Miracle-dz/UniFAR-FTUs huggingface dataset:
Charting the course of renal cryoinjury

We sought to characterize a minor renal cryoinjury that allows investigation into renal damage processes and subsequent endogenous repair mechanisms. To achieve this, we induced a small cryoinjury to mice, in which the transient superficial application of a liquid nitrogen‐cooled cryoprobe to the exposed kidney induces a localized lesion that did not impair renal function. The resulting cryoinjury was examined by immunohistochemistry and Laser‐Doppler flowmetry. Within hours of cryoinjury induction, tubular and vascular necrotic damage was observed, while blood flow in the directly injured area was reduced by 65%. The injured area demonstrated a peak in tubular and perivascular cell proliferation at 4 days postinjury, while apoptosis and fibrosis peaked at day 7. Infiltration of macrophages into the injury was first observed at day 4, and peaked at day 7. Vascular density in the direct injured area was lowest at day 7. As compared to the direct injured area, the (peripheral) penumbral region surrounding the directly injured area demonstrated enhanced cellular proliferation (2.5–6‐fold greater), vascular density (1.6–2.9 fold greater) and blood perfusion (twofold greater). After 4 weeks, the area of damage was reduced by 73%, fibrosis decreased by 50% and blood flow in the direct injured area was reestablished by 63% with almost complete perfusion restoration in the injury's penumbral region. In conclusion, kidney cryoinjury provides a flexible facile model for the study of renal damage and associated endogenous repair processes.
Customers Perceived Quality and Satisfaction of Self Service Technology-Automated Teller Machine in Ghana

Introduction Over the last four decades, Automated Teller Machine (ATM) has emerged as a major channel for routing banking services to customers. Al-Hawari et al., (2006) argue that firms would reap benefits such as cost savings, efficiency, greater consumer involvement, customer satisfaction and loyalty and improved financial performance if they provide quality electronic banking channels. Pantouvakis (2010) asserts that the measurement of SQ is a major issue facing service firms and as a result, research into how customers perceive and evaluate the quality of these electronic portals is still ongoing (Parasuraman et al., 2005; Loonam & O’Loughlin, 2008; Chong et al., 2010). As different technologies might influence customer’s perception of service quality (SQ) in different ways, Joseph et al., (1999) and Curran & Meuter, (2005) postulate that consumer perceptions of SQ vary depending on the type of self service used and called for studies investigating SQ based on the different technologies. In response to this, most scholars have focused on the dimensions of internet banking quality (Loonam & O’Loughlin, 2008; Ho and Lin, 2010; Chong et al., 2010), but there is almost no comprehensive conceptualization of ATM SQ, prompting Khan (2010) to call for further studies on the dimensions of ATM SQ. It has also been proposed that customer perceived satisfaction is an essential determinant of success in the technology based delivery channels (Tong, 2009). Few studies have investigated the relative importance of ATM SQ dimensions in predicting customer satisfaction and therefore, this current study attempts to fill these research gaps. The objectives of this study are to: (i) determine the dimensions of perceived ATMs SQ and (ii) evaluate the relative importance of these dimensions in predicting customer satisfaction. The introduction section is followed by contextual background information and the conceptual framework. The methodology is then presented, followed by analysis of findings, conclusion and discussions.
A Pictorial Operator Formalism for NMR Coherence Phenomena

An NMR pulse experiment can often be more easily understood if it is described in a pictorial manner. In classical models spins are visualized as vectors, rotated by an alternating magnetic field during r.f. pulses, and between pulses, precessing at frequencies corresponding to each spin's local magnetic field. There are however many important phenomena such as multiquantum coherence, coherence transfer, dipolar order, and solid echoes, which are more difficut to describe using classical models (1,2). In this paper we describe an operator formalism which we have found useful both to show how different pulse sequences work, and to bring out how they are related to one another. The method was developed in the thesis of one of us (PKW) in the course of our work on adsorbed molecules on metal surfaces (3). When we considered publication, we discovered that in the meanwhile a substantial article by Sorensen et al appeared, which gave a complete and general treatment of the method (4a). They have called the method "Product Operator Formalism". In addition, a clear discussion of the formal method for two spins by Van der Ven and Hilbers (4b) has also appeared which represents a very systematic approach and treats as an example the 2D correlated experiment for two like nuclei coupled to each other, but with a chemical shift difference. Though both papers provide a clear, mathematically precise treatment of the topic, we decided that some readers might still find useful a short article, tutorial in nature, aimed at highlighting the similarities and the differences between the several coherence phenomena. By treating a very simple system of two spin-l/2 nuclei, we hope to show the relationship among a
Principal Component Analysis of fatigue strength

