Miracle-dz/UniFAR-FTUs huggingface dataset:
On design artifacts as sites for intermediate level knowledge production in interaction design

INTRODUCTION In this position paper, we describe two design research investigations we conducted that we view as examples of producing intermediate level knowledge in interaction design research. As stated in this workshop’s description, the means through which intermediate level knowledge can be developed and communicated in interaction design is varied and still emerging. In line with this, we offer our two examples as contributions to this nascent and growing discussion with a particular emphasis on the role design artifacts and their generation plays within intermediary level knowledge production inquiries.
The design for the initial drainage of the Great Level of the Fens: an historical whodunit in three parts

This article challenges the received view that it was the Dutchman, Sir Cornelius Vermuyden, who designed and oversaw the draining work done in the Great Level of the fens when Francis, fourth Earl of the Bedford became its Undertaker in January 1631. It first shows that Vermuyden did not become Director of Works under the Earl of a partner in the undertaking before arguing that the design employed was not the one offered by Vermuyden the previous year. The final part demonstrates that the work done while the Earl of Bedford was undertaker responded to the long held aspirations of local landowners, the group from which Commissioners of Sewers were drawn. Finally it suggests what the grounds may have been for depriving the Bedford group of the reward for which they had invested so heavily.
Polytime algorithm for the shortest path in a homotopy class amidst semi-algebraic obstacles in the plane

Given a set of semi-algebraic obstacles in the plane and two points in the same connected component of the complement, the problem is to construct the shortest path between these points in a given homotopy class. This path is unique and has some canonical form. We use the representation of homotopy classes in a way that is as general as the classical one. It consists in representing generators of a free group which describes the classes of homotopy by disjoint cuts [GS97] homeomorphic to rays. We show that given such a system of generators and a word representing a homotopy class, one can contruct the shortest path of this class in time polynomial in the size of the word and in the size of the representation of the obstacles and the cuts. The homotopy class may also be represented by a path, then the polynomial complexity will depend on the size of the representation of this path. As a technical notion we introduce one particular system of cuts, which we call an extremity basis, that proves to be especially convenient for algorithmic purposes. The considered problem is motivated by robot motion planning and by theoretical questions arising in shortest path approximations in higher dimensions.
A structural approach for space compaction for concurrent checking and BIST

In this paper a new structural method for linear output space compaction is presented. The method is applicable to concurrent checking and built-in self test (BIST). Based on simple estimates for the probabilities of the existence of sensitized paths from the signal lines to the circuit outputs output partitions are determined without fault simulation. For all ISCAS 85 benchmark circuits three groups of compacted outputs are sufficient to achieve 100% fault coverage in test mode and for 3 to 5 groups an error detection probability of 98% is obtained in on-line mode. The method can be applied to very large circuits.
Matrix Metalloproteinase Activity that Disrupts the Dystroglycan Complex : Its Role in the Molecular Pathogenesis of Muscular Dystrophies

The dystroglycan (DG) complex, composed of two subunits αDG and βDG, interacts with the sarcoglycan complex to form the dystrophin-glycoprotein complex. αDG is a cell surface peripheral membrane protein which binds to the components of the extracellular matrix, while βDG is a type I integral membrane protein which anchors αDG to the cell membrane via the N-terminal extracellular domain. Although defects of the DG gene have not been identified as the primary causes of hereditary diseases in humans, secondary but significant abnormalities of the DG complex have been revealed in a number of muscular dystrophies. In this article, we characterize the matrix metalloproteinase (MMP) activity that disrupts the DG complex by cleaving the extracellular domain of βDG and discuss if this MMP plays a role in the molecular pathogenesis of muscular dystrophies. We also address the therapeutic potential of the drugs that inhibit this MMP activity to decelerate muscle degeneration in these diseases.
Methane release from gas hydrate systems during the Paleocene-Eocene thermal maximum and other past hyperthermal events: setting appropriate parameters for discussion

Around 66% of the modern exogenic carbon cycle (by mass) occurs as dissolved inorganic carbon within intermediate and deep waters of the Pacific, Indian and southern Oceans (the actual amount depending on how one slices vertical and horizontal boundaries, and characterizes marine and terrestrial organic carbon pools). This “carbon mass majority” was almost assuredly even larger in the early Paleogene – about 75% or so – if one includes the now-destroyed Pacific and eastern Tethys regions. From the start of any discussion, it should be clear that records from central and north Atlantic may not represent intermediate and deep waters across the globe quantitatively.
Query translation for distributed information gathering on the Web

