Miracle-dz/UniFAR-FTUs huggingface dataset:
Buckling‐Induced Reversible Symmetry Breaking and Amplification of Chirality Using Supported Cellular Structures

Buckling-induced reversible symmetry breaking and amplification of chirality using macro- and microscale supported cellular structures is described. Guided by extensive theoretical analysis, cellular structures are rationally designed, in which buckling induces a reversible switching between achiral and chiral configurations. Additionally, it is demonstrated that the proposed mechanism can be generalized over a wide range of length scales, geometries, materials, and stimuli.
Sharing Spaces with Robots An Integrated Environment for Human-Robot Interaction

In this paper we oﬀer an intelligent integrated environment for human-robot interaction. This environment takes ad-vantage of the fact that robots are both digital and physical entities, thus improving human-robot interaction and communication. Using mixed reality, our approach brings digital information directly into the physical environment, allowing users to interact with robots’ ideas and thoughts directly within the shared physical interaction space. We also present a taxonomy which we use to organise and classify the various interaction techniques that this environment oﬀers. Using this taxonomy, we demonstrate by detailing three interaction techniques, thought crumbs , decorations and bubblegrams . To evaluate these techniques, we oﬀer the design of a realisable prototype
Studying Media Events through Spatio-Temporal Statistical Analysis

This report is written in the context of the ANR Geomedia and summarises the developement of methods of spatio-temporel statistical analysis of media events (delivrable 3.2). This documents presents on-going work on statistical modelling and statistical inference of the ANR GEOMEDIA corpus, that is a collection of international RSS news feeds. Central to this project, RSS news feeds are viewed as a representation of the information flow in geopolitical space. As such they allow us to study media events of global extent and how they affect international relations. Here we propose hidden Markov models (HMM) as an adequate modelling framework to study the evolution of media events in time. This set of models respect the characteristic properties of the data, such as temporal dependencies and correlations between feeds. Its specific structure corresponds well to our conceptualisation of media attention and media events. We specify the general model structure that we use for modelling an ensemble of RSS news feeds. Finally, we apply the proposed models to a case study dedicated to the analysis of the media attention for the Ebola epidemic which spread through West Africa in 2014.
Mathematical Model of Easter Island Society Collapse

In this paper we consider a mathematical model for the evolution and collapse of the Easter Island society, starting from the fifth century until the last period of the society collapse (fifteen century). Based on historical reports, the available primary sources consisted almost exclusively on the trees. We describe the inhabitants and the resources as an isolated system and both considered as dynamic variables. A mathematical analysis about why the structure of the Easter Island community collapse is performed. In particular, we analyze the critical values of the fundamental parameters driving the interaction humans-environment and consequently leading to the collapse. The technological parameter, quantifying the exploitation of the resources, is calculated and applied to the case of other extinguished civilization (Copán Maya) confirming, with a sufficiently precise estimation, the consistency of the adopted model.
TEACHING AND APPLYING WATER CONSUMPTION SIMULTANEITY IN RESIDENTIAL: AN ACTIVE LEARNING PROJECT-BASED ENGINEERING APPROACH

In the present project, spanning from April 2020 to August 2022, the study focused on Hydraulic Engineering I within the Civil Engineering program and the Hydrosanitary Installation Project in the Architecture program. The objectives included calculating the simultaneity coefficient and determining the maximum probable flow for each student's residence. To achieve these objectives, active learning methodologies, specifically project-based learning (PBL), were adeptly employed to enrich students' practical knowledge and foster collaboration. The process began with architectural surveys of residential properties, followed by inventories of pipes, sanitary appliances, and wet rooms. Measurements of flow rates at various faucet openings (25%, 50%, 75%, and 100%) were conducted, along with the recording of operating pressures within home networks. This data served as the foundation for creating calibration curves, a process carried out over 120 days. Using the collected data, each student developed a hydraulic model of their network and compared the software results to practical measurements. The participants calculated the simultaneity coefficient (Ks) and maximum possible flow for their dwellings using hydraulic design concepts and regulatory standards. The results were documented in technical reports, a video tutorial, and infographics. The research highlights the importance of understanding residential water usage patterns and their potential for optimizing water delivery systems. It also underscores the value of experiential learning, which helps students bridge theory and practice, enhancing technical skills and their understanding of hydraulic engineering.
Ordering the attributes of query results

There has been a great deal of interest in the past few years on ranking of results of queries on structured databases, including work on probabilistic information retrieval, rank aggregation, and algorithms for merging of ordered lists. In many applications, for example sales of homes, used cars or electronic goods, data items have a very large number of attributes. When displaying a (ranked) list of items to users, only a few attributes can be shown. Traditionally, these are selected manually. We argue that automatic selection of attributes is required to deal with different requirements of different users. We formulate the problem as an optimization problem of choosing the most "useful" set of attributes, that is, the attributes that are most influential in the ranking of the items. We discuss different variants of our notion of attribute usefulness, and propose a hybrid Split-Pane approach that returns a composite of the top attributes of each variant. We conduct both a performance and a user study illustrating the benefits of our algorithms in terms of efficiency and quality of explanation.
A virtual machine consolidation framework for MapReduce enabled computing clouds

