Miracle-dz/UniFAR-FTUs huggingface dataset:
Omnidirectional Learning - A New Paradigm for Learning to Predict Any Set of Variables from Any Other Set

Abstract : Awards: Best Paper Honorable Mention Award at the SIAM (Society for Industrial and Applied Mathematics Conference on Data Mining (SDM). Paper: Scaling log-linear analysis to datasets with thousands of variables. Businesses and Government are investing heavily in their data assets. As data quantities continue to grow rapidly, it is increasingly difficult to extract maximum value from those data stores. Learning to predict the future from past observations is one of the key components that make it possible to bring value to data. To date, much of the research effort has been devoted to drawing predictions about a single pre-defined target variable, such as predicting the magnitude of the global warming, or the probability of developing cancer. However, in many real-world applications, what we wish to predict can change dramatically from one instance to the next, e.g. from one tactical situation to another or from one client to another. State-of-the-art techniques only provide ad-hoc solutions to this problem, because learning one model for every possibly encountered situation does not scale to big data assets. This project investigated methods for learning a single model that can effectively and efficiently predict all unobserved variables from the currently available evidence. New technologies were developed to learn models with this property from large and high dimensional data. The results show that the developed techniques offer a gain of 4 orders of magnitude in computation time over the state of the art.
Standard Treatment Options for High-grade Glioma Surgery for High-grade Glioma

brain tumor in adults and accounts for >75% of the estimated 22,070 newly diagnosed malignant primary brain tumors in the US each year. More than half of HGGs are glioblastoma (GBM), the most aggressive subtype. The remainder include anaplastic gliomas (AGs), such as anaplastic astrocytoma (AA), anaplastic oligodendroglioma (AO), and anaplastic oligoastrocytoma (AOA), and rarer subtypes. HGG is incurable and is responsible for a disproportionate share of cancer-related morbidity and mortality. With optimal treatment, median survival is only 12–18 months for GBM and two to five years for AG. There have been recent advances in elucidating the molecular pathogenesis of HGG, which may provide additional prognostic information and lead to more effective treatments. This article summarizes the standard treatment of adult HGG with a particular focus on recent therapeutic advances.
A thin and conformal metasurface for illusion acoustics of rapidly changing profiles

Recently developed metasurfaces have been used for surface engineering applications. However, the ability to cloak or mimic reflective surfaces with a large in-plane phase gradient remains unexplored. One major challenge is that even with a small incidence angle, the strong acoustic impedance variation induced by the random height profile creates additional scattering and increases the complexity of the analysis and design of the metasurface. Here, we introduce an acoustic metasurface with 1/12 wavelength thickness to realize an acoustic carpet cloak for a randomly rapid-change surface and a virtual acoustic diffuser from a flat surface using a set of Helmholtz resonators. The limitation of the metasurface for large phase gradient application is explored based on a nonlocal model that considers the contributions from neighboring surface profiles. This study extends the integration of smart acoustic surface and may find applications of surface engineering such as in architectural acoustics.
Lumped-parameter-based thermal analysis for virtual prototyping of power electronics systems

Virtual prototyping of power electronics systems can enable rapid and iterative design process, and can satisfy the need for higher power density. Thermal modelling is a key part in the multi-physics virtual prototyping. In this paper, the T-type steady-state lumped-parameter model (LPM) for a naturally cooled heat sink with a power device on top is established. Empirical equations for the convection heat-transfer coefficient calculation are provided, which prove to be much faster compared with computational fluid dynamics (CFD) with acceptable error. The sensitivity of the predicted temperature to the mesh size of the heat sink for the LPM method is analysed, providing a way to find the most efficient mesh size. Lastly, the LPM is compared to the finite difference method (FDM) in steady state and shows competitive advantages in terms of speed and accuracy.
Fault diagnosis using kernel principal component analysis for hot strip mill

