Miracle-dz/UniFAR-FTUs huggingface dataset:
Prefronto-striatal physiology is associated with schizotypy and is modulated by a functional variant of DRD 2 Taurisano , Paolo 2014-07-09

Taurisano , P , Romano , R , Mancini , M , Di Giorgio , A , Antonucci , L A , Fazio , L , Rampino , A , Quarto , T , Gelao , B , Porcelli , A , Papazacharias , A , Ursini , G , Caforio , G , Masellis , R , Niccoli-Asabella , A , Todarello , O , Popolizio , T , Rubini , G , Blasi , G & Bertolino , A 2014 , ' Prefronto-striatal physiology is associated with schizotypy and is modulated by a functional variant of DRD2 ' Frontiers in Behavioral Neuroscience , vol 8 , 235 . DOI: 10.3389/fnbeh.2014. 00235
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The Immune Response is a new, and unique reference work covering basic and clinical principles in an up-to-date, and comprehensive fashion. Over the course of thirty chapters, written by extremely high profile authors, the broad scope of modern immunology is presented. The book is beautifully illustrated, with four-color figures and plates throughout. It is an invaluable resource for lecturers and a vital reference for research scientists throughout the life and medical sciences. * Current and thorough reference written by extremely high profile and respected authors * Dr. Tak Mak led the group that was the first to identify and clone human immune-system T-cell receptors in 1984 * An impressive array of basic and fundamental immunology questions are answered * Terminology is put into historical context that allows a fuller understanding of the area under discussion * Unique 'single voice' delivery of key subjects in immunology offer consistency of definition as complex concepts recur from chapter-to-chapter " …straight forward style…crystal clear definitions of complex immunological concepts. Uncomplicated style effortless for the reader to move from one section to the next, comfortable, unforced learning experience… " ". chapters are a delight to read.I {also} like the format of presentation with boxes for the specialists and plenty of illustration . "…very well written; it will be easily accessible to a broad readership, including undergraduate and graduate students…" ". this textbook from Mak and Saunders is very timely, reads very well, and should be of great interest to those wanting to get a start in understanding Immunology. " Abstract The Israeli isolate of Tomato yellow leaf curl geminivirus (TYLCV-Is) is a major tomato pathogen, causing extensive crop losses both in the New and Old World. Surprisingly, however, little is known about the molecular mechanisms of TYLCV-Is interactions with tomato cells. Here, we have identified a TYLCV-Is protein, V2, which acts as a suppressor of RNA silencing and which is unrelated to presently known viral suppressors. Specifically, V2, but not other proteins of TYLCV-Is, inhibited RNA silencing of a reporter transgene, GFP. This inhibition elevated the cellular levels of the GFP transcript and the GFP protein, but it had no apparent effect on the accumulation of GFP-specific short interfering RNAs (siRNAs), suggesting that TYLCV-Is V2 targets a step in the RNA silencing pathway which is subsequent to the Dicer-mediated cleavage of dsRNA. Visualization of the sub-cellular localization of TYLCV-Is V2 in plant protoplasts and tissues showed that this …
Journal of Language and Social Psychology Linguistic Context and Social Perception: Does Stimulus Abstraction Moderate Processing Style? Linguistic Context and Social Perception Does Stimulus Abstraction Moderate Processing Style? Language Abstraction and Depth of Processing

