Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated Collage Generation - With Intent

One reason why software undertaking creative tasks might be perceived of as uncreative is its lack of overall purpose or intent. In computational creativity projects, while some skillful aspects may be undertaken by the computer, there is usually a person driving the process, by making decisions with regard to the intent of the artefact being produced. Such human intervention can take different forms, for instance via the supplying of background information in scientific discovery tasks, or making choices during an evolutionary art session. We are interested in whether a notion of purpose could be projected onto The Painting Fool, an automated painter we hope will one day be taken seriously as a creative artist in its own right [3, 5]. Starting with the maxim that good art makes you think, we have enabled The Painting Fool to produce visual art specifically to invite the viewer to interpret the pieces in the context of the world around them, i.e., to make a point about a current aspect of society. However, we do not prescribe what aspect of modern life it should depict, nor do we describe the art materials – in this case digital images – it should use. Hence, we effectively opt out of specifying a purpose for any individual piece of art. As described in section 2, the software starts with an instruction to access sources of news articles at regular intervals. Then, via text manipulation, text analysis, image retrieval, image manipulation, scene construction and non-photorealistic rendering techniques, the system produces a collage which depicts a particular news story. This is initial work, and more effort is needed to produce collages of more aesthetic and semantic value. We present some preliminary results in section 3, including some illustrative examples and feedback from viewers of the collages produced. In section 4, we describe the next stages for this project.
Optimizing user exploring experience in emerging e-commerce products

E-commerce has emerged as a popular channel for Web users to conduct transaction over Internet. In e-commerce services, users usually prefer to discover information via querying over category browsing, since the hierarchical structure supported by category browsing can provide them a more effective and efficient way to find their interested properties. However, in many emerging e-commerce services, well-defined hierarchical structures are not always available; moreover, in some other e-commerce services, the pre-defined hierarchical structures are too coarse and less intuitive to distinguish properties according to users interests. This will lead to very bad user experience. In this paper, to address these problems, we propose a hierarchical clustering method to build the query taxonomy based on users' exploration behavior automatically, and further propose an intuitive and light-weight approach to construct browsing list for each cluster to help users discover interested items. The advantage of our approach is four folded. First, we build a hierarchical taxonomy automatically, which saves tedious human effort. Second, we provide a fine-grained structure, which can help user reach their interested items efficiently. Third, our hierarchical structure is derived from users' interaction logs, and thus is intuitive to users. Fourth, given the hierarchical structures, for each cluster, we present both frequently clicked items and retrieved results of queries in the category, which provides more intuitive items to users. We evaluate our work by applying it to the exploration task of a real-world e-commerce service, i.e. online shop for smart mobile phone's apps. Experimental results show that our clustering algorithm is efficient and effective to assist users to discover their interested properties, and further comparisons illustrate that the hierarchical topic browsing performs much better than existing category browsing approach (i.e. Android Market mobile apps category) in terms of information exploration.
Deterministic POMDPs Revisited

We study a subclass of POMDPs, called Deterministic POMDPs, that is characterized by deterministic actions and observations. These models do not provide the same generality of POMDPs yet they capture a number of interesting and challenging problems, and permit more efficient algorithms. Indeed, some of the recent work in planning is built around such assumptions mainly by the quest of amenable models more expressive than the classical deterministic models. We provide results about the fundamental properties of Deterministic POMDPs, their relation with AND/OR search problems and algorithms, and their computational complexity.
ETOPOSIDE (VP‐16) INHIBITS EPSTEIN‐BARR VIRUS DETERMINED NUCLEAR ANTIGEN (EBNA) SYNTHESIS