In nowadays computing clouds, it is of the cloud providers' economic interests to correctly consolidate the workload of the virtual machines (VMs) into the suitable physical servers in the cloud data center in order to minimize the total maintenance cost. However, during the consolidation process, sufficient protection should be provided to the service level agreement (SLA) of the VMs. In this paper, the VM consolidation problem for MapReduce enabled computing clouds has been investigated. In the MapReduce enabled computing clouds, MapReduce jobs are carried out by homogeneous MapReduce VM instances that have identical hardware resource. Two resource allocation schemes with corresponding SLA constraints for the MapReduce VMs and the non-MapReduce VMs are proposed. Based on these schemes, the VM consolidation problem is modeled as an integer nonlinear optimization problem and an efficient algorithm has been proposed to locate its solutions. The results show that better VM consolidation performance can be achieved by colocating MapReduce instances together with non-MapReduce instances in the same set of physical servers.
Inventory of Epiphytes Aquatic Microfungi in Pond of Tailing Bauxite in Tanjungpinang, Bintan Island, Riau Islands Province

On the washing process of bauxite mining will produce waste, that was red mud. Those red mud will be streamed in pond of tailing bauxite. Eleocharis sp. has been pioneer plant in pond of tailing bauxite. The objective of this study was identify the epiphytes aquatic microfungi in pond of tailing bauxite, at Tanjungpinang, Bintan Island. Samples were collected by three different stations from Eleocharis sp. density with three samples points in each stations. In this research, the results of epiphyte aquatic microfungi were cultured got five genera and six different species of aquatic microfungi, such as Mucor sp. , Curvularia sp. (1 and 2), Phialophora sp. , Phoma sp. , and Arthrographis sp.Keywords: aquatic microfungi, bauxite, Bintan, Eleocharis sp. , tailing
Environment normalization for robust speech recognition using direct cepstral comparison

In this paper we describe and evaluate a series of new algorithms that compensate for the effects of unknown acoustical environments or changes in environment. The algorithms use compensation vectors that are added to the cepstral representations of speech that is input to a speech recognition system. While these vectors are computed from direct frame-by-frame comparisons of cepstra of speech simultaneously recorded in the training environment and various prototype testing environments, the compensation algorithms do not assume that the acoustical characteristics of the actual testing environment are known. The specific compensation vector applied in a given frame depends on either physical attributes such as SNR or presumed phonetic identity. The compensation algorithms are evaluated using the 1992 ARPA 5000 word WSJ/CSR corpus. The best system combines phoneme-based and SNR-based cepstral compensation with cepstral mean normalization, and provides a 66.8% reduction in error rate over baseline processing when tested using a standard suite of unknown microphones. <<ETX>>
Choosing to Interact: Exploring the Relationship Between Learner Personality, Attitudes, and Tutorial Dialogue Participation

The tremendous effectiveness of intelligent tutoring systems is due in large part to their interactivity. However, when learners are free to choose the extent to which they interact with a tutoring system, not all learners do so actively. This paper examines a study with a natural language tutorial dialogue system for computer science, in which students interacted with the JavaTutor system through natural language dialogue over the course of problem solving. We explore the relationship between students’ level of dialogue interaction and learner characteristics including personality profile and pre-existing attitudes toward the learning task. The results show that these learner characteristics are significant predictors of the extent to which students engage in dialogue with the tutoring system, as well as the number of task actions students make. By identifying students who may not engage with tutoring systems as readily, this work constitutes a step toward building adaptive systems that successfully support a variety of students with different attitudes and personalities.
Coordinated multipoint: Concepts, performance, and field trial results

Coordinated multipoint or cooperative MIMO is one of the promising concepts to improve cell edge user data rate and spectral efficiency beyond what is possible with MIMOOFDM in the first versions of LTE or WiMAX. Interference can be exploited or mitigated by cooperation between sectors or different sites. Significant gains can be shown for both the uplink and downlink. A range of technical challenges were identified and partially addressed, such as backhaul traffic, synchronization and feedback design. This article also shows the principal feasibility of COMP in two field testbeds with multiple sites and different backhaul solutions between the sites. These activities have been carried out by a powerful consortium consisting of universities, chip manufacturers, equipment vendors, and network operators.
In Vivo Identification of Eugenol-Responsive and Muscone-Responsive Mouse Odorant Receptors

