Miracle-dz/UniFAR-FTUs huggingface dataset:
Trading Communities, the Networked Structure of International Relations, and the Kantian Peace

The authors argue that theories regarding the relationship between trade and conflict could benefit greatly from accounting for the networked structure of international trade. Indirect trade relations reduce the probability of conflict by creating (1) opportunity costs of conflict beyond those reflected by direct trade ties and (2) negative externalities for the potential combatants’ trading partners, giving them an incentive to prevent the conflict. Trade flows create groups of states with relatively dense trade ties, which we call trading communities. Within these groups, the interruptions to trade caused by conflict create relatively large costs. As a result, joint members of trading communities are less likely to go to war; however little they directly trade with each other. The authors systematically measure and define trading communities across various levels of aggregation using the network analytic tool of modularity maximization. The authors find significant support for their hypothesis, indicating that interdependence theory can be extended to extra-dyadic relations.
Olfactory Receptors Modulate Physiological Processes in Human Airway Smooth Muscle Cells

Pathophysiological mechanisms in human airway smooth muscle cells (HASMCs) significantly contribute to the progression of chronic inflammatory airway diseases with limited therapeutic options, such as severe asthma and COPD. These abnormalities include the contractility and hyperproduction of inflammatory proteins. To develop therapeutic strategies, key pathological mechanisms, and putative clinical targets need to be identified. In the present study, we demonstrated that the human olfactory receptors (ORs) OR1D2 and OR2AG1 are expressed at the RNA and protein levels in HASMCs. Using fluorometric calcium imaging, specific agonists for OR2AG1 and OR1D2 were identified to trigger transient Ca2+ increases in HASMCs via a cAMP-dependent signal transduction cascade. Furthermore, the activation of OR2AG1 via amyl butyrate inhibited the histamine-induced contraction of HASMCs, whereas the stimulation of OR1D2 with bourgeonal led to an increase in cell contractility. In addition, OR1D2 activation induced the secretion of IL-8 and GM-CSF. Both effects were inhibited by the specific OR1D2 antagonist undecanal. We herein provide the first evidence to show that ORs are functionally expressed in HASMCs and regulate pathophysiological processes. Therefore, ORs might be new therapeutic targets for these diseases, and blocking ORs could be an auspicious strategy for the treatment of early-stage chronic inflammatory lung diseases.
Building an economical VR system for CS education

As an immersive, interactive 3D environment, virtual reality (VR) is a way to capture students' imaginations and unleash their creativity. Such a system might be used in Computer Graphics, Gaming, Simulation, and with a suitable API, introductory courses. As such, it offers an excellent means of attracting CS students in a time of dwindling enrollments. However, the cost and complexity of building a VR system has been prohibitive until recently. This paper presents a fully immersive, 2-sensor, six degrees of freedom VR system we built for less than $4000.
The Effect of Cognitive Abilities and Learning Approach on Domain Surface Understanding from a Process Model

Process models are used by information professionals to convey semantics about the business operations in a real-world domain that are intended to be supported by an information system. The understandability of these models is vital to them actually being used. Until now, understandability has primarily been defined as an intrinsic quality of the models themselves. In this paper we conceptualize model understandability as an emergent property and advance an integrative framework to understand the role of the user in the process of understanding process models. Building on cognitive psychology, student learning theory and multimedia learning theory, we identify important factors during the presage and process stages of learning, and hypothesize their contributions to realizing domain understanding from a process model. Through an empirical study, we provide evidence that cognitive abilities, learning style and learning approach influence the development of domain understanding. We detail implications for theory and practice.
An accelerated coordination of stochastic multi-agents by moving speed

This paper presents a new behavior of moving multi-agents, whose agents move on cells in accordance with transition probabilities, depending on other agents over resources consisting of cells. We consider interactions or co-ordination among agents such that an agent can not move to a destination cell occupied by agents more than the agents of a current cell. This paper shows that a moving multiagent with an appropriate average moving speed is more stable than a moving multi-agent without average moving speed from both theory and experiments.
Internal and external pressures: How does an organic cotton production network learn to keep its hybrid nature?

