Miracle-dz/UniFAR-FTUs huggingface dataset:
Risk Factors in IT Enterprise Systems' Implementations - a Perspective of SAP Consultants

E nterprise System (ES) is a standard, configurable and customizable, multi-component application suite that includes integrated business solutions for the major business processes, and management functions of an enterprise. It typically includes both transactional and analytical applications, such as Enterprise Resource Planning, Customer Relationship Management, Supply Chain Management, Content Management, Business Intelligence/Business Analytics and others, and constitutes the main source of management information, and the main tool for managing business processes in an enterprise. Despite being popular business software, the implementation failure rate of Enterprise Systems is consistently high [Aloini et al., 2007; Wu, Wang, 2007]. Although there is discussion concerning what criteria should be used to label an implementation a failure [Basten et al., 2011; Lech, 2013; Yeo, 2002], there is no doubt that many ES projects face problems with meeting the original scope, budget and/or schedule. These problems have led to considerable research on implementation success/failure factors regarding both Information Systems in general and Enterprise Systems in particular [e.g., Belassi, Tukel, 1996; Dezdar, Sulaiman, 2009; Kappelman et al., 2006; Nah, Delgado, 2006; Nelson, 2007; Schmidt et al., 2001; Soja, Paliwoda-Pękosz, 2009]. All of this research, however, takes only the perspective of the organisation that adopts the new Information System, while the classic project setup involves three stakeholders: the adopting organisation, the system vendor and the consultants that perform the implementation [Haines, Goodhue, 2003; Simon et al., 2010; Vilpola, 2008, Wang, Chen, 2006]. The perspective of the system vendor and consulting enterprise is largely omitted in the literature. The aim of this paper is to fill this gap in the research and explore the Enterprise System project risk factors from the perspective of the consultants performing the implementation. The paper is structured as follows: the literature review on Enterprise Systems success/failure factors is presented in the following section. It is then followed by a presentation of the results of empirical research, which was conducted on 14 Enterprise System consultants, representing 174 projects and which aimed to identify risk factors using their perspective.
Learning Analytics Interoperability - looking for Low-Hanging Fruits

When Learning Analytics is seeking a wide community, the challenge of efficiently and reliably moving data between systems becomes important. This paper gives a summary of the current status of Learning Analytics Interoperability and proposes a framework to help structuring the interoperability work. The model is based on a three dimensional Enterprise Interoperability Framework mapping concerns, interoperability barriers and potential solutions. The paper also introduces the concept of low-hanging fruits in prioritising among solutions. Data gathered from a small group of Norwegian stakeholders are analysed, and a list of potential interoperability issues is presented.
Low-Complexity Grassmannian Quantization Based on Binary Chirps

We consider autocorrelation-based low-complexity decoders for identifying Binary Chirp codewords from noisy signals in N = 2m dimensions. The underlying algebraic structure enables dimensionality reduction from N complex to m binary di- mensions, which can be used to reduce decoding complexity, when decoding is successively performed in the m binary dimensions. Existing low-complexity decoders suffer from poor performance in scenarios with strong noise. This is problematic especially in a vector quantization scenario, where quantization noise power cannot be controlled in the system. We construct two improvements to existing algorithms; a geometrically inspired algorithm based on successive projections, and an algorithm based on adaptive decoding order selection. When combined with a breadth-first list decoder, these algorithms make it possible to approach the performance of exhaustive search with low complexity.
Dynamic modeling of a 3-D 4-directional braided composite beam with a central rigid body

