Miracle-dz/UniFAR-FTUs huggingface dataset:
Antiangiogenic Therapy by Local Intracerebral Microinfusion Improves Treatment Efficiency and Survival in an Orthotopic Human Glioblastoma Model

Targeting active angiogenesis, which is a major hallmark of malignant gliomas, is a potential therapeutic approach. For effective inhibition of tumor-induced neovascularization, antiangiogenic compounds have to be delivered in sufficient quantities over a sustained period of time. The short biological half-life of many antiangiogenic inhibitors and the impaired intratumoral blood flow create logistical difficulties that make it necessary to optimize drug delivery for the treatment of malignant gliomas. In this study, we compared the effects of endostatin delivered by daily systemic administration or local intracerebral microinfusion on established intracranial U87 human glioblastoma xenografts in nude mice. Noninvasive magnetic resonance imaging methods were used to assess treatment effects and additional histopathological analysis of tumor volume, microvessel density, proliferation, and apoptosis rate were performed. Three weeks of local intracerebral microinfusion of endostatin (2 mg/kg/day) led to 74% (P < 0.05) reduction of tumor volumes with decreased microvessel densities (33.5%, P < 0.005) and a 3-fold increased tumor cell apoptosis (P < 0.002). Systemic administration of a 10-fold higher amount of endostatin (20 mg/kg/day) did not result in a reduction of tumor volume nor in an increase of tumor cell apoptosis despite a significant decrease of microvessel densities (26.9%, P < 0.005). Magnetic resonance imaging was used to successfully demonstrate treatment effects. The local microinfusion of human endostatin significantly increased survival when administered at 2 mg/kg/day and was prolonged further when the dose was increased to 12 mg/kg/day. Our results indicate that the local intracerebral microinfusion of antiangiogenic compounds is an effective way to overcome the logistical problems of inhibiting glioma-induced angiogenesis.
Utilization of bagasse from the beer industry in clay brick production for building

This study analyzes bricks manufactured from bagasse, a by-product of the brewing industry. Raw materials (clay and bagasse) were characterized to determine their chemical composition, mineralogical composition and thermal behaviour. Mixtures were prepared with amounts of 0, 2.5, 5, 7.5 and 10 wt% of bagasse incorporated into the clay body. Rectangular test pieces were obtained by application of 54.5 MPa pressure, they were dried at 110 °C and fired at 950 oC in a laboratory furnace for 1 hour. Ceramic properties related to weight loss on ignition, linear shrinkage, bulk and absolute density, water absorption, water suction and compressive strength were analyzed in order to evaluate the suitability of using this wastes in ceramic matrix to the production of building bricks. The results indicate that the incorporation of the bagasse decreases the absolute and bulk density, increases the water absorption and reduces the compressive strength of the brick.
Intelligence is as intelligence does: Can additional support needs replace disability?

Abstract In many developed cultures there is an assumption that IQ is intelligence. However, emerging theories of multiple intelligences, of emotional intelligence, as well as the application of IQ testing to other cultural groups, and to people with disability, raises many questions as to what IQ actually measures. Despite recent research that shows IQ testing produces a floor effect when applied to people with lower IQ, as well as research that shows the Flynn effect also applies to people with lower IQ, in practice IQ scores below a certain cut-off are still being used to determine and classify a person's intellectual disability. However, a new paradigm is emerging, almost returning to the original intent of Binet, where measurement is made of the supports the person needs. In this paper, we argue that if one extends the notions of this supports paradigm that diagnosis of intellectual or physical disability could potentially be replaced by diagnosis of additional intellectual support needs, or additional physical support needs.
Composable Virtual Memory for an Embedded SoC

Systems on a Chip concurrently execute multiple applications that may start and stop at run-time, creating many use-cases. Composability reduces the verifcation effort, by making the functional and temporal behaviours of an application independent of other applications. Existing approaches link applications to static address ranges that cannot be reused between applications that are not simultaneously active, wasting resources. In this paper we propose a composable virtual memory scheme that enables dynamic binding and relocation of applications. Our virtual memory is also predictable, for applications with real-time constraints. We integrated the virtual memory on, CompSOC, an existing composable SoC prototyped in FPGA. The implementation indicates that virtual memory is in general expensive, because it incurs a performance loss around 39% due to address translation latency. On top of this, composability adds to virtual memory an insigni cant extra performance penalty, below 1%.
Transport or store? Synthesizing flow-based microfluidic biochips using distributed channel storage

Flow-based microfluidic biochips have attracted much attention in the EDA community due to their miniaturized size and execution efficiency. Previous research, however, still follows the traditional computing model with a dedicated storage unit, which actually becomes a bottleneck of the performance of biochips. In this paper, we propose the first architectural synthesis framework considering distributed storage constructed temporarily from transportation channels to cache fluid samples. Since distributed storage can be accessed more efficiently than a dedicated storage unit and channels can switch between the roles of transportation and storage easily, biochips with this distributed computing architecture can achieve a higher execution efficiency even with fewer resources. Experimental results confirm that the execution efficiency of a bioassay can be improved by up to 28% while the number of valves in the biochip can be reduced effectively.
The underlying dimensionality of PTSD in the diagnostic and statistical manual of mental disorders: where are we going?

