Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of G-CSF on Monocytes and Neurons: In vitro and in vivo studies in a Mouse Model of Alzheimer's Disease

G-CSF has been reported to promote neurogenesis both in vitro and in vivo mouse model of AD. The objective of the present study was to further identify the effect of G-CSF on neural stem/progenitor cell proliferation and neurogenesis in a normal and AD mouse model. Methods: Flow cytometry was used to quantify numbers of BrdU+ and double-labeled (BrdU+/NeuN+) cells in the hippocampi of a wild-type and AD mouse model with and without G-CSF treatment. Brdu+ and DCX+ cells were also counted in the DG of the HC using fluorescence immunohistochemistry in G-CSF or vehicle treated AD and in NT mice. Synaptophysin in CA1 region of HC, amyloid and microglial burden in both HC and EC were determined using biotinylated immunohistochemistry. Results: In normal ICR mice G-CSF significantly increased proliferation of stem/progenitor cells and generation of new neurons in the SGZ of the HC as determined via FACS. Using immunohistochemistry for quantification, DCX+ counts in the SGZ of the HC of APP/PS1 mice treated with G-CSF were increased to NT mouse levels. Synaptophysin density in the CA1 region was significantly increased in both NT and APP/PS1 mice after G-CSF treatment. Amyloid burden (4G8) was significantly decreased while microgliosis (Iba1) was significantly increased in the HC of APP/PS1 G-CSF treated mice. Conclusions: G-CSF has direct effects on
Constraint-based diagram beautification

Recently a new metaphor for diagramming, the intelligent diagram has emerged. This new metaphor provides an excellent basis for diagram beautification since it automatically collects geometric constraints which capture the semantics of a diagram during diagram construction. By applying visual-language-specific layout rules which impose additional desired constraints on the diagram component placement, we can provide powerful semantics preserving diagram beautification. We have demonstrated the feasibility of this approach by developing a simple extension to the Penguins system which generates beautification rules from a grammatical specification of the visual language and tested the system with three example visual languages: Binary trees, state transition diagrams and mathematical equations.
Matching NIR face to VIS face using multi-feature based MSDA

Visual and near infrared (VIS-NIR) face image matching, which is also called cross-spectral face matching in heterogeneous face recognition, is important for security application. However, most existing methods perform poorly in this scenario because of the cross-modality appearance differences. To address this problem, we propose a new method named multi-feature based Multi-view Smooth Discriminant Analysis (MSDA) in this paper. The proposed method involves three kinds of local feature descriptors (i.e., Histogram of Oriented Gradient, HOG; Local Triplet Pattern, LTP; Scale-invariant feature transform, SIFT). In addition, MSDA is formulated for finding a multi-view learning based common discriminative feature space and it can utilize the underlying relationship of features from different modalities. Extensive experiments demonstrate the superiority of the new proposed multi-feature based MSDA approach for VIS-NIR face matching.
The Sustainable Use of Water Resources: A Technical Support for Planning. A Case Study

The paper presents both the structure and application of a Decision Support System (DSS) for an important river in Brazil—along with the sustainable management of its watershed. This DSS assesses both surface-water quality and riverine microhabitats in terms of future scenarios, taking into account regulation limits and appropriate quality indexes. Our future scenarios consider: (a) population and climate change trends; (b) upgrade of sewage systems and wastewater treatment plants; and (c) withdrawal management from rivers and reservoirs. We use some main types of interrelated models, which can simulate different aspects of the responses of a basin, with respect to different modes of use of the water resource. In particular, the surface-water quality models simulate total phosphorus, BOD, dissolved oxygen concentration and thermo-tolerant coliform bacteria pollution. The riverine microhabitat models apply habitat suitability indexes of autochthonous fish species considering water depth, velocity, bottom substrate and dissolved oxygen. Both models are based on hydrologic and hydraulic models results and both were calibrated using discharge and water quality measurements collected over a 1.5-year monitoring period. Our pre- and post-processing are based on common spreadsheets and the output data are spatially analyzed using GIS software. Examples are also shown of how the DSS can contribute to developing a sustainable use of the basin resources, including a reservoir used to supply drinking water to the capital city (Salvador da Bahia).
EFFECTS OF RATIONAL EMOTIVE BEHAVIOIUR THERAPY AND PSYCHOEDUCATION ON SCHIZOPHRENIC PATIENTS