Abstract Although 3-D braided composites can be incorporated with rotating central body-beam systems, there are currently few dynamic models for the rotating systems made of braided composites. This paper proposes a dynamic model of a 3-D 4-directional braided composite beam with a central rigid body. Based on the Timoshenko beam hypothesis, the displacements of the composite beam are described by the arc-length coordinate, and the displacement field is represented by the slope angle, tensile strain, and shear angle. The assumed mode method is employed to discrete the displacement field, and the dynamic model of the system is derived from the Lagrange equation. The equivalent stiffness matrices of 3-D 4-directional braided composite beams with different braiding angles are obtained using the volume average method. The influences of different angular velocities, braiding angles, and beam section parameters on the system's dynamic characteristics are studied. The model proposed in this study can be utilized to estimate the dynamic responses of braided composite blades, and lays the theoretical foundation for analyzing dynamic characteristics of anisotropic beams in engineering.
Identification of the Aroma Compounds of Ocimum americanum as a Function of Growth Stages and their In Vitro Antioxidant and Anti-inflammatory Potential

Abstract The present study investigated the variability in the content, composition, antioxidant and anti-inflammatory potential of the volatile oil constituents of aerial parts of Ocimum americanum Linn. collected at two stages from two sites of north Himalayas. The essential oils of O. americanum at vegetative and full blooming stages were isolated by using hydrodistillation technique and analysed by gas chromatography with flame ionization detection (GC/FID), GC-with mass spectrometry (GC/MS). The antioxidant potential was evaluated using 2,2ʹ-diphenyl -1-picrylhydrazyl (DPPH) radical scavenging activity, Fe2+ ferrozine test for iron-chelating and hydrogen peroxide scavenging activity methods while anti-inflammatory activity was assayed by measuring the protein denaturation capacity of oil samples. The oil content was recorded highest during the full blooming stage from Ct-2 collection. Out of 28-31 identified constituents, β-bisabolene (14.46-29.74%), (E)-α-bisabolene (11.42-22.17%), methyl chavicol (11.28-17.83%), (E)-β-ocimene (7.48-11.54%), 1,8-cineole (3.29-17.40%), eugenol (1.27-10.42%) and germacrene D (1.92-8.39%) were the major constituents. The oil composition during full blooming stages was characterized by the abundant presence of sesquiterpenes (34.34-70.81%) while phenyl propanoids became the dominant class at vegetative stages (12.55-25.42%). EO’s revealed good results of anti-inflammatory and antioxidant activity at both stages while more potent at full blooming stage.
A WIRE DRAWING MACHINE DESIGNED FOR RESEARCH AND EXPERIMENTAL TEACHING OF MECHANICAL AND METALLURGICAL ENGINEERING COURSES

The aim of this work is to present a wire drawing machine bench designed and built for research and experimental teaching of mechanical and metallurgical engineering courses. This machine is a redesign of the one already presented at CONEM 2000 (Mechanical National Conference in North and North-East Brazil). It is currently set up to enable students to measure the wire drawing force for two pulling wire velocities (7.8x10 -3 m/s and 3.2x10 -2 m/s), using different lubricants, and so to allow comparison with theoretical models. During tests, copper wire was progressively drawn in stages from an initial 3.2mm diameter down to 1.3mm. For each pulling wire, eight tungsten carbide die were used and chosen to produce succesive area reductions of approximately 20%. , resulting in a total true deformation of approximately 180.2%. The effect of lubrication and lack of it on wire pulling force was measured, using olive oil and graphite spray for comparison. Graphite spray facilitated the least wire pulling force, whereas olive oil proved to be inadequate as a lubricant. Load cell measurements (500kgf (~ 4.9 kN) capacity) confirmed that the force needed to draw larger diameter wire is greater than for smaller diameters. However, students can also observe that as the wire diameter decreases there is a corresponding increase in pulling wire stress. The method of uniform deformation energy was used to compare with load cell measurements.
Towards the next generation of online social networks

This thesis considers the design of a social network that addresses the shortcomings of the existing ones, and identifies user privacy, security, and service availability as strong motivations that push the architecture of the proposed design to be distributed. We describe our design in detail and identify the property of resiliency as a key objective for the overall design philosophy. We define the system goals, threat model, and trust model as part of the system model, and discuss the challenges in adapting such distributed frameworks to become highly available and highly resilient in potentially hostile environments. We propose a distributed solution called MyZone to address these challenges based on a trust-based friendship model for replicating user profiles and disseminating messages, and evaluate the feasibility of our solution based on availability, resource utilization and scalability.
Internet of Intelligence: A Survey on the Enabling Technologies, Applications, and Challenges

