Miracle-dz/UniFAR-FTUs huggingface dataset:
A Cylindrical Virtual Space Based Catadioptric Real-time Panorama Imaging System

Since it has small field of view and only records the light intension of scene, the regular optical imaging system is short of immersion and stereo vision. The needs for stereo apperception and recurrence of large field of view scene are emerging due to the development of robot navigation technology and virtual reality technology. Some panoramic stereo imaging technologies have been developed under the drive of optoelectronics and computer vision and graphics. In this paper, a new method to construct cylindrical image-based virtual space (IBVS) automatically with smooth quadric convex curved mirror catadioptric imaging is proposed, and the projection transformation with conic reflection surface and telecentric lens is described in detail. The method to transform pixel point at image plane taken by camera into field of view image along gaze direction in cylindrical IBVS is given. The prototype instrument of system is designed, and its hardware implementation is given. The experiment result shows that the instrument can construct real-time IBVS that has wide field of view and better imaging effect. The method would enhance the capability of surveillance and reconnaissance and self defense in battlefield
Reputations and Economic Performances in Dictatorships

We show that reputational effects may explain differences in economic performances of dictatorial or authoritarian governments. A good reputation convinces citizens that the dictator will exert high effort in economic performance. With replacement, a dictator exerts high effort only if its foregone rent is not too large. Without replacement, the dictator succeeds in convincing the citizens of its competence but may go “bad” subsequently. In contrast, electoral contest allows citizens to punish a government by imposing a high significant cost with their votes at the polls after any reduction in beliefs in the government’s competence. JEL Classifications: D72, O12, P16
Tip of the red giant branch distance for the Sculptor group dwarf ESO 540-032 ?

We present the rst VICCD photometry for the Sculptor group galaxy ESO 540-032 obtained at the Very Large Telescope UT1+FORS1. The (I; V I) colour-magnitude diagram indicates that this intermediate- type dwarf galaxy is dominated by old, metal-poor ((Fe=H) 1:7 dex) stars, with a small population of slightly more metal-rich ((Fe=H) 1:3 dex), young (age 150 500 Myr) stars. A discontinuity in the I-band luminosity function is detected at I0 =2 3:44 0:09 mag. Interpreting this feature as the tip of the red giant branch and adopting MI = 4:20 0:10 mag for its absolute magnitude, we have determined a Population II distance modulus of (m M)0 =2 7:64 0:14 mag (3:4 0:2 Mpc). This distance conrms ESO 540-032 as a member of the nearby Sculptor group but is signicantly larger than a previously reported value based on the Surface Brightness Fluctuation (SBF) method. The results from stellar population synthesis models suggest that the application of the SBF technique on dwarf galaxies with mixed morphology requires a detailed knowledge of the underlying stellar composition and thus oers no advantage over a direct distance measurement using the tip of the red giant branch as distance indicator. We produce the surface brightness proles for ESO 540-032 and derive the photometric and structural parameters. The global properties follow closely the relations between metallicity and both absolute magnitude and central surface brightness dened by dwarf elliptical galaxies in the Local Group. Finally, we identify and discuss a non-stellar object near the galaxy center which may resemble a globular cluster.
Mathematical Modelling of the Neurochemical Processes in Schizophrenia

