Miracle-dz/UniFAR-FTUs huggingface dataset:
In dogs undergoing elective procedures is medetomidine superior to acepromazine when used as a premedication?

PICO question In dogs undergoing elective procedures does the use of medetomidine during premedication result in an increase in anaesthetic complication rates, when compared to acepromazine? Clinical bottom line Category of research question Treatment The number and type of study designs reviewed Four papers were critically reviewed, all of which were randomised controlled trials Strength of evidence Strong Outcomes reported There were some statistically significant differences between using medetomidine and acepromazine as premedications in the outcomes measured, but as the clinical parameters including blood pressure were still within acceptable clinical limits, the clinical benefits of these findings remain undetermined. There is also evidence to suggest that patients premedicated with medetomidine have less of a perioperative stress response than those receiving acepromazine, but in addition may have increased risk of cardiac conduction disturbances, but the clinical importance of these findings is also unknown Conclusion The overall findings showed that either drug can be used as a suitable premedication, but the differences in pain score postoperatively shown in one small study mean that due to its poor analgesic properties it is recommended when using acepromazine instead of medetomidine, that additional analgesia should be given to reduce postoperative pain for better animal welfare How to apply this evidence in practice The application of evidence into practice should take into account multiple factors, not limited to: individual clinical expertise, patient’s circumstances and owners’ values, country, location or clinic where you work, the individual case in front of you, the availability of therapies and resources. Knowledge Summaries are a resource to help reinforce or inform decision making. They do not override the responsibility or judgement of the practitioner to do what is best for the animal in their care.
Mean-Square Approximation of Navier-Stokes Equations with Additive Noise in Vorticity-Velocity Formulation

We consider a time discretization of incompressible Navier-Stokes equations with spatial periodic boundary conditions and additive noise in the vorticity-velocity formulation. The approximation is based on freezing the velocity on time subintervals resulting in a linear stochastic parabolic equation for vorticity. At each time step, the velocity is expressed via vorticity using a formula corresponding to the Biot-Savart-type law. We prove the ﬁrst mean-square convergence order of the vorticity approximation.
Moderating role of top management support in electronic procurement usage of Jordanian firms

Article history: Received: August 14, 2020 Received in revised format: November 14 2020 Accepted: November 14, 2020 Available online: November 23, 2020 The use of e-procurement aids organisations in reducing business costs, broadening their market access and simplifying purchasing processes. However, in Jordan, only 27.6% of firms utilise e-procurement systems. Hence, the usage of e-procurement systems by Jordanian firms is still in its infancy. In this work, the technology, organisation and environment (TOE) factors affecting the use of e-procurement systems by large firms in Jordan were investigated. Previous studies have reported inconsistent findings with regard to the antecedent factors that may affect e-procurement usage. Therefore, this work aimed to determine the factors related to e-procurement usage and whether or not top management support moderates the relationship between TOE factors and e-procurement usage. Results revealed that all TOE factors used in this study influenced the e-procurement usage of the firms. Moreover, the moderating role of top management support was found to be positively related to relative advantages and organisational readiness and negatively related to complexity. © 2021 by the authors; licensee Growing Science, Canada
Nanofluidics: Molecularly thin lubricant layers under confinement

Confined liquid films with a thickness in the range of a few molecular diameters exhibit different mechanical properties than in the bulk. With the technique of a 2-dimensional (2D) imaging surface forces apparatus (SFA) we investigated in detail the layer by layer thinning of a thin liquid film confined between two atomically smooth surfaces upon pressing them towards each other with increasing load. The dynamics of a series of subsequent squeeze-out processes of individual layers were analyzed. Using a simple hydrodynamic model, we extracted the thickness-dependence of the viscosity. For the system investigated here—the model lubricant Octamethylcyclotetrasiloxane (OMCTS) confined between ultraclean, recleaved mica surfaces—we found that the viscosity increased by a factor of 10 with decreasing the film thickness from 6 to 2 layers. We decomposed the friction into two components, one describing the sliding of liquid layers on top of the substrates, and the other describing liquid-on-liquid sliding. The latter contribution was found to agree closely with expectations based on the bulk viscosity, whereas the former was approximately 35 times higher for the present system.
Handbook of Research on Islamic Social Finance and Economic Recovery After a Global Health Crisis