P d u a University School of Medicine, DrpurOment of Clinicul Medicine, Clinical Immunology Branch, via Giustiniani 2, 35128 Padua, ltul! Division of Medicine SBRGIO ZAMBONI Rovigo General Hospital, It& FRANCESCO LAVEDER RBNZO MARCOL~NCW headache, gastric intolerance, liver toxicity, erythema multiforme and thrombocytopenia are less frequent or rare. To date, the appearance of severe thrombocytopenia (platelet count between 1 and 8 x 109/1 has been reported only in four young women following a 7-10d danazol therapy for endometriosis (Arrowsmith & Dreis, 1986). We here report the case of a young woman admitted to our hospital for the sudden onset of thrombocytopenic purpura, menorrhagia and epistaxis following an 8 d danairol therapy (400 mg/d) for endometriosis. The patient did not receive any other drug or notice prodromal symptoms prior to haemorrhagic manifestations. On admission, the platelet count was <1 x 109/1, the spleen was not palpable, and the red cell and neutrophil counts were normal. The drug was stopped and the patient received platelet transfusions (4 units), high-dose i.v. immunoglobulins (1 g/kg/d for 2 d) and prednisone (1 mg/kg/d for 6d). The platelet count returned to 230 x 109/1 within 2d. Laboratory tests for antinuclear antibody, HW, anti-platelet antibody, fibrinogen and fibrinogen-derived products were negative. Before exposure to danazol the patient had never shown signs of thrombocytopenia and this did not recur after discontinuation of prednisone. Thle pathogenetic mechanism of danazol-induced thrombocytopenia is still unknown, even if the time elapsing between the beginning of the therapy and the appearance of the thrombocytopenia, observed in our and in previously reported cases, suggests an immunological REFERENCES
IR-NLI : An Expert Natural Language Interface to Online Data Bases

Constructing natural language interfaces to computer systems often requires achievment of advanced reasoning and expert capabilities in addition to basic natural language understanding. In this paper the above issues are faced in the frame of an actual application concerning the design of a natural language interface for the access to online information retrieval systems. After a short discussion of the peculiarities of this application, which requires both natural language understanding and reasoning capabilities, the general architecture and fundamental design criteria of a system presently being developed at the University of Udine are then presented. The system, named IR-NLI, is aimed at allowing non-technical users to directly access through natural language the services offered by online data bases. Attention is later focused on the basic functions of IR-NLI, namely, understanding and dialogue, strategy generation, and reasoning. Knowledge represenetation methods and algorithms adopted are also illustarted. A short example of interaction with IR-NLI is presented. Perspectives and directions for future research are also discussed.
PDMS valves in DNA computers

DNA computing is an interdisciplinary field accessing the possibility for the use of biomolecules, such as DNA, RNA and proteins, as a computational or control tool. Traditionally, DNA computers were thought to compete with electronic computers to solve, for example, NP-complete problems. However recently, there has been a focus shift to biomedical applications. One form of DNA computing is performed in microfluidics. A network of microreactors decides the computational aspects and DNA is the tool for selection procedures. To control complex microflow systems like this, a series of pneumatic valves are used to control the flow direction, i.e. the information direction, and to contain DNA functionalised beads in the microreactors.
A Survey On Restraining Virus Propagation In Mobile Networks

Mobile communication systems are becoming increasingly significant and ubiquitous in people’s daily lives. Due to the enormous growth in mobile devices, virus propagation in mobile virus is an important security concern. A mobile virus is nothing but malicious computer software that targets mobile phones and causing the collapse of the system and leakage of confidential information. In the wireless communication viruses can even jam wireless services by transmitting thousands of spam messages and diminish the quality of voice communication. Because of the virus propagation, there is leakage of privacy data, additional service charges and exhaustion of battery power. These malware or virus is cell-phone worms that are malicious codes that exploit vulnerabilities in cell-phone software and propagate in networks via popular services such as Bluetooth and Multimedia Messaging Service (MMS). Worms are devastating to both users and network. A user can be instinctively charged for several messages created by the worm and the phone battery will be rapidly drained. Other reported worm damages expand from stealing user data and privacy to destroying hardware. Due to the severe damages of the mobile virus, it is significant for the users to gain a deep understanding of the propagation mechanisms of mobile viruses. So, in these circumstances there is a critical requirement for both users and service providers to further recognize the propagation mechanisms of mobile viruses and to deploy proficient countermeasures. Key terms: Mobile Networks, Phone virus, virus propagation, security, malware
Local Oriented Statistics Information Booster (LOSIB) for Texture Classification