The heterogeneity of Web information services poses new problems in the processing of user queries over distributed federated data. It was recently proven that the query translation between two information services supporting all Boolean operators can be done in an optimal way. On the Web, however, the situation when at least one Boolean operator is not supported is frequent. We study the case where a Boolean user query cannot be directly translated and should be split into sub-queries. We propose two strategies for query subsumption and discuss in detail the strategy which minimizes the number of submitted sub-queries. We derive an appropriate query form for the minimal strategy and demonstrate how both translation strategies are implemented in the Knowledge Brokers system.
The Immunological Synapse Balances T Cell Receptor Signaling and Degradation

The immunological synapse is a specialized cell-cell junction between T cell and antigen-presenting cell surfaces. It is characterized by a central cluster of antigen receptors, a ring of integrin family adhesion molecules, and temporal stability over hours. The role of this specific organization in signaling for T cell activation has been controversial. We use in vitro and in silico experiments to determine that the immunological synapse acts as a type of adaptive controller that both boosts T cell receptor triggering and attenuates strong signals.
A sample set perspective on the classification of hyperspectral image with weighted affine constraint

Hyperspectral images (HSIs) provide abundant spectral information of land covers, allowing detailed analysis of the materials on the earth. Besides, the homogeneity of land covers' distribution, that neighboring pixels usually belong to the same class, is also an important spatial information in HSI analysis. In this paper, a novel classification method in a sample set perspective is proposed to jointly exploit the spectral and the spatial information. More specifically, the proposed method treats the neighboring pixels as a sample set from the same class, and then classifies the set in the affine subspace spanned by the samples of the set using sparse representation based classification. In order to reduce the impact of possible outliers in the set, a weighted affine constraint is enforced on the combination coefficients. With this remedy, the proposed method is not only effective in exploiting the complementary information among the neighboring pixels of the same class, but also robust to possible outliers caused by neighbors of other classes. Experiments on two popular benchmarks demonstrate that our algorithm outperforms several state-of-the-art approaches for HSI classification with limited training samples.
Association rule based frequent pattern mining in biological sequences

To find all frequent patterns present in a set of strings is computationally intensive. An exhaustive search, where every possible candidate is taken into consideration, is not practical for larger pattern widths due to exponential computational complexity. Other approaches apply heuristics, where algorithm tries to reduce search space, but may compromise the accuracy of results to certain extent. We used modified Apriori algorithm to mine possible patterns in a very long sequence, especially most frequent substring pattern of a fixed length in biological sequence. The algorithm gives good performance by rapid reduction in search space, and computations using bit-wise operations instead of expensive string comparison operations. This algorithm outperform existing pattern finding methods such as MEME in terms of execution time.
Multi-level adaptive network for accented Mandarin speech recognition

Accented speech recognition is more challenging than standard speech recognition due to acoustic and linguistic mismatch between standard and accented data. In this paper, we propose a new framework combining Tandem system to improve the discriminative ability of acoustic features with Multi-level Adaptive Network (MLAN) to incorporate information from standard Mandarin corpus and also to solve the data sparseness problem. Mandarin spoken by Guangzhou speakers is considered as the accented mandarin (accented Putonghua, A-PTH), while spoken by northern area as the standard mandarin (standard Putonghua, S-PTH). Significant character error rate reduction of 13.8% and 24.6% relative are obtained over the baseline GMM-HMM systems trained on mixed corpus including both A-PTH and S-PTH corpus, as well as only the A-PTH corpus respectively.
A Model for Ocular Dominance Plasticity Controlled by Feedforward and Feedback Inhibition