Purpose – This study aims to investigate how an organic cotton production network learns to maintain its hybrid network and its sustainability in the face of internal and external pressures.Design/methodology/approach – A qualitative case study was conducted in Justa Trama, a Brazilian‐based organic cotton production network formed by six members with different roles and organisational logics.Findings – The study contributes to the literature on hybrid organisations by suggesting that in the case of networks, a compromise strategy is required at the internal level and a manipulation strategy is required at the external level. The network has to learn how to engineer a compromise among internal members and to enforce change among external institutions to maintain its sustainability.Social implications – The study was performed in Brazil, a country with serious social and environmental problems. The study thus informs managers of social economy organisations on how to deal with internal and external pressur.
Dense stereo matching in restricted disparity space

We propose a new domain-specific area-based stereo method that is applicable to various tasks including safe navigation and pedestrian detection. Incorporating a spatial restriction in the height direction of road scenes into the recursive computation of correlation measures, the proposed method efficiently provides dense disparity measures. A pair of cameras just has to be weakly calibrated due to the non-metric formulation. We also implement our stereo method on a newly developed onboard LSI, which has a dedicated architecture for practical automotive use and realizes more than BOM disparity estimations per second. Furthermore, we apply our method to a side collision warning system, which detects approaching objects such as pedestrians and bicycles. Through experiments we demonstrate the efficiency of our stereo method in road environments.
On the EMG-based torque estimation for humans coupled with a force-controlled elbow exoskeleton

Exoskeletons are successful at supporting human motion only when the necessary amount of power is provided at the right time. Exoskeleton control based on EMG signals can be utilized to command the required amount of support in real-time. To this end, one needs to map human muscle activity to the desired task-specific exoskeleton torques. In order to achieve such mapping, this paper analyzes two distinct methods to estimate the human-elbow-joint torque based on the related muscle activity. The first model is adopted from pneumatic artificial muscles (PAMs). The second model is based on a machine learning method known as Gaussian Process Regression (GPR). The performance of both approaches were assessed based on their ability to estimate the elbow-joint torque of two able-bodied subjects using EMG signals that were collected from biceps and triceps muscles. The experiments suggest that the GPR-based approach provides relatively more favorable predictions.
ON SIMPLIFYING BRAIN FUNCTIONS

A new approximation to the dynamics of neocortex, preserving essential functions but not the microstructure, is presented. Local feature spaces are used to replace neurodynamics of neural cell assemblies in categorization, approximation and generalization processes. A global workspace (mind space), resulting from cooperation among local feature spaces, facilitates memory-based reasoning. Implementation of this idea leads to a modular, neurofuzzy system as a model of mind. This approach provides a link between neurodynamics and cognitive science. The status and further directions of this project are reviewed.
Improved trade-based multi-robot coordination

Team work is essential to multiple mobile robot systems. An important question is, which robot should implement which action? In our previous work, we presented a trade-based task allocation approach for coordinated multi-robot exploration, which simulates the relationship between buyers and sellers in a business system, to achieve dynamic task allocation by using a mechanism of unsolicited bid. This paper still addresses the problem of coordinating multi-robot exploration while presents an improved trade-based approach to raise the efficiency of task allocation by using the Hungarian method. The proposed approach has been implemented and evaluated in simulation. The experimental results demonstrate the total exploration time can be significantly reduced by the improved trade-based approach compared to previous approaches.
Human-centered concepts for exploration and understanding of Earth observation images

The progress in information retrieval, computer vision, and image analysis makes it possible to establish very complete bases of algorithms and operators. A specialist in remote sensing or image processing now has the tools that allow him, at least in theory, to configure applications solving complex problems of image understanding. However, in reality, earth observation (EO) data analysis is still performed in a very laborious way at the end of repeated cycles of trial and error. To overcome this, we proposed a novel advanced remote sensing information processing system knowledge-driven information mining (KIM). KIM is based on human-centered concepts (HCCs), which implements new features and functions allowing improved feature extraction, search on a semantic level, the availability of collected knowledge, interactive knowledge discovery, and new visual user interfaces. We assess the HCC methodology for solving several difficult tasks in EO image interpretation, using a broad variety of sensor data, from meter-resolution synthetic aperture radar and optical images to hyperspectral data.
Social behaviour and mood in everyday life: the effects of tryptophan in quarrelsome individuals.

OBJECTIVE We hypothesized that increasing brain serotonin in healthy individuals with high scores on 2 self-report measures of trait quarrelsomeness would reduce quarrelsome behaviours and enhance agreeable behaviours when measured ecologically using an event-contingent recording method. METHODS We conducted a double-blind crossover study, in which participants took tryptophan (3 g/d) and placebo for 15 days each and recorded how they behaved, felt and perceived others during everyday social interactions. RESULTS Tryptophan significantly decreased quarrelsome behaviours and increased agreeable behaviours and perceptions of agreeableness. Men also behaved less dominantly, whereas both men and women perceived others as more dominant. CONCLUSION Tryptophan's effects on behaviours and perceptions, while more marked in the men, were generally positive and accompanied by improved affect. Increasing serotonin in quarrelsome people may not only reduce behaviours associated with a predisposition to various mental and physical disorders but also enhance socially constructive behaviours and improve social perceptions.
An efficient scheduling algorithm for QoS in wireless packet data transmission

