Miracle-dz/UniFAR-FTUs huggingface dataset:
Caveolin as a potential drug target for cardiovascular protection

Caveolae and caveolin are key players in a number of disease processes. Current research indicates that caveolins play a significant role in cardiovascular disease and dysfunction. The far-reaching roles of caveolins in disease and dysfunction make them particularly notable therapeutic targets. In particular, caveolin-1 (Cav-1) and caveolin-3 (Cav-3) have been identified as potential regulators of vascular dysfunction and heart disease and might even confer cardiac protection in certain settings. Such a central role in vascular health therefore makes manipulation of Cav-1/3 function or expression levels clear therapeutic targets in a variety of cardiovascular related disease states. Here, we highlight the role of Cav-1 and Cav-3 in cardiovascular health and explore the potential of Cav-1 and Cav-3 derived experimental therapeutics.
Why Trust the Subject

It is a great pleasure to introduce this collection of papers on the use of introspective evidence in cognitive science. Our task as guest editors has been tremendously stimulating. We have received an outstanding number of contributions, in terms of quantity and quality, from academics across a wide disciplinary span, both from younger researchers and from the most experienced scholars in the field. We therefore had to redraw the plans for this project a number of times. It quickly became clear to us that the collection would expand beyond the scheduled double issue of the Journal of Consciousness Studies. A triple issue was then drafted, but the number of excellent contributions continued to grow. We therefore had to reconsider the publication plans again, and the decision was made to publish an extended collection of papers in discrete instalments. At present substantial progress has been made towards determining the content of a second double issue of the Journal of Consciousness Studies, due summer 2004. A third instalment now appears to be a real possibility. We welcome enquiries from authors interested in submitting to later instalments, especially those offering a novel perspective that is not otherwise represented. However, we do not intend continue this collection indefinitely. In putting together the first major interdisciplinary collection on this topic, we view our task as that of providing a starting point. Sufficient outlets exist to support ongoing debate. The idea for this collection first took shape when we proposed it to the managing editor of JCS, Anthony Freeman, at the ‘Towards a Science of Consciousness’ conference in Skovde, Sweden, August 2001. Since then, he has been involved in every stage of its development and construction. His editorial experience and his patient assistance have been invaluable to us and to the collection.
Securing Very Dynamic Groups and Data Aggregation in Wireless Sensor Networks

We present a new encryption mode of operation that allows nodes of a network to exchange messages securely (i.e. encrypted and authenticated) without sharing a common key or using public key cryptography. Our scheme is well adapted to networks, such as ad hoc, overlay or sensor networks, where nodes have limited capabilities and can share only a small number of symmetric keys. It provides privacy and integrity protection. We show that our proposal can be used in wireless sensor networks to send encrypted packets to very dynamic sets of nodes without having to establish and maintain group keys. These sets of nodes can be explicitly specified by the source or can be specified by the network according to some criteria, such as their location, proximity to an object, temperature range. As a result, a node can, for example, send encrypted data to all the nodes within a given geographical area, without having to identify the destination nodes in advance. Finally we show that our proposal can be used to implement a secure and scalable aggregation scheme for wireless sensor networks.
Oopsy-daisy: failure stories in quantitative evaluation studies for visualizations

Designing, conducting, and interpreting evaluation studies with human participants is challenging. While researchers in cognitive psychology, social science, and human-computer interaction view competence in evaluation study methodology a key job skill, it is only recently that visualization researchers have begun to feel the need to learn this skill as well. Acquiring such competence is a lengthy and difficult process fraught with much trial and error. Recent work on patterns for visualization evaluation is now providing much-needed best practices for how to evaluate a visualization technique with human participants. However, negative examples of evaluation methods that fail, yield no usable results, or simply do not work are still missing, mainly because of the difficulty and lack of incentive for publishing negative results or failed research. In this paper, we take the position that there are many good ideas with the best intentions for how to evaluate a visualization tool that simply do not work. We call upon the community to help collect these negative examples in order to show the other side of the coin: what not to do when trying to evaluate visualization.
Evaluation of Normal Model Visualization for Anomaly Detection in Maritime Traffic