The maturation of inhibitory transmission through γaminobutyric acid (GABA) is required to induce ocular dominance (OD) plasticity in the visual cortex. However, only circuits that are mediated by specific GABAA receptors can selectively elicit OD plasticity, implying a role of local circuits involved in GABA inhibition in this process. In this study, in order to theoretically examine the effects of such local pathways associated with cortical inhibition on the induction of OD plasticity, we compared synaptic modification dynamics regulated by feedforward inhibition and those regulated by feedback inhibition. Feedforward inhibition facilitated competitive interactions between different groups of inputs conveying correlated activities, which were required for the emergence of experience-dependent plasticity. Conversely, feedback inhibition suppressed competitive interactions and prevented synapses from reflecting past sensory experience. Our results suggest that the balance between feedforward and feedback inhibition regulates the timing and level of cortical plasticity by modulating competition among synapses. This result suggests an importance of activity-dependent competition in experience-dependent OD plasticity, which is in line with the results of previous experiments. key words: STDP, GABA, synaptic competition, visual cortex
Low-Profile Microstrip Patch Antenna for Over-Body Surface Communication at 2.45 GHz

A compact higher-order mode microstrip patch antenna (HM-MPA) suitable for on-body communications at 2.45 GHz is presented. Using FDTD simulations we show that the HM-MPA had an impedance bandwidth of 150 MHz and a relatively good bodyworn efficiency of more than 60% when placed in close proximity from a lossy medium with the characteristics of muscle tissue. On-body performance was investigated by modelling S21 coupling of two HM-MPAs spaced 200 mm apart on a muscle tissue layer. The HM-MPA coupling results are comparable to those achieved using a quarter wave monopole antenna on the same size of groundplane, mounted normal to the tissue surface. Considering that the HM-MPA has the benefit of being low-profile and physically more robust, it is a promising solution for over body surface applications.
Level-0 meta-models for predicting human behavior in games

Behavioral game theory seeks to describe the way actual people (as compared to idealized, ``rational'' agents) act in strategic situations. Our own recent work has identified iterative models (such as quantal cognitive hierarchy) as the state of the art for predicting human play in unrepeated, simultaneous-move games [Wright and Leyton-Brown 2012]. Iterative models predict that agents reason iteratively about their opponents, building up from a specification of nonstrategic behavior called level-0. The modeler is in principle free to choose any description of level-0 behavior that makes sense for the given setting; however, in practice almost all existing work specifies this behavior as a uniform distribution over actions. In most games it is not plausible that even nonstrategic agents would choose an action uniformly at random, nor that other agents would expect them to do so. A more accurate model for level-0 behavior has the potential to dramatically improve predictions of human behavior, since a substantial fraction of agents may play level-0 strategies directly, and furthermore since iterative models ground all higher-level strategies in responses to the level-0 strategy. Our work considers ``meta-models'' of level-0 behavior: models of the way in which level-0 agents construct a probability distribution over actions, given an arbitrary game. We evaluated many such meta-models, each of which makes its prediction based only on general features that can be computed from any normal form game. We evaluated the effects of combining each new level-0 meta-model with various iterative models, and in many cases observed large improvements in the models' predictive accuracies. In the end, we recommend a meta-model that achieved excellent performance across the board: a linear weighting of features that requires the estimation of five weights.
Release of ATP in the central nervous system during systemic inflammation: real-time measurement in the hypothalamus of conscious rabbits

Receptors for extracellular ATP (both ionotropic and metabotropic) are widely expressed in the CNS both in neurones and glia. ATP can modulate neuronal activity in many parts of the brain and contributes to the central nervous control of several physiological functions. Here we show that during the systemic inflammatory response the extracellular concentrations of ATP increase in the anterior hypothalamus and this has a profound effect on the development of the thermoregulatory febrile response. In conscious rabbits we measured ATP release in real time with novel amperometric biosensors and monitored a marked increase in the concentration of ATP (4.0 ± 0.7 μm) in the anterior hypothalamus in response to intravenous injection of bacterial endotoxin – lipopolysaccharide (LPS). No ATP release was observed in the posterior hypothalamus. The release of ATP coincided with the development of the initial phase of the febrile response, starting 18 ± 2 min and reaching its peak 45 ± 2 min after LPS injection. Application of the ATP receptor antagonists pyridoxal‐5′‐phosphate‐6‐azophenyl‐2′,4′‐disulphonic acid, Brilliant Blue G or periodate oxidized ATP dialdehyde to the site of ATP release in the anterior hypothalamus markedly augmented and prolonged the febrile response. These data indicate that during the development of the systemic inflammation, ATP is released in the anterior hypothalamus to limit the magnitude and duration of fever. This release may also have a profound effect on the hypothalamic control of other physiological functions in which ATP and related purines have been implicated to play modulatory roles, such as food intake, hormone secretion, cardiovascular activity and sleep.
VIP: Vision tool for comparing Images of People

