Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a Formal Theory for Complex Objects and Content-Based Image Retrieval

Advanced services in digital libraries (DLs) have been developed and are widely used to address the required capabilities of an assortment of systems as DLs expand into diverse application domains. In order to reuse, integrate, unify, manage, and support these heterogeneous resources, the notion of complex objects (COs) has emerged as a means to facilitate aggregation of content and to help developers to manage heterogeneous information resources, and their internal components. In particular, complex image objects (along with the most used service - Content-Based Image Retrieval) have the potential to play a key role in information systems, due to the large availability of images and the need to integrate them with other datasets (and metadata), and image manipulation software. However, the lack of consensus on precise theoretical definitions for these concepts usually leads to ad hoc implementation, duplication of efforts, and interoperability problems. In this article we exploit the 5S Framework to propose a formal description for Complex Objects and Content-Based Image Retrieval, defining their fundamental concepts and relationships from a digital library (DL) perspective. These formalized concepts can be used to classify, compare, and highlight the differences among components, technologies, and applications, impacting digital library researchers, designers, and developers. The theoretical extensions of digital library functionality presented here cover complex image objects, within a practical case study, to exemplify the integrative use of services, thus balancing theory and practice.
Control techniques for walking robots

This article presents the application of three control techniques to a 7 DOF walking robot consisting of five actuators. In this study we focus on the motion control with respect to the sagittal plane. The gait pattern of the biped robot is given and its dynamic model together with the controller are used in closed loop. The considered controllers are: a PD modification using a gain-varying exponential term that is our contribution, a classical proportional-derivative (PD) controller and a PD-fuzzy controller. The advantages and disadvantages of each of these controllers are highlighted when facing the challenging task of controlling the motion of a walking robot.
The synchronous data flow programming language LUSTRE

The authors describe LUSTRE, a data flow synchronous language designed for programming reactive systems-such as automatic control and monitoring systems-as well as for describing hardware. The data flow aspect of LUSTRE makes it very close to usual description tools in these domains (block-diagrams, networks of operators, dynamical sample-systems, etc.), and its synchronous interpretation makes it well suited for handling time in programs. Moreover, this synchronous interpretation allows it to be compiled into an efficient sequential program. The LUSTRE formalism is very similar to temporal logics. This allows the language to be used for both writing programs and expressing program properties, which results in an original program verification methodology. >
Performance improvement on the Downlink HAPS communication channel employing MIMO antenna

Long Term Evolution (LTE) is one of the latest generations of the mobile cellular technology, while High Altitude Platform Station (HAPS) is envisaged to be the novel wireless infrastructure. Compared with existing wireless system such as terrestrial and satellite system, HAPS have been proposed to be a complementary technology of mobile cellular system. HAPS channel characteristic can be approached using Ricean fading model. In this paper, we evaluate the performance of downlink HAPS channel in delivering LTE services using MIMO antenna of 2×1 and 2×2. To improve the performance. Based on computer simulation, MIMO 2×1 can improve LTE Downlink performance of 1.4 – 12.3 dB for BER 10−3. Additionally, MIMO 2×2 can improve the performance more significant with 7.7 – 15.7 dB for the same BER value.
An Improvised DNA Sequence Compressor Using Pattern Recognition

Genome contains the hereditary information of biological organisms. Currently, there are large number of DNA sequences are stored in DNA databases. This paper presents an improvised version of (PRDNAC) Pattern Recognition based DNA Sequence Compression algorithm which compresses the DNA sequences. The development takes place in the area of time complexity factor and compression ratio.
The Asian monsoon, the tropospheric biennial oscillation, and the Indian Ocean zonal mode in the NCAR CSM

Abstract The interaction of the Indian Ocean dynamics and the tropospheric biennial oscillation (TBO) is analyzed in the 300-yr control run of the National Center for Atmospheric Research (NCAR) Climate System Model (CSM). Sea surface temperature (SST) anomalies and equatorial ocean dynamics in the Indian Ocean are associated with the TBO and interannual variability of Asian–Australian monsoons in observations. The air–sea interactions involved in these processes in the coupled ocean–atmosphere model are analyzed, so as to diagnose the causes of the SST anomalies and their role in the development of a biennial cycle in the Indian–Pacific Ocean region. By using singular value decomposition (SVD) analysis, it is found that the model reproduces the dominant mechanisms that are involved in the development of the TBO's influence on the south Asian monsoon: large-scale forcing from the tropical Pacific and regional forcing associated with both the meridional temperature gradient between the Asian continent and .
An integrative approach for multi-sensor based robot task programming