Local oriented statistical information booster (LOSIB) is a descriptor enhancer based on the extraction of the gray level differences along several orientations. Specifically, the mean of the differences along particular orientations is considered. In this paper we have carried out some experiments using several classical texture descriptors to show that classification results are better when they are combined with LOSIB, than without it. Both parametric and non-parametric classifiers, Support Vector Machine and k-Nearest Neighbourhoods respectively, were applied to assess this new method. Furthermore, two different texture dataset were evaluated: KTH-Tips-2a and Brodatz32 to prove the robustness of LOSIB. Global descriptors such as WCF4 (Wavelet Co-occurrence Features), that extracts Haralick features from the Wavelet Transform, have been combined with LOSIB obtaining an improvement of 16.94% on KTH and 7.55% on Brodatz when classifying with SVM. Moreover, LOSIB was used together with state-of-the-art local descriptors such as LBP (Local Binary Pattern) and several of its recent variants. Combined with CLBP (Complete LBP), the LOSIB booster results were improved in 5.80% on KTH-Tips 2a and 7.09% on the Brodatz dataset. For all the tested descriptors, we have observed that a higher performance has been achieved, with the two classifiers on both datasets, when using some LOSIB settings.
Selling privacy at auction

We initiate the study of markets for private data, through the lens of differential privacy. Although the purchase and sale of private data has already begun on a large scale, a theory of privacy as a commodity is missing. In this paper, we propose to build such a theory. Specifically, we consider a setting in which a data analyst wishes to buy information from a population from which he can estimate some statistic. The analyst wishes to obtain an accurate estimate cheaply, while the owners of the private data experience some cost for their loss of privacy, and must be compensated for this loss. Agents are selfish, and wish to maximize their profit, so our goal is to design truthful mechanisms. Our main result is that such problems can naturally be viewed and optimally solved as variants of multi-unit procurement auctions. Based on this result, we derive auctions which are optimal up to small constant factors for two natural settings: When the data analyst has a fixed accuracy goal, we show that an application of the classic Vickrey auction achieves the analyst's accuracy goal while minimizing his total payment. When the data analyst has a fixed budget, we give a mechanism which maximizes the accuracy of the resulting estimate while guaranteeing that the resulting sum payments do not exceed the analyst's budget. In both cases, our comparison class is the set of envy-free mechanisms, which correspond to the natural class of fixed-price mechanisms in our setting. In both of these results, we ignore the privacy cost due to possible correlations between an individual's private data and his valuation for privacy itself. We then show that generically, no individually rational mechanism can compensate individuals for the privacy loss incurred due to their reported valuations for privacy. This is nevertheless an important issue, and modeling it correctly is one of the many exciting directions for future work.
Impact of Expanding Criteria for Resectability of Colorectal Metastases on Short- and Long-Term Outcomes After Hepatic Resection