The study examined the effects of rational emotive behavior therapy and psychoeducation among schizophrenic patients. Patients of age range 18 to 59 years with mean age of 34.65 and standard deviation of 11.31were selected from Neuro-psychiatric hospital, Nwafia. One instrument was used for the study: the Brief Psychiatric Rating Scale developed by Overall and Gorham (1962) and validated in Nigeria. The study was an experimental study and repeated measure design was used. Pair wise t-test was employed as the statistical tool for data analyses. The result indicated a significant reduction in psychiatric symptoms in patients treated with REBT compared with the control at (t (19) =10.19, P<. 0001. The second hypothesis which stated that schizophrenic patients who received REBT plus psychoeducation will show significantly lower psychiatric symptoms when compared with the control was confirmed at t (19) =12.11 p <. 0001. The third hypothesis which stated that schizophrenic patients who receive REBT plus psychoeducation will show reduced psychiatric symptoms when compared with those that receive REBT alone was confirmed at t (19) = 7.21 p<. 0001.This reveals that the combination of REBT and psychoeducation yielded better results. This study therefore recommends a combination of rational emotive behavior therapy and psychoeducation in the treatment of psychiatric symptoms among schizophrenic patients.
Designing the handheld maritime communicator

We present the process of designing the first prototype of the Handheld Maritime Communicator: a mobile computer system supporting communication and coordination of safety-critical work activities on large container vessels. Designing the user experience of the Handheld Maritime Communicator was a particular challenge because it targets a highly specialized context of use and because poor design could potentially become a safety hazard. Meeting this challenge, ethnographic field studies on board container vessels were conducted, detailed analyses were carried out, and iterative design was performed. The design produced replaces a large amount of present spoken communication with predefined textual messages on a handheld device. This facilitates persistency, partial automation, and possible integration with other computer-based data. Evaluating the prototype in a high-fidelity ship simulator, prospective users validated the overall design, but also identified a number of usability problems that need to be addressed.
Adaptive Flow Control for Enabling Quality of Service in Tactical Ad Hoc Wireless Networks

Abstract : Wireless networks for emergency responders and military personnel operating in tactical situations are often assembled without any preexisting infrastructure (i.e., ad hoc) and are subject to changing topology as nodes enter or leave service or move (i.e., are mobile) in the environment. These networks often have lower-than-optimal bandwidth and can see further bandwidth reductions due to disadvantageous topologies and other factors. In addition, needed applications must compete for possibly diminishing bandwidth. As a result, such networks are frequently oversubscribed: they cannot fully meet the quality of service (QoS) expectations of all applications. This report provides an overview of approaches for satisfying QoS expectations in ad hoc wireless networks assembled to support high criticality crisis and tactical scenarios. It illustrates that these approaches are adaptations of approaches used in wired (often fixed) infrastructures where bandwidth is known and interference is not the norm. It documents and provides experimental evidence for the Adaptive QoS (AQoS) approach that allows applications to adapt bandwidth demand to conditions without the need to know, estimate, or predict available bandwidth. AQoS informs applications that oversubscription is occurring, thereby allowing them to continue to operate, albeit at diminished rate or capacity, and meet mission needs.
Learning in Liminality: a hermeneutic phenomenological investigation of student nurse learning during a study abroad journey

Study abroad generates positive learning outcomes for students. However, experiences of learning, and processes, strategies and influences on learning during unaccompanied nursing study abroad are unclear. This hermeneutic phenomenological study therefore investigated student nurse experiences of learning during a study abroad journey in order to explore the phenomenon of learning and the processes, strategies and influences on learning throughout this journey. Twenty student nurses, from the UK and Europe, participated; two semi-structured interviews were conducted per participant (post-return and follow-up). Phenomenological hermeneutical data analysis revealed the phenomenon of learning comprised four themes: ‘experiencing a different reality’; ‘active sense-making’; ‘being with others’ and ‘being changed and transformed’. Findings identify that study abroad was experienced as the liminal space in which learning occurred. Students experienced liminality in this space and the process of learning was triggered by disjuncture. Students took responsibility for learning and undertook active sense-making activities to gain insight. Students struggled to make sense of troublesome experiences, and remained in a stuck place until resolution of troublesome-ness enabled students to cross a threshold into understanding. Threshold concepts in nursing were revealed as particularly troublesome. Learning was influenced by others; this included communitas, communities and communities of practice. Otherness also influenced student learning and position in these communities. Students experienced change and transformation as a result of the learning that had occurred. A postliminal state was attained when troublesome-ness was resolved and students had re-integrated back into their usual reality. These findings offer new practical and theoretical insight into student nurse learning during unaccompanied study abroad journeys and further development of educational policy, practice and research is recommended.
Notice of Violation of IEEE Publication PrinciplesA Formal Framework for Security Policy Specification and Implementation

In information systems, security policies are used to specify various security requirements, and the guarantee of these requirements can be obtained by implementing the security policies efficiently and consistently. Therefore, specification and implemen-tation of security policies are of great importance to information system security. In this paper, we propose a formal security policy framework, allowing to specify diverse security policies, together with a description of implementation of security policies, which can enhance the efficiency and security of the information system. As an example, we show how the proposed model can be used to specify and implement the Bell and LaPadula policies.
On randomly interleaved memories