In this paper authors examine the possibility of using modeling technique based on Principal Component Analysis (PCA) on fatigue strength modeling of selected specimens of steel. The PCA technique will be used for data analysis and model development with goal of identification of variables with most influence on fatigue strength. The model is trained upon data available in literature and application of described model is tested on series of laboratory experiments.
Redefining the Digital Divide in the 'Smart State'

This paper will present a research project that explores the psychological factors that prevent people within community from integrating information and communication technology (ICT) into their lives. The research will use Bandura's social cognitive theory to examine the psychology of the digital divide. Participants in the study are members of the Brisbane community. Self administered surveys are used for data collection. The research has both theoretical and practical significance. It establishes a way of thinking about and understanding digital inequality in community that goes beyond just simple physical access to ICT. The research provides evidence that the characteristics or make up of the digital divide is more complex than the current socio-economic understanding of the phenomenon. The research illustrates that psychology does matter, and that the digital divide involves both more members of the population and different members of the population then current research has shown to date. The digital divide is not about computers, modems, the internet and hardware. It is about people. As such the key to solving the issue of digital inequality is not going to be found with corporate or government funds providing physical access to technology. Instead, the key to solving digital inequality is inside the individual person.
Memory-Based Approximation of the Gaussian Mixture Model Framework for Bandwidth Extension of Narrowband Speech

In this paper, we extend our previous work on exploiting speech temporal properties to improve Bandwidth Extension (BWE) of narrowband speech using Gaussian Mixture Models (GMMs). By quantifying temporal properties through information theoretic measures and using delta features, we have shown that narrowband memory significantly increases certainty about highband parameters. However, as delta features are non-invertible, they can not be directly used to reconstruct highband frequency content. In the work presented herein, we embed temporal properties indirectly into the GMM structure through a memorydependent tree-based approach to extend representation of the narrow band. In particular, sequences of past frames are progressively used to grow the GMM in a tree-like fashion. This growth approach results in reliable estimates for the GMM parameters such that Maximum Likelihood estimation is no longer necessary, thus circumventing the complexity accompanying high-dimensionality GMM training.
A Time and Memory Efficient Implementation of the Nano-Threads Programming Model

As more means to exploit parallelism are incorporated into modern processors and more programmers are exposed to them, thread-based parallel programming models gain popularity. However, this increasing interest poses new challenges to those models. They are required to efficiently support a growing range of parallelization methods on diverge systems, with an ever increasing number of threads. Under these circumstances, mindful usage of all resources of a system, but especially memory, becomes a necessity. The nano-threads programming model has been proposed to effectively support applications with a varying degree of parallelism. However, NthLib, a run-time library that implements the nano-threads programming model, currently requires excessive portions of memory to represent parallelism, which makes it inadequate for applications that require a considerable number of threads. We propose a new implementation, which allows exploitation of lazy techniques and avoids excessive accesses to queues. Moreover, it allows to accurately predict the number of stacks that an application requires and pre-allocate them. Our results indicate that the new implementation not only saves up to 98,44% of memory to represent parallelism, but also proves to be up to 21,82% faster than the original implementation.
Wideband high-gain multi-layer patch antenna-coupler with metamaterial superstrate for X-band applications

A wide bandwidth, high-gain and high directivity multi-layer patch antenna integrated with coupler and covered with metamaterial superstrate is proposed for frequency range of 10.8 to 12 GHz. The novel high level of integration of three different functions in one configuration is done in a straightforward design. It consists of a 50 ohm microstrip line coupled directly to the non-radiating edge of a patch antenna. This structure is covered by two layers of near zero refractive index metamaterial. The prototype of this configuration shows a flat coupling factor of 25 dB and a high isolation factor of 33 dB. The two layers of metamaterial superstrate enhanced the performance of the patch antenna-coupler. At the center frequency of 11.4 GHz, the gain of the patch antenna-coupler with metamaterial superstrate is improved by 8 dB to 13.4 dB and the return loss bandwidth is improved to more than 10%. Furthermore, the 3-dB beamwidth of the antenna is reduced by more than 70° to 30°.
Reversible Information Embedding in Multi-User Channels ∗