This article considers the role of linguistic context in social memory and social judgment. Two experiments compared perceivers' responses to person descriptions formulated at a high level of linguistic abstraction (adjectives/traits) versus a low level of linguistic abstraction (action verbs/behaviors). Based on the linguistic category model, together with prior empirical findings in psychology and linguistics, traits as compared with behavioral descriptions of a social target were hypothesized to elicit lower attention, poorer recall, and more expectancy-consistent impressions. Support for these hypotheses was obtained for a social target consisting of an individual as well as a nonentitative group. These results suggest a moderating role of linguistic context in inconsistency processing. Whereas concrete (behavioral) person descriptions elicited relatively deep, systematic processing, abstract (trait) person descriptions elicited more cursory, heuristic processing guided by the perceiver's expectancies regarding the target person. It is concluded that the methodological and substantive implications of linguistic context deserve greater attention in social psychological research. How do we deal with events or situations that deviate from our expectations? How do we respond when we witness our introverted scientist painting the town red? Such situations constitute critical moments when we must either reaffirm or adjust our views about people. surprisingly, how we reconcile inconsistencies in social information poses an important topic in social psychology. Research to date has addressed the cognitive processes underlying our responses to such inconsistencies. Although substantial headway has been made, a full understanding will require greater insight into the role played by con-textual factors A key contextual factor in social cognition is language. As Semin and Fiedler (1991) have noted, " Language enters social psychological phenomena at all imaginable levels, not only as they are manifested in everyday life but also in the construction of most if not all experimental settings and instructions, and most independent and dependent measures " (p. 2). Although prior research attests to the important role of language in social cognition (cf. Semin, 1995), no attention has been given to its potential impact on inconsistency processing and social judgment. The theoretical point of departure for the present investigation of the role of language in inconsistency processing was Semin and Fiedler's (1988, 1991) linguistic category model. This model offers a taxonomy of predicate types used in interpersonal communication. The present research focused on two of these predicate types, namely, action verbs (e.g., " The professor danced ") and adjectives (e.g., " The professor …
Assessing high performance: A South African case study

The dual challenge of globalisation of competition and global economic slowdown has increasingly forced businesses to do introspection not only in terms of their cost structures, but also in terms of their value proposition in search of sustainable organisational success. Given the limited influence that organisations, in general, have over their external environments, organisations have become more focussed on identifying internal constraints that inhibit rapid responses to market challenges and opportunities, and on identifying the interventions that are most critical to address these issues. This study focussed on the organisational characteristics that drive high performance, derived from De Waal’s high-performance organisation (HPO) framework, and proposed interventions to enhance the development of a high performance culture within the case company. Employing a self-administered questionnaire, it was possible to determine the performance of the case company across a range of five critical dimensions for high performance. A detailed analysis of each of the 35 questions provided an in-depth picture of the organisation’s strong and weak points and, from this analysis, specific actions to address the areas of weakness were identified. The study confirmed the robustness of the HPO framework employed as well as demonstrating its usefulness to management in terms of a detailed analysis of where the organisation was positioned in terms of the various high performance factors that are linked to organisational success.
Strategic Management and Information Systems: An Integrated Approach

Robson's book aims to provide information systems students with an understanding of strategic management concepts and to direct business studies students to apply their management understanding to information systems. This text explains what management is, and the tools and techniques employed for business analysis. The author covers both the strategic management of information systems and how to improve strategic management using information systems. This includes areas such as how to stucture and manage the IS resource, the risks to which coporate systems are exposed and the legislative framework. Each section is supported by mini-case material, longer case exercises and other material designed to stimulate discussion. It is suitable for undergraduates following programmes in information systems and business studies, as well as those on MBA and MSc programmes.
Comparison of Dexmedetomidine or Buprenorphine as an Adjuvant to Levo-Bupivacaine in Spinal Anaesthesia for Lower Limb Surgeries