The Internet of Intelligence is conceived as an emerging networking paradigm, which will make intelligence as easy to obtain as information. This paper provides an overview of the Internet of Intelligence, focusing on motivations, architecture, enabling technologies, applications, and existing challenges. This can provide a good foundation for those who are interested to gain insights into the concept of the Internet of Intelligence and the key enablers of this emerging networking paradigm. Specifically, this paper starts by investigating the evolution of networking paradigms and artificial intelligence (AI), based on which we present the motivations of the Internet of Intelligence by demonstrating that networking needs intelligence and intelligence needs networking. We then present the layered architecture to characterize the Internet of Intelligence systems and discuss the enabling technologies of each layer. Moreover, we discuss the critical applications and their integration with the Internet of Intelligence paradigm. Finally, some technical challenges and open issues are summarized to fully exploit the benefits of the Internet of Intelligence.
Aircraft Cruise Drag Reduction Through Variable Camber Using Existing Control Surfaces

The ability to morph the shape of an aircraft wing to optimize performance is widely accepted as a path to improved aircraft e ciency. A simpler approach is to change the wing camber using existing control surfaces. In this work, a Reynolds-averaged Navier-Stokes based aerodynamic shape optimization methodology is applied to the design of a business jet with variable camber. Variable camber is achieved using the three existing control surfaces on each wing. Multipoint optimization is performed over a range of cruise operating conditions with and without variable camber. Variable camber is found to yield a reduction in drag of approximately 3-11 counts, or 1-5%, over a range of cruise conditions, with the largest reductions seen at lower lift coe cients. The control surface deflections are used to reduce the wing camber at lower lift cruise conditions, leading to an increase in the aircraft angle of attack across most operating points. The increased angles of attack transfer lift to the fuselage, which enables reductions in induced, wave, and trim drag. This additional drag reduction mechanism has not been identified in previous studies and cannot be seen in optimizations that do not include the fuselage and a trim constraint.
Association of Pain with Plasma C5a in Patients with Neuromyelitis Optica Spectrum Disorders During Remission

Objective To investigate the association of pain with plasma C5a levels and other related inflammatory cytokines in neuromyelitis optica spectrum disorders (NMOSD) patients during remission. Participants and Methods NMOSD patients (n = 87) and healthy controls (HC; n = 44) were consecutively recruited between January 2017 and April 2018. Plasma complement 5 (C5), C5a, interleukin (IL)-6, tumor necrosis factor (TNF)-α, and IL-1β levels were detected. Visual Analogue Scale (VAS), ID pain scale, 24-item Hamilton Depression Scale (HAMD), Multiple Sclerosis Impact Scale (MSIS-29), and Kurtzke Expanded Disability Status Scale (EDSS) were used to evaluate the degree and types of pain, the existence of depression and anxiety, and the life quality and disability status of patients. Binary logistic regression equation was used to assess the association of pain with plasma C5a levels. Results Among the 87 NMOSD patients, 40 complained of pain that in 67.5% (27/40) of cases had a neuropathic component (ID pain ≥2). Plasma C5a, IL-6, TNF-α, and IL-1β levels were significantly elevated in NMOSD patients than in HC. Plasma C5 levels were negatively correlated with the time from sampling to the last relapse or disease onset. NMOSD patients with pain had higher plasma C5a levels, and they suffered from a higher disability, more anxiety, and worse life quality compared to those patients without pain. In NMOSD patients with pain, there were not significant differences between plasma levels of C5, C5a, IL-6, TNF-α, or IL-1β, regardless of neuropathic pain or not. Binary logistic regression showed that the OR of plasma C5a level was 1.002, with gender and EDSS score were identified as independent factors associated with pain in NMOSD. Conclusion NMOSD patients during remission had elevated C5a and related inflammatory cytokines levels in peripheral blood. Elevated C5a may have a unique role in the pathogenesis of pain in NMOSD patients.
Enabling Precision Medicine via Contemporary and Future Communication Technologies: A Survey

