. Our experiments show that the proposed NLML method achieves the state-of-the-art results on the widely used VIPeR, GRID, and CUHK 01 datasets.
Research in Spelling : Implications for Adult Basic Education

Literacy has been likened to a societal currency (Kirsch, Jungeblut, Jen-kins, & Kolstad, 1993). In this chapter, we consider how spelling ability might contribute to the value of that currency and the ways in which adult basic literacy instruction can support that contribution. Over the last few centuries, society has been increasing the value it places on accurate spelling , and spelling diffi cult words has now become a mark of a good education. Gerber and Hall (1987) noted, " The ability to spell is still imbued by an admiring public with connotations of studiousness, literacy, and intelligence " (p. 34). In the United States, the fact that we hold an annual National Spelling Bee in Washington, DC, attests to the cultural value that is placed on correct spelling, for its own sake, even today. A recent study revealed that the perception, among their peers, of college students' writing ability and even of intelligence is negatively affected by the presence of a large number of spelling errors in a piece of writing
A Unified Checklist for Observational and Experimental Research in Software Engineering (Version 1)

Current checklists for empirical software engineering cover either experimental research or case study research but ignore the many commonalities that exist across all kinds of empirical research. Identifying these commonalities, and explaining why they exist, would enhance our understanding of empirical research in general and of the differences between experimental and case study research in particular. In this report we design a unified checklist for empirical research, and identify commonalities and differences between experimental and case study research. We design the unified checklist as a specialization of the general engineering cycle, which itself is a special case of the rational choice cycle. We then compare the resulting empirical research cycle with two checklists for experimental research, and with one checklist for case study research. The resulting checklist identifies important questions to be answered in experimental and case study research design and reports. The checklist provides insights in two different types of empirical research design and their relationships. Its limitations are that it ignores other research methods such as meta-research or surveys. It has been tested so far only in our own research designs and in teaching empirical methods. Future work includes expanding the comparison with other methods and application in more cases, by others than ourselves.
The Role of Work-Group Emotional Intelligence in Learning Organizations: A Case Study of the Greek Public Sector

The purpose of this paper is to explore the impact of Emotional Intelligence at work-group level on Learning Organization, examining five dimensions of L.O. according to Senge’s model, within a framework of Greek Public Administration reform. The research was conducted among Greek Independent Administrative Authorities, a modern European institution that among others guarantees transparency and optimum performance, leading to upgraded public sector services. Our research is a quantitative research consisting of 257 valid questionnaires out of a sample of 300 employees. Our research highlights the strong correlation between Work-group Emotional Intelligence and Learning Organization. A constructive emotional climate affects the vision of the organization, while emotions have an impact on employees’ attitudes/behaviours and on the learning process within the group as well as on the diffusion of information. Finally, our research demonstrated that emotional intelligence affects the personal improvement and development of employees. Managers should focus on developing more emotionally intelligent employees by cultivating an emotional environment that promotes positive behaviours, system thinking and group learning. Thus, the benefits generated can be identified at both individual and organizational level, including higher levels of employees’ personal development, better communication processes and implementing the organization’s vision.
Comparative study on different adaptation approaches concerning a sip and puff controller for a powered wheelchair

Advance technologies are used to overcome a wide range of deficiencies for driving a powered wheelchair. Tetraplegia is one of the cases where complex and expensive interfaces are used for this issue. One interesting solution for this kind of deficiency consists of using a sip and puff interface. It is a simple and inexpensive method but it has two important limitations that restrict its practical use. The first one is in the reduced degree of freedom. The second one is in the tiring driving process. In order to minimize the driving effort for a given trajectory or for an unknown trajectory, this paper presents an optimal adaptation of the controller parameters. The adaptation could be done statically or dynamically according to the environment requirements. The controller is validated by means of simulations applied to three different cases: 1- the complete pathway is defined, 2- the pathway is divided to sub-paths and 3- the pathway is unknown. The first two cases are processed by means of averaging the pathway parameters and the third one by using a fuzzy controller.
General Overview on Nontuberculous Mycobacteria, Biofilms, and Human Infection