There has been a substantial body of literature devoted to answering one question: Which latent model of posttraumatic stress disorder (PTSD) best represents PTSD's underlying dimensionality? This research summary will, therefore, focus on the literature pertaining to PTSD's latent structure as represented in the fourth (DSM-IV, 1994) to the fifth (DSM-5, 2013) edition of the DSM. This article will begin by providing a clear rationale as to why this is a pertinent research area, then the body of literature pertaining to the DSM-IV and DSM-IV-TR will be summarised, and this will be followed by a summary of the literature pertaining to the recently published DSM-5. To conclude, there will be a discussion with recommendations for future research directions, namely that researchers must investigate the applicability of the new DSM-5 criteria and the newly created DSM-5 symptom sets to trauma survivors. In addition, researchers must continue to endeavour to identify the “correct” constellations of symptoms within symptom sets to ensure that diagnostic algorithms are appropriate and aid in the development of targeted treatment approaches and interventions. In particular, the newly proposed DSM-5 anhedonia model, externalising behaviours model, and hybrid models must be further investigated. It is also important that researchers follow up on the idea that a more parsimonious latent structure of PTSD may exist.
Supervised Sense Tagging using Support Vector Machines

We describe the University of Maryland's supervised sense tagger, which participated in the SENSEVAL-2 lexical sample evaluations for English, Spanish, and Swedish; we also present unofficial results for Basque. We designed a highly modular combination of language-independent feature extraction and supervised learning using support vector machines in order to permit rapid ramp-up, language independence, and capability for future expansion.
The DNA Binding-Independent Function of the Glucocorticoid Receptor Mediates Repression of Ap-1–Dependent Genes in Skin

The glucocorticoid receptor (GR) mediates the biological effects of glucocorticoids (GCs) through activation or repression of gene expression, either by DNA binding or via interaction with other transcription factors, such as AP-1. Work in tissue culture cells on the regulation of AP-1–dependent genes, such as collagenase (MMP-13) and stromelysin (MMP-3) has suggested that the antitumor and antiinflammatory activity of GCs is mediated, at least in part, by GR-mediated downmodulation of AP-1. Here, we have identified phorbol ester-induced expression of MMP-3 and MMP-13 in mouse skin as the first example of an in vivo system to measure negative interference between AP-1 and GR in the animal. Cell type-specific induction of these genes by tumor promoters is abolished by GCs. Importantly, this is also the case in GRdim mice expressing a DNA binding-defective mutant version of GR. In contrast, the newly identified target genes in skin, plasma glutathione peroxidase and HSP-27, were induced by GC in wild-type, but not in GRdim mice. Thus, these data suggest that the DNA binding-independent function of the GR is dispensable for repression of AP-1 activity in vivo and responsible for the antitumor promoting activity of GCs.
Computational-Mechanism Design: A Call to Arms

Computational-mechanism design has an important role to play in developing complex distributed systems comprising multiple interacting agents. Game theory has developed powerful tools for analyzing, predicting, and controlling the behavior of self-interested agents and decision making in systems with multiple autonomous actors. These tools, when tailored to computational settings, provide a foundation for building multiagent software systems. This tailoring gives rise to the field of computational-mechanism design, which applies economic principles to computer systems design.
Non-invasive imaging of blood cell concentration and blood distribution in zebrafish Danio rerio incubated in hypoxic conditions in vivo