Monitoring dynamic objects in surveillance applications is normally a demanding activity for operators, not only because of the complexity and high dimensionality of the data but also because of other factors like time constraints and uncertainty. Timely detection of anomalous objects or situations that need further investigation may reduce operators’ cognitive load. Surveillance applications may include anomaly detection capabilities, but their use is not widespread, as they usually generate a high number of false alarms, they do not provide appropriate cognitive support for operators, and their outcomes can be difficult to comprehend and trust. Visual analytics can bridge the gap between computational and human approaches to detecting anomalous behavior in traffic data, making this process more transparent. As a step toward this goal of transparency, this article presents an evaluation that assesses whether visualizations of normal behavioral models of vessel traffic support two of the main analytical tasks specified during our field work in maritime control centers. The evaluation combines quantitative and qualitative usability assessments. The quantitative evaluation, which was carried out with a proof-of-concept prototype, reveals that participants who used the visualization of normal behavioral models outperformed the group that did not do so. The qualitative assessment shows that domain experts have a positive attitude toward the provision of automatic support and the visualization of normal behavioral models, as these aids may reduce reaction time and increase trust in and comprehensibility of the system.
History-Aware Adaptive Backoff for Neighbor Discovery in Wireless Networks

The ability of discovering neighboring nodes, namely neighbor discovery, is essential for the self-organization of wireless ad hoc networks. In this paper, we propose a history-aware adaptive back off algorithm for neighbor discovery assuming collision detection and feedback mechanisms. Given successful discovery feedback, undiscovered nodes can adjust their contention window. With collision feedback and historical information, only transmission nodes enter the re-contention process, and decrease their contention window to accelerate neighbor discovery process after collision. Then, we give theoretical analysis of our algorithm on the discovery time and energy consumption, and derive the optimal size of contention windows by two rounds of optimization. Finally, we validate our theoretical analysis by simulations, and show the performance improvement over existing algorithms.
Bad Parts: Are Our Manufacturing Systems at Risk of Silent Cyberattacks?

Recent cyberattacks have highlighted the risk of physical equipment operating outside designed tolerances to produce catastrophic failures. A related threat is cyberattacks that change the design and manufacturing of a machine's part, such as an automobile brake component, so it no longer functions properly. These risks stem from the lack of cyber-physical models to identify ongoing attacks as well as the lack of rigorous application of known cybersecurity best practices. To protect manufacturing processes in the future, research will be needed on a number of critical cyber-physical manufacturing security topics.
THE ANALYSIS OF THE RELATIONSHIP BETWEEN EDUCATIONAL BELIEFS AND TECHNO-PEDAGOGICAL EDUCATION PROFICIENCY OF CANDIDATE TEACHERS

The aim of this study was examining the relationship between educational beliefs and techno-pedagogical education proficiency of candidate teachers. In this study, relational screening model was used. The universe of the study was determined as the candidate teachers having been studied in Faculty of Education at Mugla Sitki Kocman University in 2017-2018 autumn semester and the sampling consisted of 558 candidate teachers. At the end of the study, it was found that candidate teachers internalized existentialist educational belief at most. It was seen that educational beliefs had significant difference in terms of gender, department and grades. With regard to techno-pedagogical education proficiency, candidate teachers found themselves highly sufficient. Although techno-pedagogical education proficiency of candidate teachers had not mean difference in terms of gender and department, it had a mean difference for grades. It was finally stated that there was a low level of positive correlation between techno-pedagogical education proficiency and educational beliefs of candidate teachers. Article visualizations:
Real-time motion planning for agile autonomous vehicles

Planning the path of an autonomous, agile vehicle in a dynamic environment is a very complex problem, especially when the vehicle is required to use its full maneuvering capabilities. Recent efforts aimed at using randomized algorithms for planning the path of kinematic and dynamic vehicles have demonstrated considerable potential for implementation on future autonomous platforms. This paper builds upon these efforts by proposing a randomized motion planning architecture for dynamical systems in the presence of fixed and moving obstacles. This architecture addresses the dynamic constraints on the vehicle's motion, and it provides at the same time a consistent decoupling between low-level control and motion planning. Simulation examples involving a ground robot and a small autonomous helicopter, are presented and discussed.
Development of Long Live Love+, a school-based online sexual health programme for young adults. An intervention mapping approach

Abstract This paper describes the development of a Dutch online programme called Long Live Love+ focusing on positive, coercion-free relationships, contraception use, and the prevention of STIs, using the Intervention Mapping (IM) approach. All six steps of the approach were followed. Step 1 confirmed the need for a sexual health programme targeting young people aged 15 and over enrolled in higher level secondary education. Step 2 resulted in the production of a series of matrices-of-changes, including detailed programme objectives at the behavioural and the psycho-social level. Step 3 involved the selection of relevant methods and applications. Step 4 consisted of programme development, resulting in a sexual health programme with online and offline components, and including interactive exercises. Step 5 focused on adoption and implementation and included the production of a detailed teacher manual. Step 6 involved detailed planning for the process and effect evaluation and included interviews with teachers and focus group discussions with students to evaluate their experiences of the programme. The inclusion of a linkage group – and especially the inclusion of teachers in the development of the programme – turned out to be essential in terms of developing a programme in line with their context and needs.
Law of requisite variety: a case of IT and business alignment

