Miracle-dz/UniFAR-FTUs huggingface dataset:
Demonstration of Non-Gaussian Restricted Diffusion in Tumor Cells Using Diffusion Time-Dependent Diffusion-Weighted Magnetic Resonance Imaging Contrast

The diffusion-weighted magnetic resonance imaging (DWI) technique enables quantification of water mobility for probing microstructural properties of biological tissue and has become an effective tool for collecting information about the underlying pathology of cancerous tissue. Measurements using multiple b-values have indicated biexponential signal attenuation, ascribed to “fast” (high ADC) and “slow” (low ADC) diffusion components. In this empirical study, we investigate the properties of the diffusion time (Δ)-dependent components of the diffusion-weighted (DW) signal in a constant b-value experiment. A xenograft gliobastoma mouse was imaged using Δ = 11 ms, 20 ms, 40 ms, 60 ms, and b = 500–4000 s/mm2 in intervals of 500 s/mm2. Data were corrected for EPI distortions, and the Δ-dependence on the DW-signal was measured within three regions of interest [intermediate- and high-density tumor regions and normal-appearing brain (NAB) tissue regions]. In this study, we verify the assumption that the slow decaying component of the DW-signal is non-Gaussian and dependent on Δ, consistent with restricted diffusion of the intracellular space. As the DW-signal is a function of Δ and is specific to restricted diffusion, manipulating Δ at constant b-value (cb) provides a complementary and direct approach for separating the restricted from the hindered diffusion component. We found that Δ-dependence is specific to the tumor tissue signal. Based on an extended biexponential model, we verified the interpretation of the diffusion time-dependent contrast and successfully estimated the intracellular restricted ADC, signal volume fraction, and cell size within each ROI.
Deformed Epidermal Autoregulatory Factor-1 (DEAF1) Interacts with the Ku70 Subunit of the DNA-Dependent Protein Kinase Complex

Deformed Epidermal Autoregulatory Factor 1 (DEAF1) is a transcription factor linked to suicide, cancer, autoimmune disorders and neural tube defects. To better understand the role of DEAF1 in protein interaction networks, a GST-DEAF1 fusion protein was used to isolate interacting proteins in mammalian cell lysates, and the XRCC6 (Ku70) and the XRCC5 (Ku80) subunits of DNA dependent protein kinase (DNA-PK) complex were identified by mass spectrometry, and the DNA-PK catalytic subunit was identified by immunoblotting. Interaction of DEAF1 with Ku70 and Ku80 was confirmed to occur within cells by co-immunoprecipitation of epitope-tagged proteins, and was mediated through interaction with the Ku70 subunit. Using in vitro GST-pulldowns, interaction between DEAF1 and the Ku70 subunit was mapped to the DEAF1 DNA binding domain and the C-terminal Bax-binding region of Ku70. In transfected cells, DEAF1 and Ku70 colocalized to the nucleus, but Ku70 could not relocalize a mutant cytoplasmic form of DEAF1 to the nucleus. Using an in vitro kinase assay, DEAF1 was phosphorylated by DNA-PK in a DNA-independent manner. Electrophoretic mobility shift assays showed that DEAF1 or Ku70/Ku80 did not interfere with the DNA binding of each other, but DNA containing DEAF1 binding sites inhibited the DEAF1-Ku70 interaction. The data demonstrates that DEAF1 can interact with the DNA-PK complex through interactions of its DNA binding domain with the carboxy-terminal region of Ku70 that contains the Bax binding domain, and that DEAF1 is a potential substrate for DNA-PK.
Recognizing real world objects using multiple views

Object recognition, i.e. the classification of objects into predefined categories is an important tool in many computer vision systems. Unlike other types of recognition, it must be quite generic in order to be able to handle the great variety of objects that can exist. An aid to the solution of this difficult problem can be the use of information from different camera views. Here, we have extended a robust object recognition method in order to be able to function with information from more than one camera, and from arbitrary viewpoints. This method uses local feature points to construct visual vocabularies which then form an input to Support Vector Machines. We have found the multi-camera variant to produce superior results to the single-camera one.
Biometric score fusion in identification model using the Choquet integral

In this paper, we present a novel method for multibiometric identification system based on fusion at matching score level using the Choquet integral and the associated fuzzy measure. The output of each biometric matcher is modeled as a fuzzy set using membership functions, and the corresponding fuzzy entropy estimates the reliability of the information provided by each biometric matcher. Then, the fuzzy densities are generated based on training accuracy and fuzzy entropy. The results are aggregated using the Choquet integral. This novel method can measure the importance of each biometric matcher and improves the accuracy of the fusion model significantly.
Environment Exploration Using “ Just-inTime ” Sensor Fusion