In this paper, we suggest skill primitive nets for multi-sensor integration in robot task programming. Each skill primitive is either a hybrid motion or a command interpreted by an external vision system. For the integration of different sensors into one general and comprehensive approach, one has to consider different sensing modalities. With an extension of our previously outlined approach of skill primitive nets, multi-sensor integration is possible. Thereby, a large amount of applications can be realized. We also give a precise specification as XML-interface for skill primitive nets. In this paper advantages are outlined, when using this interface between programming and control. Our skill primitive net approach for multi-sensor integration has been evaluated with industrial applications.
Foxa1 and Foxa2 Are Required for Formation of the Intervertebral Discs

The intervertebral disc (IVD) is composed of 3 main structures, the collagenous annulus fibrosus (AF), which surrounds the gel-like nucleus pulposus (NP), and hyaline cartilage endplates, which are attached to the vertebral bodies. An IVD is located between each vertebral body. Degeneration of the IVD is thought to be a major cause of back pain, a potentially chronic condition for which there exist few effective treatments. The NP forms from the embryonic notochord. Foxa1 and Foxa2, transcription factors in the forkhead box family, are expressed early during notochord development. However, embryonic lethality and the absence of the notochord in Foxa2 null mice have precluded the study of potential roles these genes may play during IVD formation. Using a conditional Foxa2 allele in conjunction with a tamoxifen-inducible Cre allele (ShhcreERT2), we removed Foxa2 from the notochord of E7.5 mice null for Foxa1. Foxa1−/−;Foxa2c/c;ShhcreERT2 double mutant animals had a severely deformed nucleus pulposus, an increase in cell death in the tail, decreased hedgehog signaling, defects in the notochord sheath, and aberrant dorsal-ventral patterning of the neural tube. Embryos lacking only Foxa1 or Foxa2 from the notochord were indistinguishable from control animals, demonstrating a functional redundancy for these genes in IVD formation. In addition, we provide in vivo genetic evidence that Foxa genes are required for activation of Shh in the notochord.
Effects of Low-Frequency Cranial Electrostimulation on the Rest-Activity Rhythm and Salivary Cortisol in Alzheimer's Disease

Objective. In previous studies, cranial electrostimulation (CES) had positive effects on sleep in depressed patients and in patients with vascular dementia. The present study examined the effects of low-frequency CES on the rest-activity rhythm and cortisol levels of patients with probable Alzheimer's disease (AD). Method. It was hypothesised that a decreased level of cortisol would parallel a positive effect of low-frequency CES on nocturnal restlessness. Sixteen AD patients were randomly assigned to an experimental group (n = 8) or a control group (n = 8). The experimental group was treated with CES, whereas the control group received sham stimulation, for 30 minutes a day, during 6 weeks. The rest-activity rhythm was assessed by actigraphy. Cortisol was measured repeatedly in the saliva throughout the day by means of salivette tubes. Results. Low-frequency CES did not improve the rest-activity rhythm in AD patients. Moreover, both groups showed an increase instead of a decrease in the level of cortisol. Conclusions: These preliminary results suggest that low-frequency CES has no positive effect on the rest-activity rhythm in AD patients. An alternative research design with high-frequency CES in AD is discussed.
Magnetoliposomes Loaded with Poly-Unsaturated Fatty Acids as Novel Theranostic Anti-Inflammatory Formulations

We describe the preparation, physico-chemical characterization and anti-inflammatory properties of liposomes containing the superparamagnetic nanoparticle Nanotex, the fluorescent dye Rhodamine-100 and omega-3 polyunsaturated fatty acid ethyl ester (ω-3 PUFA-EE), as theranostic anti-inflammatory agents. Liposomes were prepared after drying chloroform suspensions of egg phosphatidylcholine, hydration of the lipid film with aqueous phases containing or not Nanotex, Rhodamine-100 dye or ω-3 PUFA-EE, and eleven extrusion steps through nanometric membrane filters. This resulted in uniform preparations of liposomes of approximately 200 nm diameter. Extraliposomal contents were removed from the preparation by gel filtration chromatography. High Resolution Magic Angle Spinning 1H NMR Spectroscopy of the liposomal preparations containing ω-3 PUFA-EE revealed well resolved 1H resonances from highly mobile ω-3 PUFA-EE, suggesting the formation of very small (ca. 10 nm) ω-3 PUFA-EE nanogoticules, tumbling fast in the NMR timescale. Chloroform extraction of the liposomal preparations revealed additionally the incorporation of ω-3 PUFA-EE within the membrane domain. Water diffusion weighted spectra, indicated that the goticules of ω-3 PUFA-EE or its insertion in the membrane did not affect the average translational diffusion coefficient of water, suggesting an intraliposomal localization, that was confirmed by ultrafiltration. The therapeutic efficacy of these preparations was tested in two different models of inflammatory disease as inflammatory colitis or the inflammatory component associated to glioma development. Results indicate that the magnetoliposomes loaded with ω-3 PUFA-EE allowed MRI visualization in vivo and improved the outcome of inflammatory disease in both animal models, decreasing significantly colonic inflammation and delaying, or even reversing, glioma development. Together, our results indicate that magnetoliposomes loaded with ω-3 PUFA-EE may become useful anti-inflammatory agents for image guided drug delivery.
Recognition error processing for speech understanding