This paper provides an explanation of the increasing complexity of corporate IT management as a special case of application of the law of requisite variety. Frequently cited drawback of established frameworks of IT best practices like COBIT and ITIL is their complexity and related difficulty in their implementation. Through the perspective of the law of requisite variety, drawn from the field of cybernetics, we can take a more elaborated approach to this phenomenon. First, through mapping the domain of corporate IT management to the concepts from cybernetics, we ground this area in set of well defined terms. The aim of this paper is to promote the perspective, that problems with increasing complexity in IT management are directly traceable to the encompassing business environment.
The role of human peritoneal mesothelial cells in the fibrosis and progression of gastric cancer

Peritoneal dissemination is the most frequent metastatic pattern of scirrhous gastric cancer. However, despite extensive research effort, disease outcomes have not improved sufficiently. Tumor progression and metastasis result from interactions between cancer and various cells in the stroma, including endothelial cells, immune cells and fibroblasts. Fibroblasts have been particularly well studied; they are known to change into carcinoma-associated fibroblasts (CAFs) and produce transforming growth factor β (TGF-β), which mediates cancer-stroma interactions. Here, we investigated whether TGF-β derived from cancer cells in the peritoneal microenvironment activates human peritoneal mesothelial cells (HPMCs), leading to the progression and fibrosis of gastric cancer. We found that activated HPMCs (a-HPMCs) took on a spindle shape formation, decreased the expression of E-cadherin and increased that of α-SMA. Furthermore, a-HPMCs became more invasive and upregulated proliferation of human gastric cancer-derived MKN45 cells following direct cell-cell contact. Notably, MKN45 cells co-cultured with a-HPMCs also acquired anchorage-independent cell growth and decreased expression of E-cadherin in vitro. To measure the effects of the co-culture in vivo, we developed a mouse xenograft model into which different culture products were subcutaneously injected. The largest tumors were observed in mice that had been given MKN45 cells co-cultured with a-HPMCs. Furthermore, these tumors contained HPMC-derived fibrous tissue. Thus, the epithelial-mesenchymal transition (EMT) of HPMCs appears to drive peritoneal dissemination and tumor fibrosis.
A new trust model to secure routing protocols against DoS attacks in MANETs

In mobile Ad hoc networks, data is transmitted in airspace between mobile entities without any centralized control. This environment offers many and very important services for mobile users. However, the level of security in this kind of network has not yet reached a significant level of maturity against the ferocious attacks. In this work, we present a new model to trust routing protocols communications in MANETs against DoS attacks. We have used the box plot theory to define accurately the threshold to detect a DoS attack and to reduce the number of false positives.
Epidemiology of preterm birth and its clinical subtypes

Preterm birth (<37 weeks) complicates 12.5% of all deliveries in the USA, and remains the leading cause of perinatal mortality and morbidity, accounting for as many as 75% of perinatal deaths. Despite the recent temporal increase in preterm birth, efforts to understand the problem of prematurity have met with little success. This may be attributable to the under-appreciation of the etiologic heterogeneity of preterm birth as well as the heterogeneity in its underlying clinical presentations—spontaneous onset of labor, preterm premature rupture of membranes, and medically indicated preterm birth. In this paper, we review data regarding preterm births with particular focus on its incidence, temporal trends, and recurrence. Studies of births from the USA indicate that the recent temporal increase in the overall preterm birth rate is driven by an impressive concomitant increase in medically indicated preterm birth. However, the largest temporal decline in perinatal mortality has also occurred among medically indicated preterm births (relative to other clinical subtypes), suggesting that these obstetric interventions at preterm gestational ages are associated with a reduction in perinatal mortality. Recent data indicate that spontaneous preterm birth is not only associated with increased recurrence of spontaneous, but also medically indicated, preterm birth, and vice versa. This suggests that the clinical subtypes may share common underlying etiologies. Since medically indicated preterm birth accounts for as many as 40% of all preterm births, efforts to understand the reasons for such interventions and their impact on short- and long-term morbidity in newborns is compelling. Further research is necessary in order to understand the mechanisms and etiology of preterm birth, thus leading to the possibility of effective preventive or therapeutic strategies.
Motion camouflage in a stochastic setting