In this paper, we proposed an efficient packet scheduling scheme, where the tradeoff of channel condition and QoS (quality of service) is factored according to the user traffic. It can be performed by adding the exponent term to the part of DRC (data rate control) which indicates the channel condition, in the proportional fair algorithm. With measuring the current level of supporting the QoS and controlling the DRC exponent, the proposed scheme can enhance the overall throughput without violating the QoS threshold.
[POSTER] Retrieving Lights Positions Using Plane Segmentation with Diffuse Illumination Reinforced with Specular Component

We present a novel method to retrieve multiple positions of point lights in real indoor scenes based on a 3D reconstruction. This method takes advantage of illumination over planes detected using a segmentation of the reconstructed mesh of the scene. We can also provide an estimation without suffering from the presence of specular highlights but rather use this component to refine the final estimation. This allows consistent relighting throughout the entire scene for aumented reality purposes.
Optimize the distribution of preferred stimulus in a population code

We consider two methods to optimize the distribution of preferred stimulus in a population code based on the knowledge of the distribution of stimulus. One method is to maximize the mean Fisher information of the population with respect to the stimulus ensemble. The other is to minimize the lower bound of the mean decoding error. The implication of the two methods is discussed.
Force transmission in joint-less tendon driven wearable robotic hand

This paper presents the design analysis and the fabrication process of Tendon Anchoring Support(TA Support). TA Support is developed to deliver the wire tension effectively to target actuation point, fingertip, while developing SNU Exo-Glove, which is joint-less tendon driven robot. Based on the force analysis of SNU Exo-Glove, TA Support was developed with several design considerations, especially customization to maximize force transmission. For that, fabrication process for customization to patient's hand has been established and introduced in this paper. To check the viability of customization, pressure measurement experiment has been performed. Engineers developing the soft wearable robot with tendon driven mechanism will always encounter force transmission problem, delivering force from actuator to target actuation point, as stated in this paper and this paper can suggest one possible effective solution.
Dynamic range constraints in image fusion and visualization

This article describes the trade-off in contrast content versus dynamic-range incurred by most image fusion algorithms. While this phenomenon is pervasive and must be addressed by all practitioners in the field, a satisfactory treatment is lacking from the literature. We formulate image fusion as an obstacle problem, explicitly taking into account the dynamic-range constraints of the display device, and derive an improved algorithm which outperforms those that do not include these constraints explicitly. The new method is applied to the problem of dynamic-range reduction, showing improved results over existing techniques, both visually and quantitatively. Keywords— Multispectral image processing, image fusion, dynamicrange compression, remote sensing, constrained optimization.
StoryBeads : a wearable for story construction and trade

Stories take hundreds of different forms and serve many functions. They can be as energetic as an entire life story or as simple as directions to a favorite beach. Technological developments challenge and change storytelling processes. The invention of writing changed the story from an orally recounted form, mediated by the storyteller, to a recorded version which was technologically reproducible. The fleeting experience of a storyteller’s woven tale became an immutable object. In cinema stories are told with a sequence of juxtaposed still images moving at a speed fast enough to fool the eye into seeing a continuously changing image instead of one image after another. The invention of the computer with its capacity for storage and manipulation of information let authors design stories and present them to different viewing audiences in different ways. Mobile computing, like the technological developments that came before it, will demand its own storytelling processes and story forms. This paper introduces a tool for mobile, digital storytelling called StoryBeads. StoryBeads are necklaces made of small computer “beads” capable of storing, transmitting, or displaying images. They are wearable computers used for constructing stories by allowing users to sequence and trade story pieces combining image and text. The beads communicate by infrared light, allowing the trading of digital images from bead to bead. The network consists of a chain of beads connected wirelessly, where individual beads communicate with their two nearest neighbors. Each necklace is a database of images distributed across a network of communicating beads. Inter-necklace communication allows a community of users to share stories digitally by beaming them from necklace to necklace or by exchanging physical beads between necklaces. As images travel between users, new image descriptions are added, providing historical context. Theories of play styles, narrative accrual, and image-based storytelling informed the design. StoryBeads encourage messaging among a group of story participants, demonstrating that mobile and portable devices can create new possibilities for participation in distributed and networked story experiences.
On threat assessment and collision avoidance for articulated machinery in low-speed scenarios