DOI: 10.21276/sjams.2017. 5.12. 38 Abstract: Buprenorphine or dexmedetomidine used as adjuvant with 0.5% levo bupivacaine intrathecal to prolong the duration of analgesia. Eighty patients were randomly allocated to two groups, Group B received 60μg of buprenorphine with 15mg of 0.5% levo-bupivacaine and Group D received 5μg of dexmedetomidine with 15mg of 0.5% levo-bupivacaine. The onset and duration of sensory and motor blockade, the sensory and motor regression times, Ramsay sedation score in postoperative period were recorded. Hemodynamic changes and time to use first rescue analgesia were also recorded. There was no significant difference in the onset time of sensory block and motor block in group B and group D. Duration of analgesia was in Groups D and group B was 495.42±24.95 min. v/s 292.22±24.94 min. respectively, with p value<0.0001. The Duration of motor block was 416.67±28.22 min in group D, as compared to 205.45 ± 13.14 min in group B. Ramsay sedation score at the end of surgery was 3.82 ±0.67 in group D as compared to 2.07 ± 0.26 in group B. The time to give first rescue analgesia was significantly prolonged in Group D compared with Group B. Dexmedetomidine produces a prolongation in the duration of the motor and sensory block and postoperative analgesia when compared to buprenorphine with preserved hemodynamic stability.
Robust 3 D Hand Pose Estimation From Single Depth Images Using MultiView CNNs

Articulated hand pose estimation is one of core technologies in human–computer interaction. Despite the recent progress, most existing methods still cannot achieve satisfactory performance, partly due to the difficulty of the embedded high-dimensional nonlinear regression problem. Most existing data-driven methods directly regress 3D hand pose from 2D depth image, which cannot fully utilize the depth information. In this paper, we propose a novel multi-view convolutional neural network (CNN)-based approach for 3D hand pose estimation. To better exploit 3D information in the depth image, we project the point cloud generated from the query depth image onto multiple views of two projection settings and integrate them for more robust estimation. Multi-view CNNs are trained to learn the mapping from projected images to heat-maps, which reflect probability distributions of joints on each view. These multiview heat-maps are then fused to estimate the optimal 3D hand pose with learned pose priors, and the unreliable information in multi-view heat-maps is suppressed using a view selection method. Experimental results show that the proposed method is superior to the state-of-the-art methods on two challenging data sets. Furthermore, a cross-data set experiment also validates that our proposed approach has good generalization ability.
Determination of trace elements on some wild mushroom samples encountered from Western ghats of Karnataka

Eleven trace elements (Macro elements-Na, K, P, Ca, Mg and micro elements-Zn, Cu, Mn, Fe, Pb, Cd) in sixdifferent mushroom species were determined, usin g flame photometer, spectrophotometer and atomic ab sorption spectrometry after microwave digestion. The mushroo ms samples were collected from Western Ghats of Shi moga forest regions, Karnataka. The ranges of element co centrations for macro elements Na, K, P, Ca and Mg were 1.3±0.1-3.9±0.3,followed by 1.5±1.0-22.3±2.1, 1.4±0 . 1-6.4±0.5, 0.20±0.01-1.4±0.1 and 0.10±0.02-1.5±0.1 whereas micro elements such asZn, Cu, Mn, Fe, Pb and Cd wer e 42.1±3.3-65.4±5.3, 9.4±0.5-43.9±3.9, 13.9±1.2-94. 3±8.1, 179±10.8-381±25.4, 7.9±0.8-12.2±1.1 and 0.11±0.01-0 . 68±0.04mg/kg, respectively.
The Role of Network Processors in Active Networks

This paper argues that network processors can play an important role in the implementation and the deployment of active networks. The balance between hardware and software supplied with network processors addresses the demand for performance and programmability in active networks. The paper introduces network processors and discusses their relationship with active networks in general. Furthermore, a specific example of an advanced active networking function is given that demonstrates the capabilities of active networks based on network processors. The implementation is described for the IBM PowerNP network processor.
Structured Discriminative Models For Speech Recognition