Recent work has formulated 2- and 3-dimensional models and steering control laws for motion camouflage, a stealthy pursuit strategy observed in nature. Here we extend the model to encompass the use of a high-gain pursuit law in the presence of sensor noise as well as in the case when the evader's steering is driven by a stochastic process, demonstrating (in the planar setting) that motion camouflage is still accessible (in the mean) in finite time. We also discuss a family of admissible stochastic evader controls, laying out the groundwork for a future game-theoretic study of optimal evasion strategies.
Adaptive Edge-Oriented Shot Boundary Detection

We study the problem of video shot boundary detection using an adaptive edge-oriented framework. Our approach is distinct in its use of multiple multilevel features in the required processing. Adaptation is provided by a careful analysis of these multilevel features, based on shot variability. We consider three levels of adaptation: at the feature extraction stage using locally-adaptive edge maps, at the video sequence level, and at the individual shot level. We show how to provide adaptive parameters for the multilevel edge-based approach, and how to determine adaptive thresholds for the shot boundaries based on the characteristics of the particular shot being indexed. The result is a fast adaptive scheme that provides a slightly better performance in terms of robustness, and a five fold efficiency improvement in shot characterization and classification. The reported work has applications beyond direct video indexing, and could be used in real-time applications, such as in dynamic monitoring and modeling of video data traffic in multimedia communications, and in real-time video surveillance. Experimental results are included.
Fuzzy Clustering of Patterns Represented by Pairwise Dissimilarities

Clustering is the problem of grouping objects on the basis of a similarity measure between them. This paper considers the approaches belonging to the K-means family, in particular those based on fuzzy memberships. When patterns are represented by means of non-metric pairwise dissimilarities, these methods cannot be directly applied, since they are not guaranteed to converge. Symmetrization and shift operations have been proposed, to transform the dissimilarities between patterns from non-metric to metric. It has been shown that they modify the K-means objective function by a constant, that does not influence the optimization procedure. Some fuzzy clustering algorithms have been extended, in order to handle patterns described by means of pairwise dissimilarities. The literature, however, lacks of an explicit analysis on what happens to K-means style fuzzy clustering algorithms, when the dissimilarities are transformed to let them become metric. This paper shows how the objective functions of four clustering algorithms based on fuzzy memberships change, due to dissimilarities transformations. The experimental analysis conducted on a synthetic and a real data set shows the effect of the dissimilarities transformations for four clustering algorithms based on fuzzy memberships.
Designing a process migration facility: the Charlotte experience

Experience with process migration in the Charlotte distributed operating system is discussed. Charlotte's migration facility is a fairly elaborate addition to the underlying kernel and utility-process base. It separates policy from mechanism. An overview is given of Charlotte, its process migration facility, and issues encountered that have a general application for any such facility. In the discussion of each issue, alternative design approaches adopted by other process migration facilities are presented. This account is intended to help researchers contemplating the addition of a process migration facility as well as those designing other operating system facilities that might need to interact later with added process migration facilities. <<ETX>>
Brain circuits underlying visual stability across eye movements—converging evidence for a neuro-computational model of area LIP

The understanding of the subjective experience of a visually stable world despite the occurrence of an observer's eye movements has been the focus of extensive research for over 20 years. These studies have revealed fundamental mechanisms such as anticipatory receptive field (RF) shifts and the saccadic suppression of stimulus displacements, yet there currently exists no single explanatory framework for these observations. We show that a previously presented neuro-computational model of peri-saccadic mislocalization accounts for the phenomenon of predictive remapping and for the observation of saccadic suppression of displacement (SSD). This converging evidence allows us to identify the potential ingredients of perceptual stability that generalize beyond different data sets in a formal physiology-based model. In particular we propose that predictive remapping stabilizes the visual world across saccades by introducing a feedback loop and, as an emergent result, small displacements of stimuli are not noticed by the visual system. The model provides a link from neural dynamics, to neural mechanism and finally to behavior, and thus offers a testable comprehensive framework of visual stability.
Application of improved BOMP algorithm in face recognition

When the group sparse representation is used to face recognition, the same samples take participate in representation the test sample at the same time. The original method ignored the correlation between the samples. To solve this problem, an improved block orthogonal matching pursuit algorithm is presented. The proposed algorithm uses the coherent coefficient of the samples as a parameter, setting the proper threshold value to select sample discrimination. Therefore, the reconstruction of the algorithm is optimized. Experiments on the Yale B database show that the recognition rate of improved algorithm is higher than the original one. The experiment results verify the validity of the proposed algorithm.