This paper describes an approach to combining range data from both a set of sonar sensors as well as from a directional laser range finder to efficiently take advantage of the characteristics of both types of devices when exploring and mapping unknown worlds. We call our approach “just in time sensing” because it uses the more accurate but constrained laser range sensor only as needed, based upon a preliminary interpretation of sonar data. In this respect, it resembles “just in time” inventory control which attempts to judiciously obtain materials for industrial manufacturing only when and as needed. Experiments with a mobile robot equipped with sonar and a laser rangefinder demonstrate that by judiciously using the more accurate but more complex laser rangefinder to deal with the well-known ambiguity which arises in sonar data, we are able to obtain a much better map of an interior space at little additional cost (in terms of time and computational expense). 1
Nutrition and physical activity for the prevention and treatment of age-related sarcopenia

Sarcopenia, defined as loss of skeletal muscle mass and function, is associated with adverse outcomes such as physical disability, impaired quality of life and increased mortality. Several mechanisms are involved in the development of sarcopenia. Potentially modifiable factors include nutrition and physical activity. Protein metabolism is central to the nutritional issues, along with other potentially modifying nutritional factors as energy balance and vitamin D status. An increasing but still incomplete knowledge base has generated recent recommendations on an increased protein intake in the elderly. Several factors beyond the total amount of protein consumed emerge as potentially important in this context. A recent summit examined three hypotheses: (1) A meal threshold; habitually consuming 25–30 g protein at breakfast, lunch and dinner provides sufficient protein to effectively stimulate muscle protein anabolism; (2) Protein quality; including high-quality protein at each meal improves postprandial muscle protein synthesis; and (3) performing physical activity in close temporal proximity to a high-quality protein meal enhances muscle anabolism. Optimising the potential for muscle protein anabolism by consuming an adequate amount of high-quality protein at each meal, in combination with physical activity, appears as a promising strategy to prevent or delay the onset of sarcopenia. However, results of interventions are inconsistent, and well-designed, standardised studies evaluating exercise or nutrition interventions are needed before guidelines can be developed for the prevention and treatment of age-related sarcopenia.
Entailment of Set Constraints Is Not Feasible

Set constraints are inclusions between expressions denoting sets of trees. They have been used extensively for type inference and program analysis. At the lower end of the expressiveness scale there are atomic set constraints and Ines constraints (inclusions over non-empty sets) for both of which a cubic time satissability test is known. Recently, there has been increasing interest in entailment tests for set constraints. We prove that the entailment problem of atomic set constraints is coNP-hard. We also show that the entailment problem of Ines constraints is coNP-hard. This corrects a claim of polynomial complexity presented at CP'96. Our results suggest that a complete entailment test is not feasible even for simple classes of set constraints.
Multivariate Linear Cryptanalysis: The Past and Future of PRESENT

Extensions of linear cryptanalysis making use of multiple approximations such as multidimensional linear cryptanalysis are an important tool in symmetric-key cryptanalysis, among others being responsible for the best known attacks on ciphers such as Serpent and present. At CRYPTO 2015, Huang et al. provided a refined analysis of the key-dependent capacity leading to a refined key equivalence hypothesis, however at the cost of additional assumptions. Their analysis was recently extended by Blondeau and Nyberg to also cover an updated wrong key randomization hypothesis, using similar assumptions. As a consequence, the effectiveness of multidimensional linear attacks seems significantly reduced, e.g. to only 24 rounds for present. It is therefore an important open problem how to take key dependent behaviour for both right and wrong keys into account without introducing other limiting assumptions in the process. In this paper, we address this issue by proposing multivariate linear cryptanalysis as a new technique for using multiple linear approximations. Based on multivariate statistics and featuring a novel distinguishing technique based on quadratic discriminant analysis, it allows more realistic modelling of key dependence, while not relying on the limiting assumptions of previous work. Furthermore, it comes with a flexible signal/noise decomposition approach to allow for a realistic estimation of correlations. As an application of multivariate linear cryptanalysis, we provide attacks on 26 and 27 rounds (the latter marginally faster than exhaustive search) of present under much more realistic assumptions than previous work.
The Final Frontier: Embedding Networked Sensors in the Soil - eScholarship

This paper presents the first systematic design of a robust sensing system suited for the challenges presented by soil environments. We describe three soil deployments we have undertaken: in Bangladesh, and in California at the James Reserve and in the San Joaquin River basin. We discuss our experiences and lessons learned in deploying soil sensors. We present data from each deployment and evaluate our techniques for improving the information yield from these systems. Our most notable results include the following: in-situ calibration techniques to postpone labor-intensive and soil disruptive calibration events developed at the James Reserve; achieving a 91% network yield from a Mica2 wireless sensing system without end-to-end reliability in Bangladesh; and the javelin, a new platform that facilitates the deployment, replacement and in-situ calibration of soil sensors, deployed in the San Joaquin River basin. Our techniques to increase information yield have already led to scientifically promising results, including previously unexpected diurnal cycles in various soil chemistry parameters across several deployments.
Towards a unified platform for agent-based cloud robotics