Automatic Speech Recognition (ASR) systems classify structured sequence data, where the label sequences (sentences) must be inferred from the observation sequences (the acoustic waveform). The sequential nature of the task is one of the reasons why generative classifiers, based on combining hidden Markov model (HMM) acoustic models and N-gram language models using Bayes’ rule, have become the dominant technology used in ASR. Conversely, the machine learning and natural language processing (NLP) research areas are increasingly dominated by discriminative approaches, where the class posteriors are directly modelled. This paper describes recent work in the area of structured discriminative models for ASR. To handle continuous, variable length, observation sequences, the approaches applied to NLP tasks must be modified. This paper discusses a variety of approaches for applying structured discriminative models to ASR, both from the current literature and possible future approaches. We concentrate on structured models themselves, the descriptive features of observations commonly used within the models, and various options for optimizing the parameters of the models.
Preparing and Mounting Polymer Nanofibers onto Microscale Test Platforms

Because they can achieve a high degree of molecular chain alignment in comparison with their bulk counterparts, the mechanical and thermal properties of polymer nanofibers are of great interest. However, due to their nanometer-scale size, it is difficult to manipulate, grip, and test these fibers. Here, we demonstrate simple repeatable methods to transfer as-drawn fibers to micrometer-scale test platforms where their properties can be directly measured. Issues encountered and methods to minimize measurement artifacts are also discussed.
Handwritten Chinese Radical Recognition Using Nonlinear Active Shape Models

Handwritten Chinese characters can be recognized by first extracting the basic shapes (radicals) of which they are composed. Radicals are described by nonlinear active shape models and optimal parameters found using the chamfer distance transform and a dynamic tunneling algorithm. The radical recognition rate is 96.5 percent correct (writer-independent) on 280,000 characters containing 98 radical classes.
First Principles Simulations of Ice Surfaces

The surface of hexagonal ice Ih is investigated from first principles density functional calculations. Surface formation energies for several low-index surfaces are calculated. The formation of the Ih(0001) basal plane appears most favored. Therefore, the adsorption of water monomers on non-crystallographic sites of this plane is studied. Contrary to previous theoretical findings we do not find molecular adsorption energies larger than the bulk cohesive energy. However, the admolecules lower the ice surface energy due to stronger hydrogen bond formation. The monomer adsorption energies are found to be rather insensitive with respect to the detailed microscopic structure of the underlying substrate.
Schema on Read Modeling Approach as a Basis of Big Data Analytics Integration with EIS

— Big Data analytics refers to analysis of large volumes of data of various types and sources for patterns that identify potential risks and opportunities for an organization. This analysis almost certainly performed by highly skilled data analysis specialists such as data scientists in a flexible analytical environment called analytics sandbox. However, the most of organizations do not base their business on such flexible environments, but the traditional Enterprise Information Systems (EISs). In order to enable organizations to use the results of Big Data analysis specialists, Big Data analytics should be integrated with existing EISs, used by business users and consumers. This research focuses on the development of a model for Big Data analytics integration with existing EISs. We propose Big Data analytics integration based on schema on read modeling approach, and three scenarios of integration: 1) integration on the corporate data model level and on the data warehouse level, 2) integration on the corporate data model level and on the report level and 3) integration on the corporate data model level, on the data warehouse level and on the report level. In order to evaluate our approach we have realized the case study in the traffic domain. We carried out custom analysis of road traffic data on Hadoop platform and integrate it with the local SQL Server database, custom traffic geo-application and Business Intelligence tool, according to proposed integration approach.
Privtrans: Automatically Partitioning Programs for Privilege Separation

Privilege separation partitions a single program into two parts: a privileged program called the monitor and an unprivileged program called the slave. All trust and privileges are relegated to the monitor, which results in a smaller and more easily secured trust base. Previously the privilege separation procedure, i.e., partitioning one program into the monitor and slave, was done by hand [18, 28]. We design techniques and develop a tool called Privtrans that allows us to automatically integrate privilege separation into source code, provided a few programmer annotations. For instance, our approach can automatically integrate the privilege separation previously done by hand in OpenSSH, while enjoying similar security benefits. Additionally, we propose optimization techniques that augment static analysis with dynamic information. Our optimization techniques reduce the number of expensive calls made by the slave to the monitor. We show Privtrans is effective by integrating privilege separation into several open-source applications.
Thermal Stabilization of the Bulk-Heterojunction Morphology in Polymer:Fullerene Solar Cells Using a Bisazide Cross-Linker