The aim of this paper is to propose an extension of the stochastic conceptual model in order to increase the robustness of the understanding process faced with misrecognitions and unknown words. Corpus analysis shows that some misrecognized words are more difficult to interpret than others, so we defined a word ambiguity rate. We performed trial series on train schedule inquiry application to evaluate the understanding rate when faced with misrecognized words and in particular, when these words are city names.
Usability design for spoken language dialogue

This paper discusses factors and scientific approaches to usability of spoken dialogue systems. The view taken is that these approaches fit into the models for usability engineering and iterative system development. We propose that different aspects of usability engineering becomes important depending if the development is research-oriented or application-oriented. The relation between these aspects needs to be investiged in more depth to assure rapid development that provides still provides a basis for furhter research and theory building.
Joined up thinking? Evaluating the use of concept‐mapping to develop complex system learning

In the physical and natural sciences, the complexity of natural systems and their interactions is becoming better understood. With increased emphasis on learning about complex systems, students will be encountering concepts that are dynamic, ill‐structured and interconnected. Concept‐mapping is a method considered particularly valuable for enabling learning in subject areas that are complex or ill‐structured. Evaluations of concept‐mapping tend to reflect their many applications. Many evaluations that try to measure enhancements in learning use test scores or grade‐point averages as performance indicators, which provide little information on how cognitive processes have developed. In this study, a modification of the Biggs and Collis’ Structure of the Observed Learning Outcomes (SOLO) taxonomy is applied to measure differences in the cognitive and structural complexity of learning outcomes between groups of students who participated in a concept‐mapping activity with those from a cohort that did not. The evaluation demonstrated that the intervention was effective in enabling the great majority of students to achieve better connectivity in thinking, though improvements in overall performance were less significant. Almost all students perceived the intervention to be of value to their learning.
From Influence Diagrams to Multi-operator Cluster DAGs

There exist several architectures to solve influence diagrams using local computations, such as the Shenoy-Shafer, the HUGIN, or the Lazy Propagation architectures. They all extend usual variable elimination algorithms thanks to the use of so-called 'potentials'. In this paper, we introduce a new architecture, called the Multi-operator Cluster DAG architecture, which can produce decompositions with an improved constrained induced-width, and therefore induce potentially exponential gains. Its principle is to benefit from the composite nature of influence diagrams, instead of using uniform potentials, in order to better analyze the problem structure.
A tailored-BLAST approach to throughput communications over block-fading MIMO channels

We consider single-terminal communications over slowly fading multiple-input multiple-output (MIMO) channels from the perspective of throughput. The throughput is defined to be the average rate at which data is reliably transmitted to the receiver allowing for the possibility that some data will be received incorrectly. In delay-sensitive situations the incorrectly decoded data is simply dropped, while in reliability-sensitive situations the receiver notifies the transmitter that certain codewords were incorrectly decoded and these are retransmitted. A new code-layering approach is developed based on our own tailored BLAST that allows us to surpass the performance of a successive-decoding multiple-access approach found in the literature, and with substantially reduced complexity.
Brain controlled home automation system

Brain Computer Interface (BCI) is one of the communication channel used to make an interaction between human brain and digital computer to control/operate the external devices without having any touch of muscular body part. This provides the easiness in operations and also helpful to elder and decibel people. This is useful for people who cannot operate the peripheral devices using our normal muscular body parts. The proposed system aims to control home appliances (like bulb, fan etc.) with the help of Human Attention Level which comes under non-invasive method of brains signal measurement. This attention is being measured by NeuroSky Headset. Attention level values are ranges from 1 to 100. Attention means user's level of mental focus which occurs during intense concentration and directed (but stable) mental activity. So to get attention values user should observe the object (or focus onto the object). For demonstration purpose here are used one bulb and one fan.
Computational Statistics and Data Analysis a Linearly Distributed Lag Estimator with R-convex Coefficients