Information embedding is the reliable transmission of information embedded into a host signal under some prescribed distortion constraint. We consider distributed reversible information embedding (RIE) in which each user embeds its message into its host signal independently under some distortion constraint, all these embedded signals are transmitted to a single decoder across a multiple access channel (MAC), and messages along with host signals from all users are decoded reliably. Our general distributed RIE model considers scenarios in which the MAC output potentially depends on both the embedded signals and the host signals. We state and prove the distributed RIE capacity region and discuss various special cases of the model and result. We used a distortion-constrained superposition coding to achieve the distributed RIE capacity region, suggesting that Gel’fand and Pinsker coding is not required when the host sequences are known non-causally at the encoders and lossless reconstruction of the host sequences is considered at the decoder. We also state the RIE capacity region of degraded broadcast channels and the RIE capacity of degraded relay channels.
Output Impedance Mismatch Effects on the Linearity Performance of Digitally Predistorted Power Amplifiers

This paper analyzes the effects of load impedance mismatch in power amplifiers which linearity has been enhanced using various digital predistortion (DPD) algorithms. Two different power amplifier architectures are considered: a class AB and a Doherty amplifier and three model structures for the DPD model are compared: memoryless polynomial (MLP), general memory polynomial (GMP) and Kautz-Volterra functions (KV). This paper provides a sensitivity analysis of the linearized amplifiers under load mismatch conditions and reports the performance when dynamic parameter identification for the DPD is used to compensate for the changes in the load impedance. In general, power amplifiers linearity is sensitive to load impedance mismatch. Linearity may degrade as much as 10 dB (in normalized mean square error) according to the magnitude and the phase of the reflection coefficient provided by the load impedance. However, depending on the amplifier design, the sensitivity to load impedance mismatch varies. While the Doherty amplifier studied show significant linearity degradations in the in-band and out-of-band distortions, the out-of-band distortions of the studied class AB were less sensitive to the load impedance mismatch. In adaptive DPD schemes, the performance obtained in the MLP model does not benefit from the updating scheme and the performance achieved is similar to a static case, where no updates are made. This stresses the memory requirements in the predistorter. When employing the GMP and the KV models in an adaptive DPD scheme, they tackle to a larger extent the linearity degradations due to load impedance mismatch.
RBESP: Reliable and best effort stack protocol for UAV collaboration with WSN

This paper describes RBESP, a dual stack protocol designed as part of the communication infrastructure of a short-range Unmanned Aerial Vehicle (UAV). It aims at providing a reliable communication between the UAV and its base station and a best effort communication between the UAV and a WSN. RBESP targets two distinct communication requirements using the same communication transceiver. The other end of the communication link can be heterogeneous devices transmitting with the IEEE 802.15. 4 standard, which is also used in the UAV transceiver. The paper details the software layers that implement both the reliable communication with the base station and the best-effort communication with the WSN nodes. Two different scenarios were implemented in order to allow RBESP evaluation. The first scenario consists of the UAV node communicating with spatially distributed sensors on the ground. In the second scenario, the UAV node delivers the collected data to the base station. Both communication scenarios are very different in terms of connection time and volume of transmitted data. Obtained results are presented and discussed along the paper.
Artificial Intelligence (AI) Techniques Applied for the Development of a Clinical Decision Support System (CDSS) for Diagnosing Ischemic Heart Disease (IHD)

Heart Disease (IHD) is difficult to diagnose since most of the symptoms and clinical presentations are similar to other diseases. It is a very common, harmful disease, which is identified mostly during the mortality of an individual. The objective is to build a clinical decision support system, which will diagnose the presence of IHD with an integrated automated classifier using Artificial Intelligence (AI) techniques. A retrospective data set that included 800 clinical cases was taken for the work. A total of 88 sets were discarded during pre-processing. Tests were run on 712 cases using the Weka classifiers available in Weka 3.7. 0. Out of 113 classifiers, 16 were identified to be the best based on the following parameters: sensitivity, specificity, accuracy, F- measure, kappa statistic, correctly classified cases, time taken to run the model, and the Receiver Operating Characteristic (ROC) curve. The diagnoses made by the Clinical Decision Support System (CDSS) were compared with those made by physicians during patient consultations. The KSTAR algorithm showed the best diagnoses with the highest accuracy 97.32%, sensitivity 98%, specificity 97% kappa 0.95, and ROC 0.995. The authors thus conclude that a CDSS can be developed to assist expert physicians in separating the positive and the negative cases of heart disease.
Visual tracking of an end-effector by adaptive kinematic prediction

Presents results of a model-based approach to visual tracking and pose estimation for a moving polyhedral tool in position-based visual servoing. This enables the control of a robot in look-and-move mode to achieve six degree of freedom goal configurations. Robust solutions of the correspondence problem-known as "matching" in the static case and "tracking" in the dynamic one-are crucial to the feasibility of such an approach in real-world environments. The object's motion along an arbitrary trajectory in space is tracked using visual pose estimates through consecutive images. Subsequent positions are predicted from robot joint angle measurements. To deal with inaccurate models and to relax calibration requirements, adaptive online calibration of the kinematic chain is proposed. The kinematic predictions enable unambiguous feature matching by a pessimistic algorithm. The performance of the suggested algorithms and the robustness of the proposed system are evaluated on real image sequences of a moving gripper. The results fulfill the requirements of visual servoing, and the computational demands are sufficiently low to allow for real-time implementation.
Generation of isospectral graphs