Schizophrenia is an endogenous psychosis with a 1 \% prevalence in world population. Several pharmacological studies suggest that alterations in the function of different neurotransmitter systems such as dopamine or glutamate are related to schizophrenic symptoms. This thesis represents mathematical models that are constructed to investigate the dynamical behaviour of the neurochemical systems in the human brain. These models formulate the anatomical properties and physiological processes of synapses, single brain compartments and large neurochemical pathways involved in the regulation of behaviour such as the basal ganglia and the limbic system. The interaction between the neurochemical systems and the electrophysiological activities are considered by modelling in different scales. In the synaptic scale, it has been shown that the transport of neurotransmitters in the synaptic cleft is merely governed by electrical forces than diffusion. The intra-synaptic concentration of neurotransmitters is modelled using partial differential equations and is coupled to the Hodgkin-Huxley equation (neurochemical modification) to model the effect of neurotransmitter-receptor binding in the generation of post-synaptic potentials. Considering the morphological and ultra-morphological studies of brain compartments, the averaged electrophysiological activity is modelled by integral equations respecting these internal structures. A system comprised by nonlinear delay differential equations is constructed to simulate the dynamical behaviour of neurochemical concentrations, coupled to the local electrophysiological activity of the compartments, on the brain pathways. By parameter sensitivity analysis, we have also investigated qualitatively the influence of certain anti-psychotic agents. Synchronized oscillations are experienced in electrophysiological systems. The neurotransmitter concentrations also demonstrate an oscillatory behaviour. The resulting oscillatory dynamics of these processes reveals a profound view on the relation between the dynamical behaviour of the neurochemical systems and the occurrence of psychotic states. These facts led us to establish a hypothesis on this relation, called the oscillation hypothesis of psychosis. Because of the general formulation of the models, these are not only useful for schizophrenia, but also for the investigations of other neurological diseases.
Clinical outcome of thymic lymphoepithelioma-like carcinoma: Case report of a 14-year-old male

Thymic carcinoma is a rare type of cancer, which arises from the thymic epithelium and accounts for ~1–4% of anterior mediastinal tumors in the USA. It rarely occurs in children, and is rarer among adults. Thymic lymphoepithelioma-like carcinoma (LELC) is an uncommon subtype of thymic carcinoma in children, however, it is one of the common histological subtypes of thymic carcinoma in adults. In the present study, a 14-year-old male patient presented to the Tokyo Metropolitan Cancer and Infectious diseases Center, Komagome Hospital (Tokoyo, Japan) with chest pain due to a large anterior mediastinal mass. The patient was histologically diagnosed with thymic LELC via a needle biopsy specimen, which was obtained from the primary site and indicated the Epstein-Barr virus infection, whose markers are also associated with oncogenesis. Immunohistochemical analysis demonstrated positive staining for keratin (AE1/AE3), epithelial membrane antigen, and latent membrane protein-1 and negative staining for cluster of differentiation 5. Thus, the patient was diagnosed with metastatic thymic LELC. First-line chemotherapy comprising of a cisplatin- and adriamycin-based chemotherapy regimen achieved a partial response, however, the patient succumbed within 10 months of the initial diagnosis due to rapid disease progression and refractory to subsequent cycles of chemotherapy. Thus, the current study, as well as previously reported cases, demonstrates that pediatric patients with thymic LELC continue to have a poor prognosis.
GreenDroid: A tool for analysing power consumption in the android ecosystem

This paper presents GreenDroid, a tool for monitoring and analyzing power consumption for the Android ecosystem. This tool instruments the source code of a giving Android application and is able to estimate the power consumed when running it. Moreover, it uses advanced classification algorithms to detect abnormal power consumption and to relate them to fragments in the source code. A set of graphical results are produced that help software developers to identify abnormal power consumption in their source code.
Distinguishing Infinite Graphs

The distinguishing number $D(G)$ of a graph $G$ is the least cardinal number $\aleph$ such that $G$ has a labeling with $\aleph$ labels that is only preserved by the trivial automorphism. We show that the distinguishing number of the countable random graph is two, that tree-like graphs with not more than continuum many vertices have distinguishing number two, and determine the distinguishing number of many classes of infinite Cartesian products. For instance, $D(Q_{n}) = 2$, where $Q_{n}$ is the infinite hypercube of dimension ${n}$.
Enhancing the interaction with information portals