After enhancing the power conversion efficiencies of organic solar cells beyond 10%, their long term stability has become the most urgent challenge in order to eventually integrate organic solar cells into end-user products. Solar devices may have to endure harsh conditions already during their fabrication, typically requiring lamination temperatures up to 120 C, critical for the initial performance of organic solar cells. In this work, polymer: fullerene bulk-heterojunctions are fabricated with significantly enhanced thermal stability at 120 C and beyond, by locking the bulk-heterojunction morphology through incorporating the novel cross-linkable bisazide 1,2-bis((4(azidomethyl)phenethyl)thio)ethane (TBA-X). Bulk-heterojunctions comprising various light-harvesting polymers and the industrially relevant fullerene acceptor PC61BM are investigated. Upon thermal annealing, the reference blends without the cross-linking TBA-X exhibit only moderate thermal stability and a relative loss of more than 70% of their initial performance, mainly originating from aggregation of the fullerene. In contrast, polymer:fullerene blends comprising TBA-X retain up to 90% of their initial performance despite the harsh thermal annealing at 120 C for up to 200 h.
Optimal All-to-All Personalized Exchange in General Shuffle-Exchange Networks

All-to-all personalized exchange communication has been widely applied in many parallel and distributed processing applications. In [14], by the Latin square method, Yang and Wang proposed an optimal all-to-all personalized exchange algorithm for the unique-path, self-routable multistage interconnection networks (MINs). All the networks considered in [14], including the famous shuffle-exchange networks, satisfy N = 2n+1, in which N is the number of inputs (outputs) and n + 1 is the number of stages of the network. Do notice that Yang and Wang’s algorithm requires the states of all the switches of a stage to be identical; i.e., the stage control technique is used. In [9], Padmanabham proposed the general shuffle-exchange network (GSEN) with 2n < N ≤ 2n+1. Since a GSEN is not necessarily a unique-path MIN, Yang and Wang’s algorithm may not apply. The purpose of this paper is to propose two optimal all-to-all personalized exchange algorithms for GSENs. Unlike Yang and Wang’s algorithm, we abandon the Latin square method and the requirement on the unique-path property. The first algorithm uses the stage control technique and works for arbitrary N . We will prove it is optimal when the stage control technique is assumed for 2n−1 + 2n ≤ N ≤ 2n+1. On the contrary, the second algorithm does not use the stage control technique and works only for N = 2n + 2. We will prove that it is optimal.
Real-Time Vehicle Make and Model Recognition System

A Vehicle Make and Model Recognition (VMMR) system can provide great value in terms of vehicle monitoring and identification based on vehicle appearance in addition to the vehicles’ attached license plate typical recognition. A real-time VMMR system is an important component of many applications such as automatic vehicle surveillance, traffic management, driver assistance systems, traffic behavior analysis, and traffic monitoring, etc. A VMMR system has a unique set of challenges and issues. Few of the challenges are image acquisition, variations in illuminations and weather, occlusions, shadows, reflections, large variety of vehicles, inter-class and intra-class similarities, addition/deletion of vehicles’ models over time, etc. In this work, we present a unique and robust real-time VMMR system which can handle the challenges described above and recognize vehicles with high accuracy. We extract image features from vehicle images and create feature vectors to represent the dataset. We use two classification algorithms, Random Forest (RF) and Support Vector Machine (SVM), in our work. We use a realistic dataset to test and evaluate the proposed VMMR system. The vehicles’ images in the dataset reflect real-world situations. The proposed VMMR system recognizes vehicles on the basis of make, model, and generation (manufacturing years) while the existing VMMR systems can only identify the make and model. Comparison with existing VMMR research demonstrates superior performance of the proposed system in terms of recognition accuracy and processing speed.