Nontuberculous mycobacteria (NTM) are emergent pathogens whose importance in human health has been growing. After being regarded mainly as etiological agents of opportunist infections in HIV patients, they have also been recognized as etiological agents of several infections on immune-competent individuals and healthcare-associated infections. The environmental nature of NTM and their ability to assemble biofilms on different surfaces play a key role in their pathogenesis. Here, we review the clinical manifestations attributed to NTM giving particular importance to the role played by biofilm assembly.
On electromagnetic duality in locally supersymmetric N=2 Yang-Mills theory

We consider duality transformations in N=2 Yang--Mills theory coupled to N=2 supergravity, in a manifestly symplectic and coordinate covariant setting. We give the essential of the geometrical framework which allows one to discuss stringy classical and quantum monodromies, the form of the spectrum of BPS saturated states and the Picard--Fuchs identities encoded in the special geometry of N=2 supergravity theories.
TC-STAR:Specifications of Language Resources and Evaluation for Speech Synthesis

In the framework of the EU funded project TC-STAR (Technology and Corpora for Speech to Speech Translation),research on TTS aims on providing a synthesized voice sounding like the source speaker speaking the target language. To progress in this direction, research is focused on naturalness, intelligibility, expressivity and voice conversion both, in the TC-STAR framework. For this purpose, specifications on large, high quality TTS databases have been developed and the data have been recorded for UK English, Spanish and Mandarin. The development of speech technology in TC-STAR is evaluation driven. Assessment of speech synthesis is needed to determine how well a system or technique performs in comparison to previous versions as well as other approaches (systems & methods). Apart from testing the whole system, all components of the system will be evaluated separately. This approach grants better assesment of each component as well as identification of the best techniques in the different speech synthesisprocesses.This paper describes the specifications of Language Resources for speech synthesis and the specifications for evaluation of speech synthesis activities.
Motor Improvement Using Motion Sensing Game Devices for Cerebral Palsy Rehabilitation

ABSTRACT The authors aimed to investigate the effects of an intervention based on interactive game set with the movement sensor Kinect on children with cerebral palsy (CP). Twenty-eight participants were recruited. Their age was between 3 and 12 years old, and rated as level I, II, or III on the Gross Motor Function Classification System. They played two games from the Xbox 360 Kinect system and were evaluated using the Gross Motor Function Measure (GMFM) after a period of 8 weeks. The intervention led to significant motor function improvement as increase of the global scores on the GMFM (p < .001). Rehabilitation interventions using the Xbox 360 Kinect interactive games may represent useful tools for children with CP.
α-mutual information

Renyi entropy and Renyi divergence evidence a long track record of usefulness in information theory and its applications. Alfred Rényi never got around to generalizing mutual information in a similar way. In fact, in the literature there are several possible ways to accomplish such generalization, most notably those suggested by Suguru Arimoto, Imre Csiszár, and Robin Sibson. We collect several interesting properties and applications of the proposal by Sibson, hopefully making a case for its more widespread adoption.
Rethinking researcher–teacher roles and relationships in educational action research through the use of Nel Noddings’ ethics of care

ABSTRACT Action research approaches have evolved out of a criticism of previous research traditions, where teachers have been seen as research objects, at risk of being marginalized. Such approaches have also arisen out of the view that teaching, learning, and educational research are interrelated. In action research, teachers are seen as professionals, raising their status to subjects, conducting own research. The research is carried out with or by people rather than on someone, which changes the roles and relationships. Ethical dilemmas can arise, especially evident in action research, where the distinctions between researcher and researched are blurred or removed altogether. This paper aims to explore the changing roles and relationships between researchers and teachers in action research through a philosophical analysis based on the writings of Nel Noddings, especially the concept of ethics of care. The analysis creates an opportunity for a rethinking of researcher–teacher roles, focusing on responsibility and knowledge as well as reciprocity and communication. Based on the author’s own action research experiences, various dilemmas are discussed. Obstacles to and opportunities for developing caring relationships between researchers and teachers will also be highlighted. The implications of the study include valuing both researcher and teacher expertise and learning to understand each other’s perspectives as well as giving tailored care. It is also vital to find strategies to contextualize and enact these views and beliefs within the researcher–teacher relationship. Neither researchers nor teachers will have total control over the process, as they stay open to each other’s perspectives and needs based on a caring relationship.
A circular-projection based digital image stabilization algorithm and its implementation for rotating image sequences