Literature research in a scientific digital library can be a daunting and time consuming task: Retrieving the few documents containing information you currently need from a vast set of candidates, oftentimes not even knowing whether this information is in there at all, locally organizing and making sense of the retrieved documents, and somehow capturing parts of the acquired knowledge so it can be reacquired quickly when it is of use again at a later time. Current digital libraries assist the user in retrieving documents by providing sophisticated retrieval mechanisms, but because of the limited communication channel from the user to the retrieval system (usually restricted to the possibility of providing a small set of query terms), it is difficult to transform an information need to an appropriate query and subsequently estimate the quality of that query. Adding metadata to documents in the library and extending the search interfaces accordingly enriches communication, but this approach is limited to general data such as bibliographic information by the high costs of providing and maintaining domain specific knowledge bases for a rapidly growing collection of documents. Furthermore, support of digital libraries usually ends with the presentation of a list of retrieval results, so the user is
The Use of Two Culturing Methods in Parallel Reveals a High Prevalence and Diversity of Arcobacter spp. in a Wastewater Treatment Plant

The genus Arcobacter includes species considered emerging food and waterborne pathogens. Despite Arcobacter has been linked to the presence of faecal pollution, few studies have investigated its prevalence in wastewater, and the only isolated species were Arcobacter butzleri and Arcobacter cryaerophilus. This study aimed to establish the prevalence of Arcobacter spp. at a WWTP using in parallel two culturing methods (direct plating and culturing after enrichment) and a direct detection by m-PCR. In addition, the genetic diversity of the isolates was established using the ERIC-PCR genotyping method. Most of the wastewater samples (96.7%) were positive for Arcobacter and a high genetic diversity was observed among the 651 investigated isolates that belonged to 424 different ERIC genotypes. However, only few strains persisted at different dates or sampling points. The use of direct plating in parallel with culturing after enrichment allowed recovering the species A. butzleri, A. cryaerophilus, Arcobacter thereius, Arcobacter defluvii, Arcobacter skirrowii, Arcobacter ellisii, Arcobacter cloacae, and Arcobacter nitrofigilis, most of them isolated for the first time from wastewater. The predominant species was A. butzleri, however, by direct plating predominated A. cryaerophilus. Therefore, the overall predominance of A. butzleri was a bias associated with the use of enrichment.
The contribution of astrocytes to the regulation of cerebral blood flow

In order to maintain normal brain function, it is critical that cerebral blood flow (CBF) is matched to neuronal metabolic needs. Accordingly, blood flow is increased to areas where neurons are more active (a response termed functional hyperemia). The tight relationships between neuronal activation, glial cell activity, cerebral energy metabolism, and the cerebral vasculature, known as neurometabolic and neurovascular coupling, underpin functional MRI (fMRI) signals but are incompletely understood. As functional imaging techniques, particularly BOLD fMRI, become more widely used, their utility hinges on our ability to accurately and reliably interpret the findings. A growing body of data demonstrates that astrocytes can serve as a “bridge,” relaying information on the level of neural activity to blood vessels in order to coordinate oxygen and glucose delivery with the energy demands of the tissue. It is widely assumed that calcium-dependent release of vasoactive substances by astrocytes results in arteriole dilation and the increased blood flow which accompanies neuronal activity. However, the signaling molecules responsible for this communication between astrocytes and blood vessels are yet to be definitively confirmed. Indeed, there is controversy over whether activity-induced changes in astrocyte calcium are widespread and fast enough to elicit such functional hyperemia responses. In this review, I will summarize the evidence which has convincingly demonstrated that astrocytes are able to modify the diameter of cerebral arterioles. I will discuss the prevalence, presence, and timing of stimulus-induced astrocyte calcium transients and describe the evidence for and against the role of calcium-dependent formation and release of vasoactive substances by astrocytes. I will also review alternative mechanisms of astrocyte-evoked changes in arteriole diameter and consider the questions which remain to be answered in this exciting area of research.
Using Experimental Evolution to Investigate Geographic Range Limits in Monkeyflowers

