Miracle-dz/UniFAR-FTUs huggingface dataset:
A Model Predictive Controller for Managing QoS Enforcements and Microarchitecture-Level Interferences in a Lambda Platform

Lambda paradigm, also known as Function as a Service (FaaS), is a novel event-driven concept that allows companies to build scalable and reliable enterprise applications in an off-premise computing data-center as a serverless solution. In practice, however, an important goal for the service provider of a Lambda platform is to devise an efficient way to consolidate multiple Lambda functions in a single host. While the majority of existing resource management solutions use only operating-system level metrics (e.g., average utilization of computing and I/O resources) to allocate the available resources among the submitted workloads in a balanced way, a resource allocation schema that is oblivious to the issue of shared-resource contention can result in a significant performance variability and degradation within the entire platform. This paper proposes a predictive controller scheme that dynamically allocates resources in a Lambda platform. This scheme uses a prediction tool to estimate the future rate of every event stream and takes into account the quality of service enforcements requested by the owner of each Lambda function. This is formulated as an optimization problem where a set of cost functions are introduced (i) to reduce the total QoS violation incidents; (ii) to keep the CPU utilization level within an accepted range; and (iii) to avoid the fierce contention among collocated applications for obtaining shared resources. Performance evaluation is carried out by comparing the proposed solution with an enhanced interference-aware version of three well-known heuristics, namely spread, binpack (the two native clustering solutions employed by Docker Swarm) and best-effort resource allocation schema. Experimental results show that the proposed controller improves the overall performance (in terms of reducing the end-to-end response time) by 14.9 percent on average compared to the best result of the other heuristics. The proposed solution also increases the overall CPU utilization by 18 percent on average (for lightweight workloads), while achieves an average 87 percent (maximum 146 percent) improvement in preventing QoS violation incidents.
Lipase-catalyzed ethanolysis of Jatropha curcas L. oil assisted by ultrasonication

Transesterification of non-edible oils using immobilized lipase is a promising process for biodiesel production. Thus, this study aimed to evaluate the enzymatic transesterification of the non-edible Jatropha curcas oil for FAEE production under ultrasound irradiation in a solvent-free system. The effects of enzyme concentration, water concentration, molar ratio of ethanol to oil and ultrasound power on the FAEE conversion have been evaluated. The results show that enzyme concentration and irradiation power have a positive significant effect on FAEE conversion, where an increase in these variables leads to higher conversions. Conversion above 54% of FAEE was achieved with 1.5 hours of reaction time using ultrasound irradiation, reducing reaction time by at least 3 times, when compared with the same experimental conditions without ultrasound irradiation. Results showed that ultrasound can improve reaction conversion mainly by enhancing the mass transfer between the constituents of the reactions.
Customizing CO2 laser inscription of LPG sensors to enhance the sensitivity to refractive index

The manufacturing process of long period fiber gratings (LPG) is investigated in order to enhance the sensitivity of the sensors to the surrounding refractive index, considering a specific mode and wavelength range. The LPG is inscribed in a standard single-mode fiber with a CO2 laser beam. It is found that the environment refractive index sensitivity is increased mainly due to the duty cycle of the grating. Results show an increase of 89% on the resonant wavelength shift for samples with refractive index varying from 1 to 1.42.
Nanotechnology and Its Use in Tissue Engineering

Tissue Engineering is an emerging field with promises for a better future. It is a blend of biology and engineering. Millions of people lose limbs and body parts as the results of tragic accidents. Patients with diabetes, ischemia, suffer from non-functional pancreas, heart. Tissue engineering plays a major role in their lives. Instead of organs donated voluntarily (long waiting is a problem here), tissue engineering has the potential to come up with replacements. The combination of nanotechnology with engineering and biology has made some excellent improvements. In this chapter, the aim is to provide very basic knowledge about the art and science of blending tissue engineering with nanotechnology. At the same time, it highlights related fields like issues of biocompatibility, fate of nanoparticles, side effects, work with stem cells, etc.
Development of artificial surface layers for thin film cathode materials