This paper describes the VIP technique, a Vision tool for comparing Images of People. This tech- nique compares two human silhouettes and produces a similarity score between them. VIP was developed in the context of a surveillance project where one of the objec- tives is to recognize, in real-time, a person over different angles. The silhouette comparison must be robust to real- world situations, in particular to variations in scales, lighting conditions and human pose. The development of VIP involved the merging of several content-based im- age retrieval techniques. Colour and texture descriptors are used to describe the regions found inside a person's silhouette and a region matching scheme associates re- gions of one silhouette to another. For a recall of 80%, the average precision was found to be between 76% and 93% for a 870 images database with 16 different people. These results show the robustness of the system against scale, angle, and rotation variations in human silhouette appearance.
Visualization Techniques for Large Datasets

In order to improve understanding and working with data, visualizing information is without a doubt the best method to implement. Data visualization as a term unites the established field of scientific visualization and the more recent field of information visualization. The goal of data visualization is to provide the viewer an aggregated representation of available data by taking into account human’s visual system and its influence to comprehension. Spotting trends, seeing patterns and identifying outliers are some of the human’s visual system processes that are being manipulated in order to make data more accessible and appealing. This procedure of graphical representations creation helps engaging data exploration and even more, data extraction. Along with computer and graphical engineering, visualizations have grown and reached a very satisfactory level of variations and techniques, indulging even the most exacting data facilitators whether they are researchers, computer scientists, statisticians etc. A variety of data visualization software has been developed the last decades but Stanford University’s Protovis is by far the most distinguished tool to do the job. Below, a study is presented on data visualization’s purpose and prospects and how these became a necessity through time.
K-Connected-Based WSN Topology-Control Algorithm - K-Connected-Based Topology Algorithm LKETA

Proposed a new topology-control algorithms which is based on k-connectivity. In wireless sensor networks, the existing topology-control algorithms now can not meet the needs of WSN in faulttolerance, connectivity, redundancy and so on. In LKETA, the node deletes redundant edges according to the information of local neighbor nodes, and it adjusts transmission power with the power adjustment algorithm to constitute a k-connected sub graph, then it can calculate the topology refresh cycle according to the rate of the neighbor nodes. This algorithm guarantees the connectivity, low the transmitted power of nodes, reduce the redundancy edges, and increase the channel capacity.
An Experimental Study in Cross-Representation Mediation of User Models

The paper presents the result on cross-representation mediation of user models in the context of movie recommendation. We analyze the possibility of initializing the user models for a content-based recommender starting from movie ratings provided by users in other social applications. We focus in particular on (i) an approach for inferring user model preferences from rating and (ii) the experimentation of several methods to solve the missing value problem exploiting community-based ratings. We tested different variations of the proposed approach exploiting a subset of the MovieLens 10M Dataset, computing rating predictions, and MAE.
Locating Nodes in Mobile Sensor Networks More Accurately and Faster

Localization in mobile sensor networks is more challenging than in static sensor networks because mobility increases the uncertainty of nodes' positions. Most existing localization algorithms in mobile sensor networks use Sequential Monte Carlo (SMC) methods due to their simplicity in implementation. However, SMC methods are very time-consuming because they need to keep sampling and filtering until enough samples are obtained for representing the posterior distribution of a moving node's position. In this paper, we propose a localization algorithm that can reduce the computation cost of obtaining the samples and improve the location accuracy. A simple bounding-box method is used to reduce the scope of searching the candidate samples. Inaccurate position estimations of the common neighbor nodes is used to reduce the scope of finding the valid samples and thus improve the accuracy of the obtained location information. Our simulation results show that, comparing with existing algorithms, our algorithm can reduce the total computation cost and increase the location accuracy. In addition, our algorithm shows several other benefits: (1) it enables each determined node to know its maximum location error, (2) it achieves higher location accuracy under higher density of common nodes, and (3) even when there are only a few anchor nodes, most nodes can still get position estimations.