We discuss a discrete version of Sunada's Theorem on isospectral manifolds, which allows the generation of isospectral simple graphs, i.e., nonisomorphic simple graphs that have the same Laplace spectrum. We also consider additional boundary conditions and Buser's transplantation technique applied to a discrete situation. © John Wiley & Sons, Inc. J Graph Theory 31: 255–265, 1999
Why ℓp-methods in signal and image processing: A fuzzy-based explanation

In signal and image processing, it is often beneficial to use semi-heuristic ℓ<inf>p</inf>-methods, i.e., methods that minimize the sum of the p-th powers of the discrepancies. In this paper, we show that a fuzzy-based analysis of the corresponding intuitive idea leads exactly to the ℓ<inf>p</inf>-methods.
Unobserved heterogeneity in stochastic cost frontier models : a comparative analysis

A COMPARATIVE ANALYSIS * * The authors are grateful to the Ticino's Dipartimento Sanità e Socialità for providing the data and their general support. We would also like to thank William Greene and Luca Crivelli for helpful comments and discussions, Ilaria Mosca and Chiara Gulfi for their excellent assistance and Giorgio Borradori for his help in understanding the data. We also benefited from helpful comments of the participants of the 8 th European Workshop on Efficiency and Productivity Analysis (Ovideo, 2003). The views expressed in this paper are strictly personal. Responsibility for all remaining errors lies solely with the authors. ABSTRACT This paper studies a number of stochastic cost frontier models comparing their ability to distinguish unobserved heterogeneity from inefficiency variation among firms. The main focus is on the panel data models that incorporate firm-specific effects in a stochastic frontier framework, as proposed by Greene (2002, 2004). In cases where the unobserved heterogeneity is correlated with some of the explanatory variables, while the random effects estimators can be biased the fixed effects model may overestimate inefficiency scores. In line with Mundlak (1978), a simple method is proposed to include such correlations in random effects specification. The models are applied to a panel of 36 Swiss nursing homes operating from 1993 to 2001. The estimation results are compared and the resulted improvements are discussed. The results suggest that the proposed specification can avoid the inconsistency problem while keeping the inefficiency estimates unaffected.
215GHz CMOS signal source based on a Maximum Gain Ring Oscillator topology

This paper introduces a Maximum Gain Ring Oscillator (MGRO) topology that maximizes the power gain achieved by the active devices using appropriately designed passive matching networks to maximize the frequency of oscillation. A design methodology is provided along with guidelines for the design of the passive matching network. In the absence of passive losses, the topology can oscillate at the fmax of the active devices. In the presence of passive loss, the losses can be taken into account in a closed-form fashion to maximize oscillation frequency. Based on this topology, an oscillator operating at approximately 107.5GHz is implemented using the 56-nm body-contacted devices of IBM's 45nm SOI CMOS technology (fmax is about 200GHz). The second harmonic of this oscillation is extracted using a load-pull-optimized, extraction network. This topology can be generalized for the extraction of any harmonic from MGROs with different number of stages. The oscillator generates −14.4dBm of power at 216.2GHz while drawing 57.5mW of DC power. The modeling of 45nm SOI devices for millimeter-wave design is also described.
Investigating Predictive Role of 2x2 Achievement Goal Orientations on Learning Strategies with Structural Equation Modeling.

The purpose of this study is to examine the relationships between achievement goal orientations and Learning Strategies. The sample of study consists of 350 public high school students (135 males and 215 females, mean age: 17± 0.65) from two high schools in Kerman province of Iran selected by random multistage cluster sampling method. In this study, The Achievement Goal Orientations Scale (Elliot & McGregor, 2001) and Learning Strategies Scale (Kember, Biggs, & Leung, 2004) were used. Structural equation modeling (SEM) was used to test the hypotheses. In correlation analysis, mastery goals predicted positive deep strategy and performance goals predicted positive surface strategy in a positive way. The model demonstrated fit (χ2/df= 1.99, GFI= .97, AGFI= .97, CFI= .93, NFI= .93, RFI= .93, and RMSEA= .05). According to the results, achievement goal orientations (exception of the path from performance-approach to deep strategy) were significant determinants of learning strategies. Results were discussed in the light of literature.