Precision medicine (PM) is an innovative medical approach that considers differences in the individuals’ omics, medical histories, lifestyles, and environmental information in treating diseases. To fully achieve the envisaged gains of PM, various contemporary and future technologies have to be employed, among which are nanotechnology, sensor network, big data, and artificial intelligence. These technologies and other applications require a communication network that will enable them to work in tandem for the benefit of PM. Hence, communication technology serves as the nervous system of PM, without which the entire system collapses. Therefore, it is essential to explore and determine the candidate communication technology requirements that can guarantee the envisioned gains of PM. To the best of our knowledge, no work exploring how communication technology directly impacts the development and deployment of PM solutions exists. This survey paper is designed to stimulate discussions on PM from the communication engineering perspective. We introduce the fundamentals of PM and the demands in terms of quality of service that each of the enabling technologies of PM places on the communication network. We explore the information in the literature to suggest the ideal metric values of the key performance indicators for the implementation of the different components of PM. The comparative analysis of the suitability of the contemporary and future communication technologies for PM implementation is discussed. Finally, some open research challenges for the candidate communication technologies that will enable the full implementation of PM solutions are highlighted.
An improved coupled PDE system applied to the inverse image denoising problem

<abstract><p>The problem of interest in this paper is the mathematical and numerical analysis of a new non-variational model based on a high order non-linear PDE system resulting from image denoising. This model is motivated by involving the decomposition approach of $ H^{-1} $ norm suggested by Guo et al. <sup>[<xref ref-type="bibr" rid="b1">1</xref>,<xref ref-type="bibr" rid="b2">2</xref>]</sup> which is more appropriate to represent the small details in the textured image. Our model is based on a diffusion tensor that improves the behavior of the Perona-Malik diffusion directions in homogeneous regions and the Weickert model near tiny edges with a high diffusion order. A rigorous analysis of the existence and uniqueness of the weak solution of the proposed reaction-diffusion model is cheked in a suitable functional framework, using the Schauder fixed point theorem. Finally, we carry out a numerical result to show the effectiveness of our model by comparing the results obtained with some competitive models. </p></abstract>
Electronically Controlled Fixed-Frequency Beam-Scanning Periodic Leaky-Wave Antenna With Positive-Order-Harmonic Radiations

An electronically controlled fixed-frequency beam-scanning periodic leaky-wave antenna operating in a millimeter-wave band is presented in this letter. An air-filled gap waveguide (GW) base is employed as a millimeter-wave excitation thanks to its low-loss property. Totally, 60 patches in a staggered two-row arrangement are introduced as the radiating elements, which get energies from the GW through longitudinal slots etched on the middle metal layer, and this produces reverse phases in the two rows under a TE10-mode excitation. Then, a method by constructing an equivalent phase constant is developed in this letter, and positive-order-harmonic radiation is used to analyze the radiation property. By introducing the period-reconfigurable method, a fixed-frequency beam-scanning performance is achieved. In addition, the developed antenna is fabricated and experiments have been implemented. A beam-scanning range of 70° from −35° to 35° is realized using the positive-order-harmonic radiations at 29 GHz, and the measured peak gain arrives at 16.5 dBi. The design shows possible applications in millimeter-wave communications.
A Novel Proxy for Tracking the Provenance of Dust Based on Paired E1’‐Peroxy Paramagnetic Defect Centers in Fine‐Grained Quartz

Crystal lattice defects in quartz have long been exploited for age determination, yet also show potential for sediment provenance studies. Here, we introduce a novel method for tracking aeolian dust provenance by utilizing the natural accumulation of E1’ and peroxy defect centers in quartz. Our approach is based on the previously observed premise that E1’ and peroxy centers arise from Frenkel defect pairs, and that their concentration increases with the age of the quartz‐bearing source rock. We propose that these defect centers can be utilized as a characteristic feature of the source rock and consequently, for fingerprinting sediments derived from it. We successfully apply our new protocol to distinguish fine‐grained quartz extracted from loess deposits from two regions in Central Asia which are known to derive from different source material of differing age. Our method offers strong potential for identifying variability in source, both spatially and through time down sedimentary sequences.
PSIC: Priority-Strict Multi-Core IRQ Processing