SUMMARY This is the first study to use a combination of digital imaging techniques and vital video microscopy to study hypoxia-induced changes in blood cell concentration, angiogenesis and blood redistribution in entire animals. Zebrafish Danio rerio, which are known to be independent of convective oxygen transport until about 2 weeks post-fertilization, were raised under chronic hypoxia (PO2=8.7 kPa) starting at 1 day after fertilization (d.p.f.) until 15 d.p.f. In control animals, the concentration of red cells (i.e. the number of red cells per nl blood) remained constant until 7 d.p.f. , and than decreased by approximately 70% until 15 d.p.f. In hypoxic animals, however, the concentration of red cells remained significantly elevated compared to control animals at 12 and 15 d.p.f. Assuming that the hemoglobin content of the red cells is similar, hypoxic animals have a higher oxygen carrying capacity in their blood. Red cell distribution within the various parts of the circulatory system, taken as an indicator for blood distribution, revealed a significant modification in the number of blood cells perfusing the organs in hypoxic animals. At 12 d.p.f. , gut perfusion was reduced by almost 50% in hypoxic animals, while perfusion of the segmental muscle tissue was increased to 350% of control values. No significant changes in brain perfusion were observed under these conditions. At 15 d.p.f. , the reduction in gut perfusion was abolished, although muscle perfusion was still significantly elevated. At this time, growth of hypoxic animals was less compared to control animals, revealing that hypoxia had become deleterious for further development. The vascular bed of various organs was not obviously different in hypoxic animals compared to normoxic animals.
Optimization and benchmark of cryptographic algorithms on network processors

As requirements for communication security grow, cryptographic processing becomes another type of application domain. However, cryptographic algorithms are all computationally intensive. This work compares and analyzes architectural characteristics of many widespread cryptographic algorithms on the Intel IXP2800 network processor. It also investigates several implementation and optimization principles that can improve overall performance. The results reported here are applicable to other network processors because they have similar components and architectures.
Binder-treated segregation-free aluminum alloy powders

Two paraffin waxes with different melting points and mixed at a specific mass ratio were used as a binder for premixed aluminum alloy powders. Dusting, segregation, and part-to-part variability were significantly reduced and powder flow improved compared to untreated powder In addition, the green density of compacts fabricated from the binder-treated powders was higher than that of the untreated powders. Sintered mechanical properties were not significantly affected by the addition of the binder Air-drying alkyd binders and water-based wax emulsions were also tested, but the results were less satisfactory.
Bach proteins belong to a novel family of BTB-basic leucine zipper transcription factors that interact with MafK and regulate transcription through the NF-E2 site

Members of the small Maf family (MafK, MafF, and MafG) are basic region leucine zipper (bZip) proteins that can function as transcriptional activators or repressors. The dimer compositions of their DNA binding forms determine whether the small Maf family proteins activate or repress transcription. Using a yeast two-hybrid screen with a GAL4-MafK fusion protein, we have identified two novel bZip transcription factors, Bach1 and Bach2, as heterodimerization partners of MafK. In addition to a Cap'n'collar-type bZip domain, these Bach proteins possess a BTB domain which is a protein interaction motif; Bach1 and Bach2 show significant similarity to each other in these regions but are otherwise divergent. Whereas expression of Bach1 appears ubiquitous, that of Bach2 is restricted to monocytes and neuronal cells. Bach proteins bind in vitro to NF-E2 binding sites, recognition elements for the hematopoietic transcription factor NF-E2, by forming heterodimers with MafK. Furthermore, a DNA binding complex that contained MafK as well as Bach2 or a protein related closely to Bach2 was found to be present in mouse brain cells. Bach1 and Bach2 function as transcription repressors in transfection assays using fibroblast cells, but they function as a transcriptional activator and repressor, respectively, in cultured erythroid cells. The results suggest that members of the Bach family play important roles in coordinating transcription activation and repression by MafK.
A Block Compressive Sensing Based Scalable Encryption Framework for Protecting Significant Image Regions

The existing Block Compressive Sensing (BCS) based image ciphers adopted the same sampling rate for all the blocks, which may lead to the desirable result that after subsampling, significant blocks lose some more-useful information while insignificant blocks still retain some less-useful information. Motivated by this observation, we propose a scalable encryption framework (SEF) based on BCS together with a Sobel Edge Detector and Cascade Chaotic Maps. Our work is firstly dedicated to the design of two new fusion techniques, chaos-based structurally random matrices and chaos-based random convolution and subsampling. The basic idea is to divide an image into some blocks with an equal size and then diagnose their respective significance with the help of the Sobel Edge Detector. For significant block encryption, chaos-based structurally random matrix is applied to significant blocks whereas chaos-based random convolution and subsampling are responsible for the remaining insignificant ones. In comparison with the BCS based image ciphers, the SEF takes lightweight subsampling and severe sensitivity encryption for the significant blocks and severe subsampling and lightweight robustness encryption for the insignificant ones in parallel, thus better protecting significant image regions.
Distributed coordination of a network of nonidentical agents with limited communication capabilities in the presence of fixed obstacles