Abstract Every species occupies a restricted geographic distribution, but it is unclear why natural selection at the range margin fails to increase tolerance to limiting environmental variables and thereby allow continual range expansion. Models indicate that the interplay of demographic asymmetries, dispersal, divergent natural selection, and adaptive trade-offs across spatially varying environments can give rise to stable range limits. Here we examine sister species of the monkeyflowers Mimulus cardinalis and M. lewisii to identify traits that might contribute to the evolution of the species' ranges and to ask whether adaptive trade-offs between environments can limit their geographic distribution. In the Sierra Nevada Mountains of California, M. cardinalis is found from low to mid elevation and M. lewisii is found from mid to high elevation. We transplanted segregating populations of interspecific hybrids to low and high elevation and cross-pollinated those that survived to flowering to create selected populations that evolved at low or high elevation. When grown in a common environment, the progeny of hybrids selected at high elevation flowered earlier compared to a greenhouse control population, whereas hybrids selected at low elevation displayed increased warm-temperature photosynthetic capacity. If adaptation to one environment entails a cost to adaptation in other environments, then selected hybrid populations should display reduced fitness, relative to an unselected control population, when grown in an environment in which they were not selected. Two such trade-offs were observed in this study, where hybrids selected at high elevation displayed reduced biomass when grown in temperatures characteristic of low elevation and hybrids selected at low elevation showed reduced resistance to freezing. These results identify traits under selection for range expansion and suggest that adaptive trade-offs can contribute to limiting the geographic distribution of species.
There are Gains, But can we Tell for Whom and Why? Predictors of Treatment Response Following Group Early Start Denver Model Intervention in Preschool - Aged Children with Autism Spectrum Disorder

There is significant variability in treatment outcomes across different interventions for Autism Spectrum Disorder and between individuals receiving the same intervention. This is likely related to the considerable phenotypic variability in ASD, which is posited to arise from a developmental cascade whereby a primary deficit in attention to social stimuli leads ultimately to widespread and diverse behavioural and functional difficulties. Purpose: To provide data on predictors of treatment outcome in a cohort of preschool - aged children with ASD receiving a group Early Start Denver Model (ESDM) intervention. Methodology: Forty-nine children (mean age 52 months) with ASD receiving group ESDM over 10 months were assessed pre - and post-intervention for ASD symptoms, developmental level, and adaptive functioning; together with measures of parental stress and coping. Results: Lower initial ASD symptomatology, particularly higher social affect and play skills, and younger age at entry to intervention predicted better outcomes. Conclusion: Reflective of hypotheses from the developmental cascade theory, younger age at entry predicted treatment gains, supporting efforts to include children in comprehensive treatment promptly. Moreover, greater initial social impairments led to relatively poorer outcomes, potentially suggesting that children with greater social affect difficulties may require a higher dose, or modified intervention, to that used in this study.
Dynamic Resource Pricing on Federated Clouds

Current large distributed systems allow users to share and trade resources. In cloud computing, users purchase different types of resources from one or more resource providers using a fixed pricing scheme. Federated clouds, a topic of recent interest, allows different cloud providers to share resources for increased scalability and reliability. However, users and providers of cloud resources are rational and maximize their own interest when consuming and contributing shared resources. In this paper, we present a dyanmic pricing scheme suitable for rational users requests containing multiple resource types. Using simulations, we compare the efficiency of our proposed strategy-proof dynamic scheme with fixed pricing, and show that user welfare and the percentage of successful requests is increased by using dynamic pricing.
Survey on Different Kinds of Malware and their Detection

As computer technology is becoming necessity in our day to day life in various aspects like education, communication, banking etc., computer system’s security becomes the main concern nowadays. Malware is getting its roots strong due to this emerging growth of high speed internet, so detection and removal of these malware in an effective manner is very essential. Malware detectors are the tools to protect against malware. The goal of this research is to study the concept of malware, its kinds and several detection techniques for their recognition. The main objective is to compare the detection techniques to check their effectiveness. The metrics used to compare the performance of these techniques have also been studied. Keywords— Malware, Detection Techniques, Signatures, Anomaly, Behaviour.
A Class of Highly Scalable Optical Crossbar-Connected Interconnection Networks (SOCNs) for Parallel Computing Systems