Background:An expansion of resectability criteria of colorectal liver metastases (CLM) is justified provided “acceptable” short-term and long-term outcomes. The aim of the present study was to ascertain this paradigm in an era of modern liver surgery. Methods:All consecutive patients who underwent hepatic resection for CLM at our institute between 1990 and 2010 were included in the study. Ninety-day mortality and morbidity rates were determined in the total study population and in 2 separate time periods (group I: 1990–2000; group II: 2000–2010). Similarly, overall and progression-free survival rates were determined. Independent predictors of postoperative morbidity were identified at multivariate analysis. Results:Between 1990 and 2010, 1394 hepatectomies were performed in 1028 patients. Overall perioperative mortality and postoperative morbidity rates were 1.3% and 33%, respectively. Although patients in group II were older, had more often comorbid illnesses, and presented with more extensive liver disease, similar perioperative mortality rates were observed (1.1% in group I and 1.4% in group II; P = 0.53). A trend toward a higher morbidity rate was observed in group II (34% vs 31% in group I; P = 0.16). Independent predictors of postoperative morbidity were: treatment between 2000 and 2010, total hepatic ischemia time of 60 minutes or more, maximum size of CLM of 30 mm or more at histopathology, and presence of abnormalities in the nontumoral liver parenchyma. Although a trend toward lower overall survival was observed in patients with significant postoperative complications, no significant differences were observed in long-term outcomes between both treatment periods. Conclusion:After an aggressive multidisciplinary treatment of CLM, acceptable overall mortality and morbidity rates were observed. Perioperative mortality rates did not differ according to treatment period; however, more recently operated patients experienced more postoperative complications. These favorable short-term outcomes, without worsening of long-term outcomes, justify an expansion of the criteria for resectability in this patient category.
Detecting Opinion Polarities using Kernel Methods

We investigate the application of kernel methods to representing both structural and lexical knowledge for predicting polarity of opinions in consumer product review. We introduce any-gram kernels which model lexical information in a significantly faster way than the traditional n-gram features, while capturing all possible orders of n-grams n in a sequence without the need to explicitly present a pre-specified set of such orders. We also present an effective format to represent constituency and dependency structure together with aspect terms and sentiment polarity scores. Furthermore, we modify the traditional tree kernel function to compute the similarity based on word embedding vectors instead of exact string match and present experiments using the new models.
Multimodal Imaging in Rat Model Recapitulates Alzheimer's Disease Biomarkers Abnormalities

Imaging biomarkers are frequently proposed as endpoints for clinical trials targeting brain amyloidosis in Alzheimer's disease (AD); however, the specific impact of amyloid-β (Aβ) aggregation on biomarker abnormalities remains elusive in AD. Using the McGill-R-Thy1-APP transgenic rat as a model of selective Aβ pathology, we characterized the longitudinal progression of abnormalities in biomarkers commonly used in AD research. Middle-aged (9–11 months) transgenic animals (both male and female) displayed mild spatial memory impairments and disrupted cingulate network connectivity measured by resting-state fMRI, even in the absence of hypometabolism (measured with PET [18F]FDG) or detectable fibrillary amyloidosis (measured with PET [18F]NAV4694). At more advanced ages (16–19 months), cognitive deficits progressed in conjunction with resting connectivity abnormalities; furthermore, hypometabolism, Aβ plaque accumulation, reduction of CSF Aβ1-42 concentrations, and hippocampal atrophy (structural MRI) were detectable at this stage. The present results emphasize the early impact of Aβ on brain connectivity and support a framework in which persistent Aβ aggregation itself is sufficient to impose memory circuits dysfunction, which propagates to adjacent brain networks at later stages. SIGNIFICANCE STATEMENT The present study proposes a “back translation” of the Alzheimer pathological cascade concept from human to animals. We used the same set of Alzheimer imaging biomarkers typically used in large human cohorts and assessed their progression over time in a transgenic rat model, which allows for a finer spatial resolution not attainable with mice. Using this translational platform, we demonstrated that amyloid-β pathology recapitulates an Alzheimer-like profile of biomarker abnormalities even in the absence of other hallmarks of the disease such as neurofibrillary tangles and widespread neuronal losses.
Cascaded model predictive speed control of a permanent magnet synchronous machine

This paper proposes a model predictive speed control of a permanent magnet synchronous machine (PMSM). The control scheme has a cascade architecture, where the inner loop uses a finite set model predictive control scheme (FS-MPC) for the electrical subsystem, and the outer loop uses a dead-beat model predictive control for the mechanical subsystem. Due to the discrete nature of the control platform an accurate discrete model of the systems is necessary. In this work both systems, electrical and mechanical, are discretizated with a second order Taylor method. Simulation results are presented to validate the proposed control strategy.
On the Low-Rank Approximation Arising in the Generalized Karhunen-Loeve Transform