In the field of hot rolling process monitoring, the activation of non-linear dynamic behaviour may render the procedure of fault diagnosis more difficult. Principal component analysis (PCA) is known as a popular method for diagnosis but as it is basically a linear method, it may pass over some useful non-linear features of the system behaviour. One possible extension of PCA is kernel PCA (KPCA), owing to the use of non-linear kernel functions that allow introduction of non-linear dependences between variables. The objective of this study is to address the problem of fault diagnosis (in terms of non-linear activation) in hot rolling automation system using a KPCA-based method. The detection is achieved by comparing the subspaces between the reference and a current state of the system through the concept of subspace angle. It is shown in this work that the exploitation of the measurements in the form of KPCA can effectively improve the detection results.
Polarization conversion with a photonic crystal slab

We show that a photonic crystal slab can enable efficient polarization conversion. Two mechanisms are identiﬁed. The ﬁrst mechanism relies on the anisotropy of the bulk properties of the metamaterial and is mediated by interferences. The second mechanism is due to the resonant excitation of leaky surface waves at the interface of the photonic crystal. The latter is analogous to the polarization conversion by excitation of surface plasmons on a metallic grating. This is another example of the possibility of mimicking plasmonics with photonic crystals.
Ju l 2 01 0 Position-dependent noncommutativity Strings from position-dependent noncommutativity

We introduce a new set of noncommutative space-time commutation relations in two space dimensions. The space-space commutation relations are deformations of the standard flat noncommutative space-time relations taken here to have position dependent structure constants. Some of the new variables are non-Hermitian in the most natural choice. We construct their Hermitian counterparts by means of a Dyson map, which also serves to introduce a new metric operator. We propose PT like symmetries, i.e. antilinear involutory maps, respected by these deformations. We compute minimal lengths and momenta arising in this space from generalized versions of Heisenberg’s uncertainty relations and find that any object in this two dimensional space is string like, i.e. having a fundamental length in one direction beyond which a resolution is impossible. Subsequently we formulate and partly solve some simple models in these new variables, the free particle, its PT -symmetric deformations and the harmonic oscillator.
Gender and Authorship Categorisation of Arabic Text from Twitter Using PPM

In this paper we present gender and authorship categorisationusing the Prediction by Partial Matching (PPM) compression scheme for text from Twitter written in Arabic. The PPMD variant of the compression scheme with different orders was used to perform the categorisation. We also applied different machine learning algorithms such as Multinational Naïve Bayes (MNB), K-Nearest Neighbours (KNN), and an implementation of Support Vector Machine ( LIBSVM ), applying the same processing steps for all the algorithms. PPMD shows significantly better accuracy in comparison to all the other machine learning algorithms, with order 11 PPMD working best, achieving 90 % and 96% accuracy for gender and authorship respectively.
A Review on Modern Age Antennas

Antenna plays a vital role in this modern wireless age. It is an important element of today’s wireless communication systems. They are used in various systems like radio broadcasting, satellite communication, cell phones, radar, wearable devices etc. It acts as a device used to convert the electrical current into Electromagnetic waves and viceversa. Now-a-days, the growth in usage of compact handheld devices makes it more attentive topic in the field of research and antenna designing. For effective communication between two points, antenna should be designed very precisely. In this paper, a review on antennas, its types, applications in various fields are discussed. The antenna designing software with solvers are also discussed. Keywords— Modern age antennas, PIFA,Microstrip antennas,Antenna designing,HFSS
Cooperative Routing in Multi-Radio Multi-Hop Wireless Network