The authors analyze and identify a basic deficiency of a class of random interleaving schemes (LINEAR), which use linear transformation techniques to achieve randomization. Since all bank addresses generated by these methods are random, constrained only by the bijective property, more conflicts tend to occur than in the more common MODULO method. Also LINEAR lacks the capability of MODULO to move several conflicting vector streams to a conflict-free steady state. To correct these deficiencies, a new class of random interleaving schemes called RANDOM-H that hash only the higher-order address bits is proposed. Unlike LINEAR, the RANDOM-H schemes randomize selectively, while retaining some of the advantages of MODULO. It is shown that RANDOM-H has a higher probability of accessing a vector without conflict than LINEAR. An an example of RANDOM-H, a method called MASH is presented that combines module interleaving with a multiplicative hashing function for randomization. <<ETX>>
Indeterminacy and sunspot fluctuations in two-sector RBC models: theory and calibration

We analyze sunspot-driven fluctuations in the standard 2-sector RBC model with moderate increasing returns to scale. We provide a detailed theoretical analysis enabling us to derive relevant bifurcation loci and to characterize the steady-state local stability properties as a function of various structural parameters. With GHH preferences, we show that local indeterminacy occurs through flip and Hopf bifurcations for a large set of values of the elasticity of intertemporal substitution in consumption if the labor supply is sufficiently inelastic. With additively-separable preferences, we prove that local indeterminacy occurs through flip and Hopf bifurcations for any value of the elasticity of the labor supply, and can even be compatible with an arbitrarily low elasticity of intertemporal substitution in consumption. Finally, we provide a detailed quantitative analysis of the model. Computing, on a quarterly basis, a new set of empirical moments related to two broadly defined consumption and investment sectors, we are able to identify, among the set of admissible calibrations consistent with sunspot equilibria, the ones that provide the best fit of the data. The model properly calibrated solves several empirical puzzles traditionally associated with 2-sector RBC models.
Stress, Employment and Academic Performance: A Study Exploring the Effects of Perceived Stress and Employment on a Third Level Student’s Academic Performance

Background: The level of employment among students today is increasing along with the amount of stressors they have to face which can have a large impact on their academic performance. This study aims to investigate the effects of perceived stress, employment, personality type and age on a third level student’s academic performance. Method: A convenience sample of 72 students from the National College of Ireland was used. A questionnaire was distributed online and in paper format containing demographic questions, employment questions, the perceived stress scale, a subscale of the PASCI (Personal and Academic Self Concept Inventory), and the measurement of pattern A behaviour. Results: There was negative correlations found between academic performance and stress and, academic performance and personality type. Further correlations between variables are discussed. Stress, personality type and age were found to be significant predictors of academic performance. Conclusion: Findings from this study suggest that stress and personality type can have a negative effect on academic performance whereas age can have a positive effect on academic performance.
Location-Based Beamforming for Enhancing Secrecy in Rician Wiretap Channels

We propose a new optimal location-based beamforming (LBB) scheme for the wiretap channel, where both the main channel and the eavesdropper's channel are subject to Rician fading. In our LBB scheme, the two key inputs are the location of the legitimate receiver and the location of the potential eavesdropper. Notably, our scheme does not require any channel state information of the main channel or the eavesdropper's channel being available at the transmitter. This makes our scheme easy to deploy in a host of application settings in which the location inputs are known. Our beamforming solution assumes a multiple-antenna transmitter and a multiple-antenna eavesdropper, and its aim is to maximize the physical layer security of the channel. To obtain our solution, we first derive the secrecy outage probability of the LBB scheme in an easy-to-evaluate expression that is valid for arbitrary real values of the Rician K-factors of the main channel and the eavesdropper's channel. Using this expression, we then determine the location-based beamformer solution that minimizes the secrecy outage probability. To assess the usefulness of our new scheme, and to quantify the value of the location information to physical layer security, we compare our scheme to other schemes, some of which do not utilize any location information. Our new beamformer solution provides optimal physical layer security for a wide range of location-based applications.
Design of an Integrated Role-Based Access Control Infrastructure for Adaptive Workflow Systems

With increasing numbers of organizations automating their business processes by using workflow systems, security aspects of workflow systems has become a heavily researched area. Also, most workflow processes nowadays need to be adaptive, i.e., constantly changing, to meet changing business conditions. However, little attention has been paid to integrating Security and Adaptive Workflow. In this paper, we investigate this important research topic, with emphasis on Role Based Access Control (RBAC) in Adaptive Workflow. Based on our earlier work on a 3-tier adaptive workflow architecture, we present the design of a similar 3-tier RBAC infrastructure, and we show that it conceptually mirrors our adaptive workflow architecture. We also describe the mappings between them, and we show how this mapping can be used to manage organizational RBAC constraints when the workflows are being adapted continuously. We illustrate our ideas throughout the paper with a simple yet non-trivial example.
An instruction-scheduling-aware data partitioning technique for coarse-grained reconfigurable architectures