The present work was based on the investigation of different thin film components of Li ion batteries. A first part was dedicated to the deposition of cathodes in thin film form of a known material, LiCoO2, and an alternative one, Li(NiMnCo)O2 employing physical vapor deposition (PVD) and chemical vapor deposition (CVD), respectively. A second part was focused on the cathode-electrolyte interface for three case studies: 1) as deposited LiCoO2 cathode thin film, 2) ZrO2 coated LiCoO2 thin film and 3) LiPON coated LiCoO2 thin film. The interface cathode-electrolyte of these three cases were studied before and after galvanostatic cycling to determine surface layer characteristics and changes arising on the interface after battery operation. The interface of a bare LiCoO2 layer was further studied after soaking in liquid electrolyte to elucidate the effect of short storage procedures in batteries. Additionally, LiPON thin films were studied on the basis of structural changes occurring with nitrogenation and its correlation to a possible mechanism during ion conduction. Composition of phosphate glasses with rf sputtering was proven to be greatly influenced by the gas ratio employed.
LINEAR MODELLING OF MAGNETO-RHEOLOGICAL DAMPERS USING HYBRID INTELLIGENCE TECHNIQUE

In this paper, the local linear models of a magneto-rheological (MR) damper are obtained based on the Takagi-Sugeno (T-S) fuzzy modelling approach. In these local linear models, the output force of the MR damper is expressed as the linear summation of the state variables (relative displacement and relative velocity) and input voltage. To obtain these local linear models with high accuracy, the genetic algorithm (GA) with a new encoding method is applied to search for the optimal model parameters. The proposed hybrid intelligence technique can evolve the fuzzy rule structure (number of rules and selection of rules) and the input structure (number of premise inputs and selection of premise inputs) simultaneously so that the obtained linear models have the simplest structures without decreasing the modelling accuracy. To validate the proposed approach, the modelling errors between the MR damper output and the corresponding linear model output are compared for the given number of rules case and for the automatically selected rules case with using three different selection approaches for the premise input variables. It is confirmed by the validation results that the proposed hybrid intelligence technique can find the optimal linear model for the MR damper.
Reparable Cell Sonoporation in Suspension: Theranostic Potential of Microbubble

The conjunction of low intensity ultrasound and encapsulated microbubbles can alter the permeability of cell membrane, offering a promising theranostic technique for non-invasive gene/drug delivery. Despite its great potential, the biophysical mechanisms of the delivery at the cellular level remains poorly understood. Here, the first direct high-speed micro-photographic images of human lymphoma cell and microbubble interaction dynamics are provided in a completely free suspension environment without any boundary parameter defect. Our real-time images and theoretical analyses prove that the negative divergence side of the microbubble's dipole microstreaming locally pulls the cell membrane, causing transient local protrusion of 2.5 µm in the cell membrane. The linear oscillation of microbubble caused microstreaming well below the inertial cavitation threshold, and imposed 35.3 Pa shear stress on the membrane, promoting an area strain of 0.12%, less than the membrane critical areal strain to cause cell rupture. Positive transfected cells with pEGFP-N1 confirm that the interaction causes membrane poration without cell disruption. The results show that the overstretched cell membrane causes reparable submicron pore formation, providing primary evidence of low amplitude (0.12 MPa at 0.834 MHz) ultrasound sonoporation mechanism.
Real-Time Map Manipulation for Mobile Robot Navigation

vi CHAPTER 1: INTRODUCTION 1 1.1 Problem 1 1.2 Research Objectives 1 1.3 Research Approach 2 1.4 Applications 3 1.5 Thesis Organization 3 CHAPTER 2: LITERATURE REVIEW 4 2.1 Highly Autonomous Approach 5 2.2 Teleoperated Approach 10 2.2.1 Haptic Feedback 11 2.2.2 Augmented Reality 12 2.2.3 Interface Evaluation 13 2.3 Semi-Autonomous Approach 15 2.3.1 Single-Robot Interfaces 15 2.3.2 Multi-Robot Interfaces 16 2.3.3 Interface Evaluation 17 2.3. 4 Scene Manipulation 19 2.4 Summary 20 CHAPTER 3: PATH PLANNING ALGORITHMS 22 3.1 Potential Fields 23 3.2 Probabilistic Road Map 26 3.3 PRM-A* 30
Indoor Scene Segmentation using Conditional Random Fields