There are many recent interests on cooperative communication (CC) in wireless networks. Despite the large capacity gain of CC in small wireless networks, CC can result in severe interference in large networks and even degraded throughput. The aim of this chapter is to concurrently exploit multi-radio and multi-channel (MRMC) and CC technique to com-bat co-channel interference and improve the performance of multi-hop wireless network. Our proposed solution concurrently considers cooperative routing, channel assignment, and relay selection and takes advantage of both MRMC technique and spatial diversity to improve the throughput. We propose two important metrics, contention-aware channel utilization routing metric (CACU) to capture the interference cost from both direct and cooperative transmission, and traffic aware channel condition metric (TACC) to evalu ate the channel load condition. Based on these metrics, we propose three algorithms for interference-aware cooperative routing, local channel adjustment, and local path and relay adaptation, respectively, to ensure high-performance communications in dynamic wire- less networks. Our algorithms are fully distributed and can effectively mitigate co-channel interference and achieve cooperative diversity gain. To our best knowledge, this is the first distributed solution that supports CC in MRMC networks. Our performance studies demonstrate that our algorithms can significantly increase the aggregate throughput.
A lithornithid (Aves: Palaeognathae) from the Paleocene (Tiffanian) of southern California

The proximal end of a bird humerus recovered from the Paleocene Goler Formation of southern California is the oldest Cenozoic record of this clade from the west coast of North America. The fossil is characterized by a relatively large, dorsally-positioned head of the humerus and a subcircular opening to the pneumotricipital fossa, consistent with the Lithornithidae among known North American Paleocene birds, and is similar in size to Lithornis celetius. This specimen from the Tiffanian NALMA extends the known geographic range of lithornithids outside of the Rocky Mountains region in the United States. The inferred coastal depositional environment of the Goler Formation is consistent with a broad ecological niche of lithornithids. The age and geographic distribution of lithornithids in North America and Europe suggests these birds dispersed from North America to Europe in the Paleocene or by the early Eocene. During the Paleogene the intercontinental dispersal of lithornithids likely occurred alongside other known bird and mammalian movements that were facilitated by climatic and sea level changes.
Update on paratuberculosis: 1. Epidemiology of Johne's disease and the biology of Mycobacterium paratuberculosis

Epidemiology of Johne’s disease Prevalence Johne’s disease, a granulomatous enteritis of ruminants caused by Mycobacterium paratuberculosis (Figure 1) and manifest clinically by chronic diarrhoea and progressive emaciation, has been reported on every continent. Sweden and some states in Australia are the only regions of the world that can claim freedom from Johne's disease based upon a reliable disease reporting system and extensive surveys using laboratory tests. The reported prevalence of infected animals by country is at least partially a reflection of the diligence with which veterinarians and animal owners look for the disease. Johne's disease is more common in dairy cattle than in other ruminants; this is likely a function of animal husbandry. In many countries Johne's disease is fairly common in small ruminants like sheep and goats but precise survey data have not been published. In the early 1990s, Johne’s disease was found in relatively few sheep flocks in Australia, prompting efforts to eradicate the disease. Since then, with improved diagnostics and surveillance efforts, the disease has been found to be fairly widespread, particularly in the state of New South Wales, and control strategies that include vaccination are being considered.
PRACTICE CAPE TOWN, SOUTH AFRICA 3-5 NOVEMBER 2010

The application of the Living Lab (LL) approach to social-technical innovation to the Digital Doorway Initiative in Zandspruit near Johannesburg is outlined in the context of the initiative’s evolution from an educational project to a broader community innovation initiative. The relationship between different stakeholders is explored in a theoretical and practical sense as a future research and practice challenge for both the study of ICTs in society (in this case, a poor community), and the fostering of community-driven innovation. The activity also offers a research challenge for understanding the cultural transformations that are necessary for bringing about more effective integration between technical and social-technical viewpoints about design and research in a social context. Current and projected community-based research activity is also outlined.
Structure and Biomass of Four Lowland Neotropical Forests