Social financial reporting as an economic tool presents the firm as a socio-economic unit with empowered social capital to enable a sustainable economic solution, particularly in response to the COVID-19 pandemic. Islamic social finance (ISF) is a corporate social responsibility initiative in the form of humanitarian and socio-development programs by Islamic financial institutions and Shariah-compliant corporations. ISF is applied through various methods and tools that structure based on Islamic Sharia Law. For example, Islamic social finance tools would either be philanthropic, involving activities such as zakat (obligatory alms-giving), Sadaqah (voluntary alms-giving/charity), and waqf (endowment) or ta’awun (cooperation-based activities), which include Qardh al-hasan (benevolent loan) and kafala (guarantee). Thus, Islamic social finance instruments play a vital role in alleviating poverty and addressing socio-economic issues such as illiteracy, unemployment, malnutrition, and health issues. As such, integrated ISF reporting can empower sustainable economic development and lead to recovery. The Handbook of Research on Islamic Social Finance and Economic Recovery After a Global Health Crisis provides insights on the role of Islamic social finance in supporting and facilitating economic recovery in the post-COVID-19 era as well as reducing poverty and addressing the challenges of socio-economic problems such as education, unemployment, malnutrition, and health issues. This book is ideally intended for practitioners, stakeholders, researchers, academicians, and students who are interested in improving their understanding on the role of Islamic social finance theoretically and empirically in solving the issue of poverty and developing excellent funds management to achieve economic empowerment with better environmental sustainability.
Bidirectional gated recurrent unit for improving classification in credit card fraud detection

In recent years, the use of credit cards around the world has grown enormously. Thus, the number of fraud cases have also increased, resulting in losses of thousands of dollars worldwide. Therefore, it is mandatory to use techniques that are able to assist in the detection of credit card fraud. For this purpose, we have proposed a multi-level architecture, composed of four levels: authentication level, behavioral level, smart level and background processing level. In this paper, we focus on the implementation of the smart level. The aim of this level is to develop a classifier for the detection of credit card fraud, using bidirectional gated recurrent units (BGRU). The experiments, applied on well-known credit card fraud dataset from Kaggle, show that this model has peak performance compared to other proposed models, with 97.16% for accuracy rate and 99.66% for the area under the ROC curve.
Analysis of full microwave propagation and backpropagation for a complex asteroid analogue via single-point quasi-monostatic data

Context. Information carried by the full wave field is particularly important in applications involving wave propagation, backpropagation, and a sparse distribution of measurement points, such as in tomographic imaging of a small Solar System body. Aims. With this study, our aim is to support the future mission and experiment design, such as for example ESA’s Hera, by providing a complete mathematical and computational framework for the analysis of structural full-wave radar data obtained for an asteroid analogue model. We analyse the direct propagation and backpropagation of microwaves within a 3D printed analogue in order to distinguish its internal relative permittivity structure. Methods. We simulate the full-wave interaction between an electromagnetic field and a three-dimensional scattering target with an arbitrary shape and structure. We apply the Born approximation and its backprojection (the adjoint operation) to evaluate and backpropagate the wave interaction at a given point within the target body. As the data modality can have a significant effect on the distinguishability of the internal details, we examine the demodulated wave and the wave amplitude as two alternative data modalities and perform full-wave simulations in frequency and time domain. Results. The results obtained for a single-point quasi-monostatic measurement configuration show the effect of the direct and higher-order scattering phenomena on both the demodulated and amplitude data. The internal mantle and void of the analogue were found to be detectable based on backpropagated radar fields from this single spatial point, both in the time domain and in the frequency domain approaches, with minor differences due to the applied signal modality. Conclusions. Our present findings reveal that it is feasible to observe and reconstruct the internal structure of an asteroid via scarce experimental data, and open up new possibilities for the development of advanced space radar applications such as tomography.
Using the multi-bit feature of memristors for register files in signed-digit arithmetic units

One of the outstanding features of memristors is their principle possibility to store more than one binary value in a single memory cell. Due to their further benefits of non-volatility, fast access times, low energy consumption, compactness and compatibility with CMOS logic, memristors are excellent devices for storing register values nearby arithmetic units. In particular, the capability to store multi-bit values allows one to realise procedures for high-speed arithmetic circuits, which are not based on usual binary but on ternary values. Arithmetic units based on three-state number representation allow carrying out an addition in two steps, i.e., in O ( 1 ) ? > , independent of the operands word length n ? > . They have been well-known in literature for a long time but have not been brought into practice because of the lack of appropriate devices to store more than two states in one elementary register or main memory cell. The disadvantage of this number representation is that a corresponding arithmetic unit would require a doubling of the memory capacity. Using memristors for the registers can avoid this drawback. Therefore, this paper presents a conceptual solution for a three-state adder based on tri-stable memristive devices. The principal feasibility of such a unit is demonstrated by SPICE simulations and the performance increase is evaluated in comparison with a ripple-carry and a carry-look-ahead adder.
35 years of research on business intelligence process: a synthesis of a fragmented literature