We consider the low-rank approximation problem arising in the generalized Karhunen-Loeve transform. A sufficient condition for the existence of a solution is derived, and the analytical expression of the solution is given. A numerical algorithm is proposed to compute the solution. The new algorithm is illustrated by numerical experiments.
Analysis of Theoretical Limits of Forced-Air Cooling Using Advanced Composite Materials With High Thermal Conductivities

Cooling systems take a significant portion of the total mass and/or volume of power electronic systems. In order to design a converter with high power density, it is necessary to minimize the converter's cooling system volume for a given maximum tolerable thermal resistance. This paper theoretically investigates whether the cooling system volume can be significantly reduced by employing new advanced composite materials like isotropic aluminum/diamond composites or anisotropic highly orientated pyrolytic graphite. Another strategy to improve the power density of the cooling system is to increase the rotating speed and/or the diameter of the fan, which is limited by increasing power consumption of the fan. Fan scaling laws are employed in order to describe volume and thermal resistance of an optimized cooling system (fan plus heat sink), resulting in a single compact equation dependent on just two design parameters. Based on this equation, a deep insight into different design strategies and their general potentials is possible. The theory of the design process is verified experimentally for cooling a 10 kW converter. Further experimental results showing the result of the operation of the optimized heat sink are also presented.
Estimating Traffic Conditions At Metropolitan Scale Using Traffic Flow Theory

The rapid urbanization and increasing traffic have serious social, economic, and environmental impact on metropolitan areas worldwide. It is of a great importance to understand the complex interplay of road networks and traffic conditions. The authors propose a novel framework to estimate traffic conditions at the metropolitan scale using GPS traces. Their approach begins with an initial estimation of network travel times by solving a convex optimization program based on traffic flow theory. Then, they iteratively refine the estimated network travel times and vehicle traversed paths. Last, the authors perform a bilevel optimization process to estimate traffic conditions on road segments that are not covered by GPS data. The evaluation and comparison of the authors' approach over two state-of-the-art methods show up to 96.57% relative improvements. The authors have further conducted field tests by coupling road networks of San Francisco and Beijing with real-world GIS data, which involve 128,701 nodes, 148,899 road segments, and over 26 million GPS traces.
A classification of ductal plate malformations based on distinct pathogenic mechanisms of biliary dysmorphogenesis

Ductal plate malformations (DPMs) are developmental anomalies considered to result from lack of ductal plate remodeling during bile duct morphogenesis. In mice, bile duct development is initiated by the formation of primitive ductal structures lined by two cell types, namely ductal plate cells and hepatoblasts. During ductal plate remodeling, the primitive ductal structures mature to ducts as a result from differentiation of the ductal plate cells and hepatoblasts to cholangiocytes. Here, we report this process is conserved in human fetal liver. These findings prompted us to evaluate how DPMs develop in three mouse models, namely mice with livers deficient in hepatocyte nuclear factor 6 (HNF6), HNF1β, or cystin‐1 (cpk [congenital polycystic kidney] mice). Human liver from a patient with a HNF1B/TCF2 mutation, and from fetuses affected with autosomal recessive polycystic kidney disease (ARPKD) were also analyzed. Despite the epistatic relationship between HNF6, HNF1β, and cystin‐1, the three mouse models displayed distinct morphogenic mechanisms of DPM. They all developed biliary cysts lined by cells with abnormal apicobasal polarity. However, the absence of HNF6 led to an early defect in ductal plate cell differentiation. In HNF1β‐deficient liver, maturation of the primitive ductal structures was impaired. Normal differentiation and maturation but abnormal duct expansion was apparent in cpk mouse livers and in human fetal ARPKD. Conclusion: DPM is the common endpoint of distinct defects initiated at distinct stages of bile duct morphogenesis. Our observations provide a new pathogenic classification of DPM. (HEPATOLOGY 2011;)