This paper investigates the hypothesis that threat assessment algorithms, developed for passenger cars and modified for articulated vehicles in low-speed scenarios, can be used to avoid a majority of the collision accidents in construction environments. The effect of using a collision avoidance system on a Volvo A25 hauler is investigated in several simulated scenarios with stationary obstacles. It is concluded that the safety benefit is severely limited by the relatively low braking capacity of the machine. Due to the limited capacity, braking manoeuvres must be initiated rather early, therefore steering is more efficient in many situations. Moreover, collisions are difficult to avoid when there is an offset between the machine and obstacle which is likely to occur in unstructured environments. The effect of different driving styles is also analysed and adapting the collision avoidance function to the individual driver can increase the number of collisions prevented. Another possible way to increase the safety benefit is to introduce a safety margin around obstacles. Both these options, however, increase the risk for generating false alarms.
Potential determinants of efficacy of mirror therapy in stroke patients – A pilot study

Abstract Background: Mirror therapy (MT) was found to improve motor function after stroke. However, there is high variability between patients regarding motor recovery. Objectives: The following pilot study was designed to identify potential factors determining this variability between patients with severe upper limb paresis, receiving MT. Methods: Eleven sub-acute stroke patients with severe upper limb paresis participated, receiving in-patient rehabilitation. After a set of pre-assessments (including measurement of brain activity at the primary motor cortex and precuneus during the mirror illusion, using near-infrared spectroscopy as described previously), four weeks of MT were applied, followed by a set of post-assessments. Discriminant group analysis for MT responders and non-responders was performed. Results: Six out of eleven patients were defined as responders and five as non-responders on the basis of their functional motor improvement. The initial motor function and the activity shift in both precunei (mirror index) were found to discriminate significantly between responders and non-responders. Conclusions: In line with earlier results, initial motor function was confirmed as crucial determinant of motor recovery. Additionally, activity response to the mirror illusion in both precunei was found to be a candidate for determination of the efficacy of MT.
Interval Neutrosophic Multiple Attribute Decision-Making Method Considering Credibility

Considering corresponding credibility on every evaluation value of interval neutrosophic numbers (INNs) in interval neutrosophic decision making, we put forward two interval neutrosophic weighted aggregation operators considering credibility, including a credibility-induced interval neutrosophic weighted arithmetic averaging (CIINWAA) operator and a credibility-induced interval neutrosophic weighted geometric averaging (CIINWGA) operator, and investigate their properties. Based on the Dice similarity measure, we introduce a ranking method for INNs, and then establish a decision-making method based on the CIINWAA and CIINWGA operators and the ranking method to handle multiple attribute decision-making problems with interval neutrosophic information and credibility information. Finally, an illustrative example of investment alternatives and the comparative analysis are provided to demonstrate the application and effectiveness of the developed approach.
using RNA-seq Candida albicans fungal pathogen Comprehensive annotation of the transcriptome of the human Material

Material Supplemental http://genome.cshlp. org/content/suppl/2010/08/06/gr.109553. 110.DC1. html References http://genome.cshlp. org/content/20/10/1451.full. html#ref-list-1 This article cites 35 articles, 22 of which can be accessed free at: Open Access Freely available online through the Genome Research Open Access option. service Email alerting click here top right corner of the article or Receive free email alerts when new articles cite this article sign up in the box at the
PHP-sensor: a prototype method to discover workflow violation and XSS vulnerabilities in PHP web applications

As the usage of web applications for security-sensitive facilities has enlarged, the quantity and cleverness of web-based attacks against the web applications have grown-up as well. Several annual cyber security reports revealed that modern web applications suffer from two main categories of attacks: Workflow Violation Attacks and Cross-Site Scripting (XSS) attacks. Presently, in comparison to XSS attacks, there have been actual restricted work carried out that discover workflow violation attacks, as web application logic errors are particular to the expected functionality of a specific web application. This paper presents PHP-Sensor, a novel defensive model that discovers both the vulnerabilities of workflow violation attack and XSS attack concurrently in the real world PHP web applications. For the workflow violation attack, we extract a certain set of axioms by monitoring the sequences of HTTP request/responses and their corresponding session variables during the offline mode. The set of axioms is then utilized for evaluating the HTTP request/response in online mode. Any HTTP request/ response that bypass the corresponding axiom is recognized as a workflow violation attack in PHP web application. For the XSS attack, PHP-Sensor discovers the self-propagating features of XSS worms by monitoring the outgoing HTTP web request with the scripts that are injected in the currently HTTP response web page. We develop prototype of our proposed defensive model on the web proxy as well as on the client-side for the recognition of workflow violation and XSS attacks respectively. We evaluate the detection capability of PHP-Sensor on open source real-world PHP web applications and the simulation outcomes reveal that our defensive model is efficient and feasible at discovering workflow violation attacks, XSS attacks and experiences tolerable performance overhead.