In this paper, we propose a data partitioning technique for the memory subsystem that consists of a multi-ported scratchpad memory (SPM) unit and a single-ported data cache in coarse-grained reconfigurable arrays (CGRA) architecture. The embedded reconfigurable processor executes programs by switching between the Non-VLIW and VLIW modes depending on the type of the code region to achieve high performance. The VLIW mode exploits code regions with high ILP that require high memory bandwidth and the Non-VLIW mode exploits those with low ILP that require low memory latency. Our data partitioning technique between the SPM and the data cache is based on data interference graph reduction and profiling information. Given an SPM size, it finds the optimal data partitions by taking the VLIW instruction schedule into consideration. We evaluate our data partitioning technique for the CGRA architecture with three representative multimedia applications.
A New Record of Candida kashinagacola (Synonym Ambrosiozyma kashinagacola) from Galleries of Platypus koryoensis, the Oak Wilt Disease Vector, in Korea

Abstract The ambrosia beetle, Platypus koryoensis, is an economically important pest affecting oak trees in Korea. Candida kashinagacola was isolated from galleries of the beetle in oak wood and identified by analyses of morphology, physiological properties, and nucleotide sequence of the large subunit ribosomal DNA. This is the first report on Candida species associated with oak wilt disease vectored by the ambrosia beetle, Platypus koryoensis, in Korea.
GPSA: A Graph Processing System with Actors

Due to the increasing need to process the fast growing graph-structured data (e.g. Social networks and Web graphs), designing high performance graph processing systems becomes one of the most urgent problems facing systems researchers. In this paper, we introduce GPSA, a single-machine graph processing system based on an actor computation model inspired by the Bulk Synchronous Parallel(BSP) computation model. GPSA takes advantage of actors to improve the concurrency on a single machine with limited resource. GPSA improves the conventional BSP computation model to fit in the actor programming paradigm by decoupling the message dispatching from the computation. Furthermore, we exploit memory mapping to avoid explicit data management to improve I/O performance. Experimental evaluation shows that our system outperforms existing systems by 2x-6x in processing large-scale graphs on a single system.
Worker Absence and Productivity: Evidence from Teaching

A significant amount of work time is lost each year due to worker absence, but evidence on the productivity losses from absenteeism remains scant due to difficulties with identification. We use uniquely detailed data on the timing, duration, and cause of absences among teachers to address many of the potential biases from the endogeneity of worker absence. Our analysis indicates that worker absences have large negative impacts: the expected loss in daily productivity from employing a temporary substitute is on par with replacing a regular worker of average productivity with one at the 10th–20th percentile of productivity.
Comparison of near-singularity cancellation quadrature schemes for curvilinear triangle domains

In the method of moments (MoM) a routine requirement is the integration of near-singular kernels over triangle domains. Increasingly, higher-order basis functions and curvilinear mesh elements are used. Near-singularity cancellation quadrature is an attractive approach for evaluating such integrals. This paper investigates the effect of curvi-linearity upon the accuracy of these quadrature schemes. Comparative results for flat and curvilinear domains with different orders of weighting functions are presented. The kernels 1/R and grad(1/R) are considered. It is found that switching to a curved domain has a similar effect as including a higher-order weighting function. Conclusions regarding the most efficient schemes are also drawn.
Two pattern classifiers for interval data based on binary regression models

This paper introduces two classifiers for interval symbolic data based on logit and probit regression models, respectively. Each example of the learning set is described by a feature vector, for which each feature value is an interval and a binary response that defines the class of this example. For each classifier two versions are considered. First fits a classic binary regression model conjointly on the lower and upper bounds of the interval values assumed by the variables in the learning set. Second fits a classic binary regression model separately on the lower and upper bounds of the intervals. The prediction of the class for new examples is accomplished from the computation of the posterior probabilities of the classes. To show the usefulness of this method, examples with synthetic symbolic data sets with overlapping classes are considered.
An Introduction to Variational Methods forGraphical

This paper presents a tutorial introduction to the use of variational methods for inference and learning in graphical models (Bayesian networks and Markov random elds). We present a number of examples of graphical models, including the QMR-DT database, the sigmoid belief network, the Boltzmann machine, and several variants of hidden Markov models, in which it is infeasible to run exact inference algorithms. We then introduce variational methods, which exploit laws of large numbers to transform the original graphical model into a simpliied graphical model in which inference is eecient. Inference in the simpiied model provides bounds on probabilities of interest in the original model. We describe a general framework for generating variational transformations based on convex duality. Finally we return to the examples and demonstrate how variational algorithms can be formulated in each case.