Our understanding of mammalian olfactory coding has been impeded by the paucity of information about the odorant receptors (ORs) that respond to a given odorant ligand in awake, freely behaving animals. Identifying the ORs that respond in vivo to a given odorant ligand from among the ∼1100 ORs in mice is intrinsically challenging but critical for our understanding of olfactory coding at the periphery. Here, we report an in vivo assay that is based on a novel gene-targeted mouse strain, S100a5–tauGFP, in which a fluorescent reporter selectively marks olfactory sensory neurons that have been activated recently in vivo. Because each olfactory sensory neuron expresses a single OR gene, multiple ORs responding to a given odorant ligand can be identified simultaneously by capturing the population of activated olfactory sensory neurons and using expression profiling methods to screen the repertoire of mouse OR genes. We used this in vivo assay to re-identify known eugenol- and muscone-responsive mouse ORs. We identified additional ORs responsive to eugenol or muscone. Heterologous expression assays confirmed nine eugenol-responsive ORs (Olfr73, Olfr178, Olfr432, Olfr610, Olfr958, Olfr960, Olfr961, Olfr913, and Olfr1234) and four muscone-responsive ORs (Olfr74, Olfr235, Olfr816, and Olfr1440). We found that the human ortholog of Olfr235 and Olfr1440 responds to macrocyclic ketone and lactone musk odorants but not to polycyclic musk odorants or a macrocyclic diester musk odorant. This novel assay, called the Kentucky in vivo odorant ligand–receptor assay, should facilitate the in vivo identification of mouse ORs for a given odorant ligand of interest.
Hv1 proton channels are required for high-level NADPH oxidase-dependent superoxide production during the phagocyte respiratory burst

Granulocytes generate a “respiratory burst” of NADPH oxidase-dependent superoxide anion (O2−∙) production that is required for efficient clearance of bacterial pathogens. Hv1 mediates a voltage-gated H+ channel activity that is proposed to serve a charge-balancing role in granulocytic phagocytes such as neutrophils and eosinophils. Using mice in which the gene encoding Hv1 is replaced by β-Geo reporter protein sequence, we show that Hv1 expression is required for measurable voltage-gated H+ current in unstimulated phagocytes. O2−∙ production is substantially reduced in the absence of Hv1, suggesting that Hv1 contributes a majority of the charge compensation required for optimal NADPH oxidase activity. Despite significant reduction in superoxide production, Hv1−/− mice are able to clear several types of bacterial infections.
Recurrence pattern and prognosis in low-risk breast cancer patients – Data from the DBCG 89-A programme

The invasive disease free survival, the overall survival, and the relative risk of death compared to the Danish population as well as the risk of recurrence and new malignancies is reported for low-risk breast cancer patients of the DBCG 89-A programme. The study includes a comparison between those patients who, according to the present criteria, would be defined low-risk and those who would be defined high-risk (the retrospective low→high-risk group) and a comparison of treatment by mastectomy and BCS combined with radiation therapy. The DBCG 89-A programme scheduled 10 years of follow-up. Data was supplemented by record linkage to the Hospital Discharge Registry (date of event) and the Central Population Registry (date of death). The study population consisted of 8 850 patients. With 12 years of follow-up 3 811 events (43%) were recorded: loco-regional recurrence 8%, distant recurrence 11%, contralateral cancer 6%, secondary cancer 8%, and deaths 11%. The DBCG registry had an incomplete reporting of events in these low-risk patients, due to premature discontinuation of control. The incidence of recurrences was higher for the retrospective low → high-risk group than for the low-risk group. The 10-year overall survival was 76%; lower in the retrospective low → high-risk group (71%) than in the low-risk group (83%). The 5-year survival following local recurrence was 68% after mastectomy and 81% after BCS. The risk of mortality was higher than in the general population for all subgroups of patients. The relative risk of mortality expressed in terms of the standardized mortality ratio was 10.4 for young patients (26–39 years) and 1.2 for old patients aged 70–74 years and 1.3 for patients in the retrospective low-risk group and 1.9 for patients in the low → high-risk group. The loco-regional treatment given did not cure all patients, in particular young patients and those of the retrospective low → high-risk group.
The Mediating Effect of Technology Adoption in the Relationship Between Entrepreneurial Orientation and Sustainable Entrepreneurship Values among Fintech Organizations in Malaysia