We contrasted the structure and biomass of four lowland Neotropical forests (La Selva, Costa Rica; Barro Colorado Island, Panama; Cocha Cashu, Peru; and KM41, Brazil) to determine if commonalities exist within and among forests differing in latitude, rainfall, seasonality, and soil fertility. We examined the effect of soil fertility specifically by measuring the density and basal area of trees, lianas, and palms on two soil types differing in fertility at each site. We used allometric relationships to estimate the contribution of the various life‐forms to total aboveground biomass (AGB) and compared two relationships for trees 30 cm diameter or greater. Estimated liana density and AGB were similar among sites, but the density and AGB of trees and palms, estimated using diameter alone, differed significantly. Basal area and AGB of trees 10 cm diameter at breast height (DBH) or greater differed among forests and averaged 30.2 m2/ha and 250 Mg/ha, respectively. Cocha Cashu and KM41 had higher tree basal area and AGB than La Selva or Barro Colorado Island. Across forests, lianas and small trees (1–10 cm DBH) each contributed between 4 and 5 percent of the total AGB and small palms contributed ca 1 percent. Many forest inventories ignore lianas, as well as trees and palms less than 10 cm DBH, and therefore underestimate AGB by ca 10 percent. Soil type had little influence on the forest structure within sites, except at Cocha Cashu where total AGB was much higher and liana density much lower on the more fertile old floodplain Entisols than the serra firme Oxisols. Although total stem density, basal area, and some biomass components differed significantly among forests, they seemed less variable than other quantitative measures (e.g., species richness).
Effect of COX-2 (PGE2) and IL-6 on Prostate Cancer Bone Mets

Abstract : We hypothesize that (1) prostate cancer cells that express cyclooxygenase-2 (COX-2), prostaglandin E2(PGE2) and interleukin-6 (IL-6) display enhanced bone targeting and (2) the level of expression of COX-2, PGE2 and IL-6 in established bone metastases determines the overall bone response, with lower vs. higher cytokine levels inducing osteoblastic vs. osteolytic responses, respectively. We utilize two human prostate cancer cell lines (MDA-PCa-2B that expresses low levels of COX-2 and PGE2 and produces osteoblastic lesions vs. PC-3 that expresses high levels COX-2/PGE2 and induces osteolytic mets). Over the past year, we demonstrated that (1) low levels of PGE2 stimulate preosteoblast cell growth, differentiation and Wnt signaling (2) Forced overexpression of COX-2 in MDA-PCa-2b cells induces the Wnt antagonist DKK-1 (3) PGE2 addition to PC-3 cells stimulates Dkk-1 (4) Forced overexpression of COX-2 in MDA-PCa-2B cells inhibits preosteoblastic cell growth in co-culture. Over the next and final year of the grant proposal we will determine the effects of COX-2/PGE2 expression in the two PCa cell lines on in vivo bone targeting and bone reaction
REGULATION AND STABILITY OF HOST-PARASITE

(1) Several models describing the dynamics of host-parasite associations are discussed. (2) The models contain the central assumption that the parasite increases the rate of host mortalities. The parasite induced changes in this rate are formulated as functions of the parasite numbers per host and hence of the statistical distribution of the parasites within the host population. (3) The parameters influencing the ability of the parasite to regulate the growth of its host's population, and the stability of parasite induced equilibria, are examined for each model. (4) Three specific categories of population processes are shown to be of particular significance in stabilizing the dynamical behaviour of host-parasite interactions and enhancing the regulatory role of the parasite. These categories are overdispersion of parasite numbers per host, nonlinear functional relationships between parasite burden per host and host death rate, and density dependent constraints on parasite population growth within individual hosts.
The Role of Inflammatory Biomarkers in the Assessment of Coronary Artery Disease