The business intelligence (BI) research witnessed a proliferation of contributions during the past three decades, yet the knowledge about the interdependencies between the BI process and organizational context is scant. This has resulted in a proliferation of fragmented literature duplicating identical endeavors. Although such pluralism expands the understanding of the idiosyncrasies of BI conceptualizations, attributes and characteristics, it cannot cumulate existing contributions to better advance the BI body of knowledge. In response, this study aims to provide an integrative framework that integrates the interrelationships across the BI process and its organizational context and outlines the covered research areas and the underexplored ones. ,This paper reviews 120 articles spanning the course of 35 years of research on BI process, antecedents and outcomes published in top tier ABS ranked journals. ,Building on a process framework, this review identifies major patterns and contradictions across eight dimensions, namely, environmental antecedents; organizational antecedents; managerial and individual antecedents; BI process; strategic outcomes; firm performance outcomes; decision-making; and organizational intelligence. Finally, the review pinpoints to gaps in linkages across the BI process, its antecedents and outcomes for future researchers to build upon. ,This review carries some implications for practitioners and particularly the role they ought to play should they seek actionable intelligence as an outcome of the BI process. Across the studies this review examined, managerial reluctance to open their intelligence practices to close examination was omnipresent. Although their apathy is understandable, due to their frustration regarding the lack of measurability of intelligence constructs, managers manifestly share a significant amount of responsibility in turning out explorative and descriptive studies partly due to their defensive managerial participation. Interestingly, managers would rather keep an ineffective BI unit confidential than open it for assessment in fear of competition or bad publicity. Therefore, this review highlights the value open participation of managers in longitudinal studies could bring to the BI research and by extent the new open intelligence culture across their organizations where knowledge is overt, intelligence is participative, not selective and where double loop learning alongside scholars is continuous. Their commitment to open participation and longitudinal studies will help generate new research that better integrates the BI process within its context and fosters new measures for intelligence performance. ,This study provides an integrative framework that integrates the interrelationships across the BI process and its organizational context and outlines the covered research areas and the underexplored ones. By so doing, the developed framework sets the ground for scholars to further develop insights within each dimension and across their interrelationships.
A multilevel hybrid anomaly detection scheme for industrial wireless sensor networks

Real‐time sensing plays an important role in ensuring the reliability of industrial wireless sensor networks (IWSNs). Sensor nodes in IWSNs have inherent limitations that give rise to different anomalies in the network. These anomalies can lead to disastrous and harmful situations or even serious system failures. This article presents a formulation to the design of an anomaly detection scheme for detecting the anomalous node along with the type of anomaly. The proposed scheme is divided into two major parts. First, spatiotemporal correlation within a cluster is obtained for the normal and anomalous behavior of sensor nodes. Second, the multilevel hybrid classifier is used by combining the sequential minimal optimization support vector machine (SMO‐SVM) as a binary classifier with optimally pruned extreme learning machine (OP‐ELM) as a multiclass classifier for detection of an anomalous node and type of anomalies, respectively. Mahalanobis distance‐based lightweight K‐Medoid clustering is used to build a new set of training datasets that represents the original training dataset, by significantly reducing the training time of a multilevel hybrid classifier. Results are analyzed using standard WSN datasets. The proposed model shows high accuracy, i.e., 94.79% and detection rate, i.e., 94.6% with a reduced false positive rate as compared to existing hybrid methods.
The art of illusion as government policy. Analysing political economies of surrealism

ABSTRACT This article advances a critical approach to the analysis of social policy texts drawing on the philosophical perspectives of hyperrealism, surrealism, ethics, and Critical Discourse Analysis. Drawing on official government texts and speeches on the continuing development of Singapore’s education policy, the paper examines the way metaphors of flexibility, diversity, choice, and opportunity are used within an evolving ideological context that work to continually produce truth conditions as justifications for inequality. In doing this, the analysis foregrounds a functional aspect of policy metaphors as divisive mechanisms of neo-liberalism through associating individuals with the appearance of discriminatory forms of economic materiality which does not in fact exist in reality.
A time series autoencoder for load identification via dimensionality reduction of sensor recordings