While processing external events, in the form of interrupt requests (IRQs), is a key concern of digital control systems, processing these events can be of different importance for a system’s functionality. Therefore, it is necessary, especially for real-time systems, to ensure that the handling of low-priority IRQs does not interfere with high-priority interrupt-service routines (ISRs) to prevent priority inversions. While prioritizing ISRs on single-core machines is a long-solved problem, priority-strict IRQ handling in multi-core systems is, as we will show, quite challenging with current interrupt controllers.With PSIC, we propose a hardware/software co-design that ensures the priority-strict execution of the top-m ISRs on an m-core machine at minimal interruption-induced overheads. We developed a drop-in replacement for an off-the-shelf interrupt controller that delivers IRQs in strict priority order while achieving low delivering delays at moderate hardware costs. Combined with a minimal IRQ software subsystem, which requires no inter-core synchronization, PSIC guarantees a priority-strict ISR execution on multiple cores.
Distributions of Posterior Quantiles and Economic Applications

We characterize the distributions of posterior quantiles under a given prior. Unlike the distributions of posterior means, which are known to be mean-preserving contractions of the prior, the distributions of posterior quantiles coincide with a first-order stochastic dominance interval bounded by an upper and a lower truncation of the prior. We apply this characterization to several environments, ranging across political economy, Bayesian persuasion, industrial organization, econometrics, finance
Mapuche Family Education: Epistemes to Dialogue With School Education

This article analyzes epistemes of Mapuche family education obtained from parents in communities of the La Araucan ía region of Chile from a perspective of dialogue of knowledge with school education. The production of Mapuche knowledge is considered an epistemological critique of the Western monoculturalism of the school curriculum. The methodology used is qualitative research and it is based on Grounded Theory. The results show intra-family and intra-community education, and processes that imply a double immersion in Chilean society. It is concluded that education is organized considering methods constructed with the logic of Mapuche educational knowledge, as a contribution to a dialogue with Western hegemonic knowledge.
MILCDock: Machine Learning Enhanced Consensus Docking for Virtual Screening in Drug Discovery

Molecular docking tools are regularly used to computationally identify new molecules in virtual screening for drug discovery. However, docking tools suffer from inaccurate scoring functions with widely varying performance on different proteins. To enable more accurate ranking of active over inactive ligands in virtual screening, we created a machine learning consensus docking tool, MILCDock, that uses predictions from five traditional molecular docking tools to predict the probability a ligand binds to a protein. MILCDock was trained and tested on data from both the DUD-E and LIT-PCBA docking datasets and shows improved performance over traditional molecular docking tools and other consensus docking methods on the DUD-E dataset. LIT-PCBA targets proved to be difficult for all methods tested. We also find that DUD-E data, although biased, can be effective in training machine learning tools if care is taken to avoid DUD-E's biases during training.
Left to the Reader: Abstracting Solutions in Mathematical Reasoning

Formal mathematical reasoning is unique in its precision: any valid conclusion can be justified by a sequence of base axioms. But human-written proofs or solutions rarely operate at that level. Instead, obvious steps are skipped to provide a simple, lucid argument. This is especially important in an educational setting, where too many details in an example solution, or too few, can confuse a student. What are the key steps for humans in a given formal solution? We investigate several computational hypotheses in the context of equation solving. Specifi- cally, we take a reinforcement learning agent that solves equations using low-level axioms, and propose a series of methods for abstracting its solutions by selecting key steps. We consider methods based on the semantic distance between subse- quent steps, based on the steps with the highest uncertainty for the agent, and based on transitions between latent “high-level skills” learned from a large number of agent-produced solutions. In a human evaluation we find that skill-base simplifi- cations were judged most useful. These results suggest new directions for understanding human mathematical reasoning.