Coronary artery disease (CAD) is the world’s leading cause of illness and death. In 2005, approximately 7.6 million deaths were attributed to coronary artery disease, accounting for almost 13% of the total deaths (WHO, 2011). From a pathophysiological point of view the disease could be considered as a severe clinical manifestation of atherosclerosis (Mallat & Tedgui, 2001). The disruption of an atherosclerotic plaque with superimposed thrombosis had been identified as the main cause of acute coronary syndromes, including acute myocardial infarction (AMI), and sudden death (Gensini & Dilaghi, 2002; Shah, 2003). The initially silent progression of arterial plaque, prompted by classic risk factors (including hypertension, diabetes mellitus, dyslipidaemia, age, stress, physical inactivity, dietary habits and cigarette smoking), is followed by a phase of acute or chronic progression toward an increasing degree of stenosis that eventually causes thrombosis (Gensini & Dilaghi, 2002; Fuster et al., 2005). Plaque disruption and/or endothelial activation represent the main trigger event for AMI, through exposure of plaque thrombogenic components to platelets and to clotting components of flowing blood. In this phase, haemostasis related risk factors and platelet status play a crucial role. However, current research supports the view of atherosclerosis as an inflammatory process that initiates and promotes lesion development to the point of acute thrombotic complications and clinical events. Thus, the time has come to embrace inflammation as a common pathway for atherogenic risk factors and for providing new opportunities for therapeutic intervention (Libby, 2003). Acute myocardial infarction is a critical clinical presentation of coronary artery disease in many asymptomatic patients and often the event is fatal. Establishing the presence of coronary lesions either in asymptomatic patients or in symptomatic patients with acute or chronic chest pain can be a challenging task. Consequently, major clinical research efforts
Deposition of multilayer optical coatings using closed field magnetron sputtering

"Closed field" magnetron (CFM) sputtering offers a flexible and high throughput deposition process for optical coatings and thin films required in display technologies. CFM sputtering uses two or more different metal targets to deposit multilayers comprising a wide range of dielectrics, metals and conductive oxides. Moreover, CFM provides a room temperature deposition process with high ion current density, low bias voltage and reactive oxidation in the entire volume around the rotating substrate drum carrier, thereby producing films over a large surface area at high deposition rate with excellent and reproducible optical properties. Machines based on the Closed Field are scaleable to meet a range of batch and in-line size requirements. Typically, thin film thickness control to < ±1% is accomplished simply using time, although optical monitoring can be used for more demanding applications. Fine layer thickness control and deposition of graded index layers is also assisted with a specially designed rotating shutter mechanism. This paper presents data on optical properties for CFM deposited optical coatings, including anti-reflection, IR blocker and colour control and thermal control filters, graded coatings, narrowband filters as well as conductive transparent oxides such as indium tin oxide. Benefits of the CFM sputter process are described.
Dealing with Interleaved Event Inputs for Intrusion Detection

We propose a method to detect intrusions given interleaved event sequences. The event sequences include alert sequences in a network and running processes on a host which are both considered to contain mixed items with unpredictable orders in the temporal domain. To detect intrusions with the interleaved event sequences, one of the major difficulties is to separate the interleaved events that are produced by different users or for different intentions. We propose a novel ATM algorithm to extract subsequences characterizing different behaviors; afterwards, a method that is based on graph representation is used to detect intrusions. In a network, there could be intruders who plan a DDoS attack on an environment that has mostly benign users. The proposed method can distinguish between different pieces of network data owning different activities and locate where the intrusive behavior is. On a host, users without enough privilege may gain access to data that they are not supposed to see. The proposed method can detect the event subsequence that is associated with the unauthorized activity given a usage sequence from users such as process, command or log sequences. Given the network and host-based data, the experiment results show that the proposed method can reach high detection accuracy while maintaining low false positives in the intrusion detection task. Moreover, the graphs produced by the proposed ATM method are also compared to the graphs generated from other methods to confirm that the graph representation indeed describes the high confidence transitions between events.
Extended depth-of-field in integral imaging by depth-dependent deconvolution

Integral Imaging is a technique to obtain true color 3D images that can provide full and continuous motion parallax for several viewers. The depth of field of these systems is mainly limited by the numerical aperture of each lenslet of the microlens array. A digital method has been developed to increase the depth of field of Integral Imaging systems in the reconstruction stage. By means of the disparity map of each elemental image, it is possible to classify the objects of the scene according to their distance from the microlenses and apply a selective deconvolution for each depth of the scene. Topographical reconstructions with enhanced depth of field of a 3D scene are presented to support our proposal.