A class of highly scalable interconnect topologies called the Scalable Optical Crossbar-Connected Interconnection Networks (SOCNs) is proposed. This proposed class of networks combines the use of tunable Vertical Cavity Surface Emitting Lasers (VCSEL's), Wavelength Division Multiplexing (WDM) and a scalable, hierarchical network architecture to implement large-scale optical crossbar based networks. A free-space and optical waveguide-based crossbar interconnect utilizing tunable VCSEL arrays is proposed for interconnecting processor elements within a local cluster. A similar WDM optical crossbar using optical fibers is proposed for implementing intercluster crossbar links. The combination of the two technologies produces large-scale optical fan-out switches that could be used to implement relatively low cost, large scale, high bandwidth, low latency, fully connected crossbar clusters supporting up to hundreds of processors. An extension of the crossbar network architecture is also proposed that implements a hybrid network architecture that is much more scalable. This could be used to connect thousands of processors in a multiprocessor configuration while maintaining a low latency and high bandwidth. Such an architecture could be very suitable for constructing relatively inexpensive, highly scalable, high bandwidth, and fault-tolerant interconnects for large-scale, massively parallel computer systems. This paper presents a thorough analysis of two example topologies, including a comparison of the two topologies to other popular networks. In addition, an overview of a proposed optical implementation and power budget is presented, along with analysis of proposed media access control protocols and corresponding optical implementation.
Building Inverted Indexes Using Balanced Trees Over DHT Systems

Distributed Hash Table (DHT) systems are scalable and efficient data structures for object storage and location using a simple put/get interface. These systems place objects over a very large set of hosts using a multitude of algorithms in order to distribute objects uniformly among hosts using logarithmic (or lower) costs for routing table sizes and message hops [1, 2]. However, these systems assume that object size (storage load) and popularity (communication load) follow an uniform distribution. When unbalanced data is used on a DHT, hotspots are created at some specific (random) hosts. Although one might argue that storage is not a critical resource, due to the current trend on secondary storage capacity, storing such large objects creates network bottlenecks, which in turn may limit data availability on very large heterogeneous systems. A typical example of unbalanced data is a textual inverted index created from a collection of documents. When implementing an inverted index over a DHT system directly, one maps index keywords to DHT keys and their posting lists (document references) as the DHT values associated with the keys. Since an inverted index follows a Zipf distribution where some keywords are far more popular than others, hosts which store the popular words will have far more load than the others [3]. Later implementations handle hotspots by using a random factor at the DHT key in order to spread load over a DHT range instead of assigning it to a unique key [4]. However, even when using this method there is the possibility of overloading individual DHT keys. Having identified a limitation of current DHTs, the inability to handle unbalanced data, we propose a new algorithm to uniform both storage and network loads for each DHT key. Our distributed algorithm is based on balanced trees which were designed to split data into bounded sized blocks while minimizing the number of block accesses per operation. These design goals, which were imposed by secondary storage, are also valid for very large systems where network latency and bandwidth are important limitations. Unlike other tree-based routing infra-structures, which replace the DHT algorithms, we designed our algorithm to use a key based routing interface. Such decision allows our algorithm to use any DHT system as a basic building block since all these systems can provide a simple key based routing interface. Furthermore, by using a balanced tree rather than a Prefix Hash Tree our data structure grows as a function of the object size, creating well balanced trees, instead of growing spuriously due to the unbalanced prefix variations of data [5]. Our algorithm is capable of storing unbalanced data over a generic DHT without loosing scalability. By deploying a well known structure, B+ trees, over generic DHTs, we are building a generic index functionality that c n be used as a basic building block for new large-scale P2P applications.