This paper describes a platform that aims to design, build, and validate a new generation of cloud robotic platforms that enable agent-based intelligent control of robots deployed in unknown and dynamic environments. The platform will consider: (1) novel techniques for programming reactive plans and robotic behaviours through missions and novel mechanisms for building new behaviours from existing ones, both for experienced and non-expert users; (2) novel multi-layered cloud platform as the infrastructure to maintain a continuous link between the robots acting on a physical environment and their agent counterparts, to provide sensor data from robots to agents, and to provide high-level autonomous decisions from agents to robots.
A framework for non-realistic projections

Over the last thirty years, most research e orts in computer graphics have been directed towards producing photorealistic images. Photorealism, however, exhibits some very real shortcomings in practical and artistic settings. Non-photorealistic renderers (NPRs) o er new solutions by abandoning the accurate modeling of optics in order to achieve more expressive results. Previous NPR systems have focused on simulating traditional media by displaying geometric results in a non-realistic fashion. By abandoning photorealism, however, NPR systems also have the option of performing projection, in addition to lighting and visibility resolution, non-realistically. Projection techniques are particularly useful as a means of controlling how information is presented to a viewer, expressing the various ways in which the shape of objects, and the spatial relations between them, can be represented in pictures. We describe a framework for interactively computing non-realistic projections from 3D world space to 2D screen space. The framework provides a means of (1) using curved projection surfaces; (2) controlling the degree to which orthogonals converge to or diverge from a vanishing point in the image; (3) controlling the behavior of orthogonals as they converge or diverge; and (4) projecting di erent objects independently and compositing their images together. We demonstrate our approach with a variety of expressive projections applied to complex models. Thesis Supervisor: Julie Dorsey Title: Associate Professor
A Systematic Composite Service Design Modeling Method Using Graph-Based Theory

The composite service design modeling is an essential process of the service-oriented software development life cycle, where the candidate services, composite services, operations and their dependencies are required to be identified and specified before their design. However, a systematic service-oriented design modeling method for composite services is still in its infancy as most of the existing approaches provide the modeling of atomic services only. For these reasons, a new method (ComSDM) is proposed in this work for modeling the concept of service-oriented design to increase the reusability and decrease the complexity of system while keeping the service composition considerations in mind. Furthermore, the ComSDM method provides the mathematical representation of the components of service-oriented design using the graph-based theoryto facilitate the design quality measurement. To demonstrate that the ComSDM method is also suitable for composite service design modeling of distributed embedded real-time systems along with enterprise software development, it is implemented in the case study of a smart home. The results of the case study not only check the applicability of ComSDM, but can also be used to validate the complexity and reusability of ComSDM. This also guides the future research towards the design quality measurement such as using the ComSDM method to measure the quality of composite service design in service-oriented software system.
Social networking affordances for open educational language practice

Open Educational Resources (OER), as openly licensed content free to (re-)use at no cost, are attracting increasing interest from scholars and practitioners for their repurpose value in new educational settings, thus enabling Open Educational Practice (OEP). A topic that is under-explored to date is the role of social networking in OER uptake, affording ways for user groups to socially engage in meaningful learning, and bridging formal and informal learning contexts. This paper critically examines whether and how social networks enable open practice, focusing on the field of language learning and teaching in particular. For the purposes of the study, expert views in response to an open-ended questionnaire on OER/OEP for language education were collected between June and August 2014. The 18 respondents were scholars operating at the crossroads of OER and Computer Assisted Language Learning (CALL). Expert views were analyzed through a content analytic framework in line with three dimensions: the value of the social dimension in OEP, social network affordances in OEP and open learning pedagogies. The study examines whether open educational practice for language education can benefit from trends of user engagement through social networks (comprising reputation, recommendation and badging systems), and the potential implications for open language education. It also contributes to an understanding of changes in learning pedagogies afforded by principles of openness.
The Genetic Algorithm in the Minimum Bit Error Rate Multi-User Detection Assisted Space Division Multiple Access System

This is a recent research on Space Division Multiple Access-Orthogonal Frequency Division Multiplexing (SDMA-OFDM) based on the biological technique of Genetic Algorithm (GA) which is reminiscent of the rules of evolution and survival where a group of fitters' individuals in a population will survive more and more using in the wireless communication in the Multi-User Detection. The goal of this research is using Genetic Algorithm assisted by Minimum Bit Error Rate (MBER) comparatively of the Conjugate Graduate (CG) method to Multi-User Detection on OFDM due to the technique using the symbol chromosomes to obtain an initial Frequency Domain-Channel Transfer Function (FD-CHTF) assisted by Minimum Bit Error Rate that the GA is capable of approaching the MBER solution at a lower complexity than the CG algorithm and it can be achieved by the simulation results provided to demonstrate the improvement of Multi-User Detection using Genetic Algorithm assisted by Minimum Bit Error Rate.
Charge crossover at the U(1) Higgs phase transition