The objective of this paper is to examine the mediating role of technology adoption (TA) in the relationship between entrepreneurial orientation (EO) and sustainable entrepreneurship values (SEV) among Fintech organizations in Malaysia. The proposed model was evaluated through the utilization of SmartPLS-SEM 4.0. 9.9. Information from Fintech organizations in Malaysia was gathered via a self-administered questionnaire. 260 questionnaires out of 294 have been incorporated into statistical analyses. Both EO and TA have favorable and statistically significant benefits on SEV. Furthermore, the impact of EO characteristics (risk-taking, pro-activeness, innovativeness, competitive aggressiveness, and autonomy) on SEV is mediated by TA. It is highly suggested that Fintech organizations in Malaysia adopt EO and cultivate the inventive potential that results from it to increase their resilience to Fintech offerings and disruptions. The findings also support and extend both the resource-based view theory and the extended Technology Acceptance Model into a collaborative framework. EO and TA are the resources and capabilities applied in Fintech organizations, with TA being a mediator that stimulates the reflection of that affiliation as examined. This paper has contributed to the extant literature and suggests future studies to extend the study by employing varied methodological analysis.
Rigorous upper bounds on data complexities of block cipher cryptanalysis

Abstract Statistical analysis of symmetric key attacks aims to obtain an expression for the data complexity which is the number of plaintext-ciphertext pairs needed to achieve the parameters of the attack. Existing statistical analyses invariably use some kind of approximation, the most common being the approximation of the distribution of a sum of random variables by a normal distribution. Such an approach leads to expressions for data complexities which are inherently approximate. Prior works do not provide any analysis of the error involved in such approximations. In contrast, this paper takes a rigorous approach to analyzing attacks on block ciphers. In particular, no approximations are used. Expressions for upper bounds on the data complexities of several basic and advanced attacks are obtained. The analysis is based on the hypothesis testing framework. Probabilities of type-I and type-II errors are upper bounded by using standard tail inequalities. In the cases of single linear and differential cryptanalysis, we use the Chernoff bound. For the cases of multiple linear and multiple differential cryptanalysis, Hoeffding bounds are used. This allows bounding the error probabilities and obtaining expressions for data complexities. We believe that our method provides important results for the attacks considered here and more generally, the techniques that we develop should have much wider applicability.
Computing finite-dimensional bipartite quantum separability

Ever since entanglement was identified as a computational and cryptographic resource, effort has been made to find an efficient way to tell whether a given density matrix represents an unentangled, or separable, state. Essentially, this is the quantum separability problem. Chapters 1 to 3 motivate a new interior-point algorithm which, given the expected values of a subset of an orthogonal basis of observables of an otherwise unknown quantum state, searches for an entanglement witness in the span of the subset of observables. When all the expected values are known, the algorithm solves the separability problem. In Chapter 4, I give the motivation for the algorithm and show how it can be used in a particular physical scenario to detect entanglement (or decide separability) of an unknown quantum state using as few quantum resources as possible. I then explain the intuitive idea behind the algorithm and relate it to the standard algorithms of its kind. I end the chapter with a comparison of the complexities of the algorithms surveyed in Chapter 3. Finally, in Chapter 5, I present the details of the algorithm and discuss its performance relative to standard methods.
Parallel processing of grid-based one-shot structured-light system for online 3D reconstruction of moving objects

In this paper, we propose a method of parallel processing of one-shot structured-light system to realize online 3D reconstruction of moving objects. The proposed method is based on a projector-camera system that reconstructs a shape from a single image where a static pattern is cast by a projector; such a method is ideal for acquisition of moving objects at a high frame rate. The structured-light pattern is a grid pattern that consists of sinusoidal wave lines of vertical and horizontal directions. Since the intersection points of wave lines are used as feature points and the lines give the connectivity of the intersections, the correspondence between camera image and projected pattern can be found by the energy minimization of the graph. The energy minimization is accomplished by belief propagation. We propose a method to improve the computational time for online 3D reconstruction by GPU-based parallel processing for the steps of the structured-light system. In the experiment, we show the proposed method realizes online 3D reconstruction.
Reduced order modeling for clearance control in turbomachinery

Finite element models (FEMs) are extensively used in the design optimization of utility scale steam turbines. As an example, by simulating multiple startup scenarios of steam power plants, engineers can obtain turbine designs that minimize material utilization and at the same time avoid the damaging effects of large thermal stresses or rubs between rotating and stationary parts. Unfortunately, FEMs are computationally expensive and only a limited amount of simulations can be afforded to get the final design. For this reason, numerous model reduction techniques have been developed to reduce the size of the original model without a significant loss of accuracy. When the models are nonlinear, as is the case for steam turbine FEMs, model reduction techniques are relatively scarce and their effectiveness becomes application dependent. Although there is an abundant literature on model reduction for nonlinear systems, many of these techniques become impractical when applied to a realistic industrial problem. This paper focuses in a class of nonlinear FEM characteristic of thermo-elastic problems with large temperature excursions. A brief overview of popular model reduction techniques is presented along with a detailed description of the computational challenges faced when applying them to a realistic problem. The main contribution of this work is a set of modifications to existing methods to increase their computational efficiency. The methodology is demonstrated on a steam turbine model, achieving a model size reduction by four orders of magnitude with only 5% loss of accuracy with respect to the full order FEMs. These practical implementations enable the calculation of multiple additional design scenarios.