In this paper, a new digital image stabilization (DIS) algorithm based on Circular-Projection is proposed to stabilize videos captured by self-rotating crafts. Considering the features of rotation movements and requirements of real-time, polar transformation and gradient projection are integrated into the algorithm, and DaVinci DM6446 ARM+DSP dual-core platform is utilized to build the system. The experimental results show that the proposed algorithm with this embedded system can achieve good stabilizing accuracy with processing speed of 38.3 fps for 480×320 video sequences.
A Robust Preconditioner with Low Memory Requirements for Large Sparse Least Squares Problems

This paper describes a technique for constructing robust preconditioners for the CGLS method applied to the solution of large and sparse least squares problems. The algorithm computes an incomplete LDLT factorization of the normal equations matrix without the need to form the normal matrix itself. The preconditioner is reliable (pivot breakdowns cannot occur) and has low intermediate storage requirements. Numerical experiments illustrating the performance of the preconditioner are presented. A comparison with incomplete QR preconditioners is also included.
Introduction to supersymmetric gauge theories

In these lectures I present a basic introduction to supersymmetry, especially to N=1 supersymmetric gauge theories and their renormalization, in the Wess-Zumino gauge. I also discuss the various ways supersymmetry may be broken in order to account for the lack of exact supersymmetry in the actual world of elementary particles.
Verification of Web service flows with model-checking techniques

Web service is an emerging software technology to use remote services in the Internet. As it becomes pervasive, some "language" to describe Web service flows is needed to combine existing services flexibly. The flow essentially describes distributed collaborations and is not easy to write and verify, while the fault that the flow description may contain can only be detected at runtime. The faulty flow description is not desirable because a tremendous amount of publicly shared network resources are consumed. The verification of the Web service flow prior to its execution in the Internet is mandatory. This paper proposes to use the software model-checking technology for the verification of the Web service flow descriptions. For a concrete discussion, the paper adapts WSFL (Web Services Flow Language) as the language to describe the Web service flows, and uses the SPIN model-checker for the verification engine. The experiment shows that the software model-checking technology is usable as a basis for the verification of WSFL descriptions.
Parabolic pulse characterization in the far field of dispersion in a passive nonlinear fiber

We investigated properties of ultrashort parabolic pulses formed in the far field of dispersion in a passive nonlinear fiber through numerical modeling. It is found that the shape of pulses in the far field of dispersion differs from parabolic one, as compared to the near field of dispersion. However their temporal and spectral intensity shapes are more stable over the fiber.
Expanding the Detection of Traversable Area with RealSense for the Visually Impaired

The introduction of RGB-Depth (RGB-D) sensors into the visually impaired people (VIP)-assisting area has stirred great interest of many researchers. However, the detection range of RGB-D sensors is limited by narrow depth field angle and sparse depth map in the distance, which hampers broader and longer traversability awareness. This paper proposes an effective approach to expand the detection of traversable area based on a RGB-D sensor, the Intel RealSense R200, which is compatible with both indoor and outdoor environments. The depth image of RealSense is enhanced with IR image large-scale matching and RGB image-guided filtering. Traversable area is obtained with RANdom SAmple Consensus (RANSAC) segmentation and surface normal vector estimation, preliminarily. A seeded growing region algorithm, combining the depth image and RGB image, enlarges the preliminary traversable area greatly. This is critical not only for avoiding close obstacles, but also for allowing superior path planning on navigation. The proposed approach has been tested on a score of indoor and outdoor scenarios. Moreover, the approach has been integrated into an assistance system, which consists of a wearable prototype and an audio interface. Furthermore, the presented approach has been proved to be useful and reliable by a field test with eight visually impaired volunteers.