In this paper, a distributed deployment algorithm is proposed for a network of multi-agent systems with limited and nonidentical communication ranges. An operation cost is defined for each agent, and it is aimed to minimize the overall cost function for both cases of an environment with and without obstacles. For the case of an obstacle-free environment, the notion of multiplicatively-weighted Voronoi (MW-Voronoi) diagram is extended to define limited communication MW-Voronoi (LCMW-Voronoi) diagram. A motion coordination strategy is subsequently presented to move the agents in such a way that the cost function over the region associated with each agent is minimized. For the second case, the limited communication visibility-aware MW-Voronoi (LCVMW-Voronoi) diagram is introduced and a proper motion coordination strategy is proposed to achieve the desired objective. Simulation results confirm the effectiveness of the proposed technique.
Differencing Provenance in Scientific Workflows

Scientific workflow management systems are increasingly providing the ability to manage and query the provenance of data products. However, the problem of differencing the provenance of two data products produced by executions of the same specification has not been adequately addressed. Although this problem is NP-hard for general workflow specifications, an analysis of real scientific (and business) workflows shows that their specifications can be captured as series-parallel graphs overlaid with well-nested forking and looping. For this natural restriction, we present efficient, polynomial-time algorithms for differencing executions of the same specification and thereby understanding the difference in the provenance of their data products. We then describe a prototype called PDiffView built around our differencing algorithm. Experimental results demonstrate the scalability of our approach using collected, real workflows and increasingly complex runs.
Mining Frequent Closed Itemsets without Duplicates Generation.

Closed itemsets are semantically equivalent to frequent item-sets but are orders of magnitude fewer, thus allowing the knowledge extracted from a transactional database to be represented very concisely. Unfortunately, no algorithm has been yet devised which allows to mine closed patterns directly. All existing algorithms may in fact generate the same closed itemset multiple times, and need to maintain the closed itemsets mined so far in the main memory in order to check if the current element has been already discovered or not. In this paper we propose a general technique for promptly detecting and discarding duplicate closed itemsets without the need of keeping in the main memory the whole set of closed patterns. Our approach can be exploited with substantial performance beneﬁts by any depth ﬁrst algorithms for mining frequent closed itemsets. As a case of study, we implemented our technique within a new mining algo-rithm which adopts a vertical bitmap representation of the dataset. The experimental evaluation demonstrates that our algorithm outperforms other state of the art algorithms such as CHARM, CLOSET+ and FPCLOSE.
A flexible quality of service model for mobile ad-hoc networks

Quality of service (QoS) support in mobile ad-hoc networks (MANETs) is a challenging task. Most of the proposals in the literature only address certain aspects of the QoS support, e.g., QoS routing, QoS medium access control (MAC) and resource reservation. However, none of them proposes a QoS model for MANETs. Meanwhile, two QoS models have been proposed for the Internet, viz., the integrated services (IntServ) model and the differentiated services (DiffServ) model, but these models are aimed for wired networks. In this paper, we propose a flexible QoS model for MANETs (FQMM) which considers the characteristics of MANETs and combines the high quality QoS of IntServ and service differentiation of Diff-Serv. Salient features of FQMM include: dynamics roles of nodes, hybrid provisioning and adaptive conditioning. Preliminary simulation results show that FQMM achieves better performance in terms of throughput and service differentiation than the best-effort model.
A Fully-Connected Layered Model of Foreground and Background Flow

Layered models allow scene segmentation and motion estimation to be formulated together and to inform one another. Traditional layered motion methods, however, employ fairly weak models of scene structure, relying on locally connected Ising/Potts models which have limited ability to capture long-range correlations in natural scenes. To address this, we formulate a fully-connected layered model that enables global reasoning about the complicated segmentations of real objects. Optimization with fully-connected graphical models is challenging, and our inference algorithm leverages recent work on efficient mean field updates for fully-connected conditional random fields. These methods can be implemented efficiently using high-dimensional Gaussian filtering. We combine these ideas with a layered flow model, and find that the long-range connections greatly improve segmentation into figure-ground layers when compared with locally connected MRF models. Experiments on several benchmark datasets show that the method can recover fine structures and large occlusion regions, with good flow accuracy and much lower computational cost than previous locally-connected layered models.
Formación de urbanistas usando realidad aumentada y tecnologías de aprendizaje móvil

This paper describes an educational experience using augmented reality (AR) on mobile devices as a tool for learning urban design concepts and specifically for architecture degree students. In a real project-based exercise, the participants had to design a sculpture to be placed in a public space, checking the suitability of the object as for example the form, scale, location, materials, etc., and taking into account the surroundings. The project is controlled on-site using AR on mobile platforms, encouraging collaborative learning by sharing the 3D models of their proposals, and acting both as producers and consumers of AR content in the process. To assess both the usability of technology, as well as the learning improvement, the class was divided into two groups with equivalent pre-course grades: a control group, who followed the conventional course in the laboratory, and a test group, who used AR technology. At the end of the course, the AR-using group showed a significant increase in academic performance, higher motivation and satisfaction compared to the control group.