The type-I region of phase transitions at finite temperature of the U(1)-Higgs theory in 3+1 dimensions is investigated in detail using a Wilsonian renormalization group. We consider, in particular, the quantitative effects induced through the crossover of the scale-dependent Abelian charge from the Gaussian to a nontrivial Abelian fixed point. As a result, the strength of the first-order phase transition is weakened. Analytical solutions to approximate flow equations are obtained, and all characteristics of the phase transition are discussed and compared to the results obtained from perturbation theory. In addition, we present a detailed quantitative study regarding the dependence of the physical observables on the coarse-graining scheme. This results in error bars for the regularization scheme (RS) dependence. We find quantitative evidence for an intimate link between the RS dependence and truncations of flow equations.
BM microenvironmental protection of CML cells from imatinib through Stat5/NF-κB signaling and reversal by Wogonin

Constitutive Stat5 activation enhanced cell survival and resistance to imatinib (IM) in chronic myelogenous leukemia (CML) cells. However, the mechanism of Stat5 activation in mediating resistance to IM in bone marrow (BM) microenvironment has not been evaluated precisely. In this study, we reported HS-5-derived conditioned medium (CM) significantly enhanced IM resistance in K562 and KU812. Interestingly, upregulation of the proportion of CD34+ subpopulation was found in CML cells. Subsequently, the BCR/ABL-independent activation of Stat5 increased P-glycoprotein (P-gp) activity in CM-mediated protection of CML stem cells (LSCs) from IM. Further research revealed Stat5 activation increased the DNA binding activity of NF-κB though binding of p-Stat5 and p-RelA in nucleus. Moreover, highly acetylated RelA was required for Stat5-mediated RelA nuclear binding. The study further confirmed that Wogonin potentiated the inhibitory effects of IM on leukemia development by suppressing Stat5 pathway both in CM model and the K562 xenograft model. In summary, results clearly demonstrated BCR/ABL-independent Stat5 survival pathway could contribute to resistance of CML LSCs to IM in BM microenvironment and suggested that natural durgs effectively inhibiting Stat5 may be an attractive approach to overcome resistance to BCR/ABL kinase inhibitors.
Valuing Investments in Multi-Energy Conversion, Storage, and Demand-Side Management Systems Under Uncertainty

In this paper, a financial valuation method for energy hubs with conversion, storage, and demand-side management (DSM) capabilities is proposed. An energy hub is an integrated system of units, e.g., a combined heat and power plant and a heat storage, which allows the conversion and storage of multiple energy carriers. In this paper, an extended energy hub model is presented which additionally takes into account the possibility of performing DSM with the load(s) connected to the hub output. Taking into account the energy hub's flexibility to change its output power(s), its economic value is determined with a method based on Monte Carlo simulation. This method calculates an optimal dispatch of the hub for a large amount of possible price paths of the input and output energy carriers. By means of the proposed energy hub Monte Carlo valuation model, integrated systems of multi-energy conversion and storage devices can be valued together with load management schemes. In doing so, the energy hub's ability to flexibly adapt its output to uncertain and volatile market prices is explicitly considered.
Wavelet packet transform based fusion of misaligned images

This paper proposes an image fusion method based on wavelet packet transform (WPT) for images with misaligned region of interest, which finds wide application in target recognition and feature extraction. The region of interest of the images are first aligned and then fused in the transform domain. The various no-reference parameters such as standard deviation (SD), spatial frequency (SF) are measured for the fused image. The result obtained from this method is compared with the other methods such as image fusion using discrete wavelet transform (DWT), stationary wavelet transform and guided filtering. It is evident from the simulation results that the two parameters are high for the fused image using wavelet packet transform.
Excalibur, a Three-Axis Force Display

In haptic simulation, a force feedback device is combined with a digital representation of a virtual world to create a kinesthetically immersive experience. The force feedback device, or haptic display, is usually a robotic manipulator with which a human operator interacts physically through a handle, stylus, finger-pad or some other form of customized interface. Modeling of the haptic display is often overlooked when building a haptic simulation. Understanding the dynamic behavior of the device is critical in assessing the stability and performance of the overall system as well as in the construction of the digital simulation. This paper describes some of the special modeling requirements for haptic displays. A dynamic model for Excalibur, a new three axis force display, is developed in a two step process. First an analytical model is constructed based on measured values and basic principals. Then the model is tuned using the results of vibrational testing to achieve a close match between the modal behavior of the theoretical and real systems. Numerical and experimental results are presented for representative points in the device’s workspace.