Current progress in sensor technology is setting the ground to push toward satisfactory solutions to challenging engineering problems, like e.g., system identification and Structural Health Monitoring (SHM). In civil engineering, SHM is often based on the analysis of vibrational recordings, represented by time histories of displacements and/or accelerations, collected through pervasive sensor networks and shaped as Multivariate Time Series (MTS). Despite the great advances in soft computing techniques such as neural networks, inverse problems featuring regression tasks on raw vibrational measurements are still challenging. Developing dimensionality reduction tools, able to infer complex correlations within and across the recorded time series, is then of paramount importance. In this work, we designed an AutoEncoder (AE) capable of condensing MTS-shaped data in a reduced format featuring a few latent variables only. The obtained reduced data representation enhances the solution of inverse problems, like e.g., the identification of the parameters governing the dynamic load applied to a structural system. Numerical examples, aimed at the identification of the loading conditions on a shear-type building, are reported to assess the effectiveness of the proposed procedure.
Adoption return trips: Family tourism and the social meanings of money

Through a focus on the planning and making of family adoption return trips, this paper explores how the social meanings of money are entangled with family-making practices and family holidays. Adoption return trips are a global phenomenon, and travel agencies offer tailored adoption return-trip packages marketed as a type of family tourism. The new trend towards conducting adoption return trips as a family when children are still young is growing and has implications for families’ finances because return trips are expensive endeavours. Still, families prioritise these trips, raising them above purely economic values so they stand out as ‘priceless’. The empirical material consists of interviews with 10 Swedish transnational adoptive families. The analyses show that family adoption return trips, despite their original features, are yet one more way of doing family holidaying. Money becomes an important contribution for understanding how family life is being done in and through parental, child and family-holiday ideals, as well as family intimacy.
Retrieval and molecule sensitivity studies for the global ozone monitoring experiment and the scanning imaging absorption spectrometer for atmospheric chartography

The Global Ozone Monitoring Experiment (GOME) and the Scanning Imaging Absorption spectroMeter for Atmospheric ChartographY (SCIAMACHY) are diode based spectrometers that will make atmospheric constituent and aerosol measurements from European satellite platforms beginning in the mid 1990's. GOME measures the atmosphere in the UV and visible in nadir scanning, while SCIAMACHY performs a combination of nadir, limb, and occultation measurements in the UV, visible, and infrared. A summary is presented of the sensitivity studies that were performed for SCIAMACHY measurements. As the GOME measurement capability is a subset of the SCIAMACHY measurement capability, the nadir, UV, and visible portion of the studies is shown to apply to GOME as well.
RBC: A memory architecture for improved performance and energy efficiency

DRAM-based memory suffers from increasing row buffer conflicts, which causes significant performance degradation and power consumption. As memory capacity increases, the overheads of the row buffer conflict are increasingly worse as increasing bitline length, which results in high row activation and precharge latencies. In this work, we propose a practical approach called Row Buffer Cache (RBC) to mitigate row buffer conflict overheads efficiently. At the core of our proposed RBC architecture, the rows with good spatial locality are cached and protected, which are exempted from being interrupted by the accesses for rows with poor locality. Such an RBC architecture significantly reduces the overheads of performance and energy caused by row activation and precharge, and thus improves overall system performance and energy efficiency. We evaluate RBC architecture using SPEC CPU2006 on a DDR4 memory compared to a commodity baseline memory system. Results show that RBC improves the overall performance by up to 2:24 (16:1% on average) and reduces the memory energy by up to 68:2% (23:6% on average) for single-core simulations. For multi-core simulations, RBC increases the overall performance by up to 1:55 (17% on average) and reduces memory energy consumption by up to 35:4% (21:3% on average).
In-Situ Stable Injectable Collagen-Based Hydrogels for Cell and Growth Factor Delivery

Here we report development of in-situ stable injectable hydrogels for delivery of cells and growth factors based on two precursors, alginate, and collagen/calcium sulfate (CaSO4). The alg/col hydrogels were shear-thinning, injectable through commercially available needles and stable right after injection. Rheological measurements revealed that pre-crosslinked alg/col hydrogels fully crosslinked at 37°C and that the storage modulus of alg/col hydrogels increased with increasing the collagen content or the concentration of CaSO4. The viscoelastic characteristics and injectability of the alg/col hydrogels were not significantly impacted by the storage of precursor solutions for 28 days. An osteoinductive bone morphogenic protein-2 (BMP-2) loaded into alg/col hydrogels was released in 14 days. Human mesenchymal stem cells (hMSCs) encapsulated in alg/col hydrogels had over 90% viability over 7 days after injection. The DNA content of hMSC-laden alg/col hydrogels increased by 6-37 folds for 28 days, depending on the initial cell density. In addition, hMSCs encapsulated in alg/col hydrogels and incubated in osteogenic medium were osteogenically differentiated and formed a mineralized matrix. Finally, a BMP-2 loaded alg/col hydrogel was used to heal a critical size calvarial bone defect in rats after 8 weeks of injection. The alg/col hydrogel holds great promise in tissue engineering and bioprinting applications.