The purpose of linearly distributed lag models is to estimate, from time series data, values of the dependent variable by incorporating prior information of the independent variable. A least-squares calculation is proposed for estimating the lag coefficients subject to the condition that the rth differences of the coefficients are non-negative, where r is a prescribed positive integer. Such priors do not assume any parameterization of the coefficients, and in several cases they provide such an accurate representation of the prior knowledge, so as to compare favorably to established methods. In particular, the choice of the prior knowledge parameter r gives the lag coefficients interesting special features such as monotonicity, convexity, convexity/concavity, etc. The proposed estimation problem is a strictly convex quadratic programming calculation, where each of the constraint functions depends on r + 1 adjacent lag coefficients multiplied by the binomial numbers with alternating signs that arise in the expansion of the rth power of (1−1). The most distinctive feature of this calculation is the Toeplitz structure of the constraint coefficient matrix, which allows the development of a special active set method that is faster than general quadratic programming algorithms. Most of this efficiency is due to reducing the equality constrained minimization calculations, which occur during the quadratic programming iterations, to unconstrained minimization ones that depend on much fewer variables. Some examples with real and simulated data are presented in order to illustrate this approach.
Proteomic Analysis of the EWS-Fli-1 Interactome Reveals the Role of the Lysosome in EWS-Fli-1 Turnover

Ewing sarcoma is a cancer of bone and soft tissue in children that is characterized by a chromosomal translocation involving EWS and an Ets family transcription factor, most commonly Fli-1. EWS-Fli-1 fusion accounts for 85% of cases. The growth and survival of Ewing sarcoma cells are critically dependent on EWS-Fli-1. A large body of evidence has established that EWS-Fli-1 functions as a DNA-binding transcription factor that regulates the expression of a number of genes important for cell proliferation and transformation. However, little is known about the biochemical properties of the EWS-Fli-1 protein. We undertook a series of proteomic analyses to dissect the EWS-Fli-1 interactome. Employing a proximity-dependent biotinylation technique, BioID, we identified cation-independent mannose 6-phosphate receptor (CIMPR) as a protein located in the vicinity of EWS-Fli-1 within a cell. CIMPR is a cargo that mediates the delivery of lysosomal hydrolases from the trans-Golgi network to the endosome, which are subsequently transferred to the lysosomes. Further molecular cell biological analyses uncovered a role for lysosomes in the turnover of the EWS-Fli-1 protein. We demonstrate that an mTORC1 active-site inhibitor, torin 1, which stimulates the TFEB-lysosome pathway, can induce the degradation of EWS-Fli-1, suggesting a potential therapeutic approach to target EWS-Fli-1 for degradation.
Generating class contracts from UML protocol statemachines

We present an approach to generate behavioral class interfaces in the form of class contracts from UML 2.0 protocol state machines. A generated class contract defines a pre- and post-condition for each operation that triggers a transition in the state machine. We consider the following protocol SM elements: state and state invariants, simple transitions, compound transitions, high-level transitions, complete transitions, self transitions also deal with the case of firing priorities. The generated contracts can be used as a behavioral interface, for documentation, run-time checking and test case generation.
Engineering Gene Networks to Emulate Drosophila Embryonic Pattern Formation

Pattern formation is essential in the development of higher eukaryotes. For example, in the Drosophila embryo, maternal morphogen gradients establish gap gene expression domain patterning along the anterior-posterior axis, through linkage with an elaborate gene network. To understand the evolution and behaviour of such systems better, it is important to establish the minimal determinants required for patterning. We have therefore engineered artificial transcription-translation networks that generate simple patterns, crudely analogous to the Drosophila gap gene system. The Drosophila syncytium was modelled using DNA-coated paramagnetic beads fixed by magnets in an artificial chamber, forming a gene expression network. Transient expression domain patterns were generated using various levels of network connectivity. Generally, adding more transcription repression interactions increased the “sharpness” of the pattern while reducing overall expression levels. An accompanying computer model for our system allowed us to search for parameter sets compatible with patterning. While it is clear that the Drosophila embryo is far more complex than our simplified model, several features of interest emerge. For example, the model suggests that simple diffusion may be too rapid for Drosophila-scale patterning, implying that sublocalisation, or “trapping,” is required. Second, we find that for pattern formation to occur under the conditions of our in vitro reaction-diffusion system, the activator molecules must propagate faster than the inhibitors. Third, adding controlled protease degradation to the system stabilizes pattern formation over time. We have reconstituted transcriptional pattern formation from purified substances, including phage RNA polymerases, ribonucleotides, and an eukaryotic translation extract. We anticipate that the system described here will be generally applicable to the study of any biological network with a spatial component.