Indoor scene segmentation is a problem that has become very popular in the field of computer vision with applications that include robotics, medical imaging, home remodeling, and video surveillance. This problem proves even more difficult when the scene is cluttered. Our project aims to explore ways to improve indoor scene segmentation algorithms by examining and evaluating a popular method. We focus on evaluating the robustness of the algorithm for indoor scene segmentation described in [16] by Silberman et. al which uses SIFT features and conditional random fields to produce segmentations. In our project, we reimplement their method and compare performance by modifying specific sections. We find that the neural network used in [16] is not robust to an increasing number of classes, but the CRF model is in the sense that as we increase the number of classes, the CRF becomes increasingly important to produce an accurate segmentation. Furthermore, we also demonstrate that changing the algorithm we use to generate superpixel segmentations increases classification accuracy of the entire pipeline.
Daily activity patterns of 2316 men and women from five countries differing in socioeconomic development

Daily rhythmicity in the locomotor activity of laboratory animals has been studied in great detail for many decades, but the daily pattern of locomotor activity has not received as much attention in humans. We collected waist-worn accelerometer data from more than 2000 individuals from five countries differing in socioeconomic development and conducted a detailed analysis of human locomotor activity. Body mass index (BMI) was computed from height and weight. Individual activity records lasting 7 days were subjected to cosinor analysis to determine the parameters of the daily activity rhythm: mesor (mean level), amplitude (half the range of excursion), acrophase (time of the peak) and robustness (rhythm strength). The activity records of all individual participants exhibited statistically significant 24-h rhythmicity, with activity increasing noticeably a few hours after sunrise and dropping off around the time of sunset, with a peak at 1:42 pm on average. The acrophase of the daily rhythm was comparable in men and women in each country but varied by as much as 3 h from country to country. Quantification of the socioeconomic stages of the five countries yielded suggestive evidence that more developed countries have more obese residents, who are less active, and who are active later in the day than residents from less developed countries. These results provide a detailed characterization of the daily activity pattern of individual human beings and reveal similarities and differences among people from five countries differing in socioeconomic development.
A PROPOSED FRAMEWORK BETWEEN INTERNAL, EXTERNAL AND PEDAGOGY DIMENSIONS IN ADOPTION OF INTERACTIVE MULTIMEDIA E-LEARNING

This study about interactive multimedia e-learning aims to improve our understanding about the dynamics of e-learning. The objective is to critical evaluate and better understand the interrelationships in the proposed framework between internal, external and the pedagogy dimensions in adoption of interactive multimedia and e-learning. It develops a tool to measure creative user adoption of interactive multimedia and e-learning services by using Partial Least Squares algorithm as the method of estimation and the major analytical tool in this study. Finding of a small scale data sampling of students in United Kingdom indicate that the proposed measurement framework is an acceptable fit with the data. Overall, the findings supply a precise tool for measuring creative user adoption of interactive multimedia and e-learning services, providing further insights for researchers and may provide to guide research and practice in interactive multimedia and e-learning by using communication media.
Blind analysis of atrial fibrillation electrograms: A sparsity-aware formulation

The problem of blind sparse analysis of electrogram (EGM) signals under atrial fibrillation (AF) conditions is considered in this paper. A mathematical model for the observed signals that takes into account the multiple foci typically appearing inside the heart during AF is firstly introduced. Then, a reconstruction model based on a fixed dictionary is developed and several alternatives for choosing the dictionary are discussed. In order to obtain a sparse solution, which takes into account the biological restrictions of the problem at the same time, the paper proposes using a Least Absolute Shrinkage and Selection Operator (LASSO) regularization followed by a post-processing stage that removes low amplitude coefficients violating the refractory period characteristic of cardiac cells. Finally, spectral analysis is performed on the clean activation sequence obtained from the sparse learning stage in order to estimate the number of latent foci and their frequencies. Simulations on synthetic signals and applications on real data are provided to validate the proposed approach.
Taking knowledge users’ knowledge needs into account in health: an evidence synthesis framework

The increased demand for evidence-based practice in health policy in recent years has provoked a parallel increase in diverse evidence-based outputs designed to translate knowledge from researchers to policy makers and practitioners. Such knowledge translation ideally creates user-friendly outputs, tailored to meet information needs in a particular context for a particular audience. Yet matching users’ knowledge needs to the most suitable output can be challenging. We have developed an evidence synthesis framework to help knowledge users, brokers, commissioners and producers decide which type of output offers the best ‘fit’ between ‘need’ and ‘response’. We conducted a four-strand literature search for characteristics and methods of evidence synthesis outputs using databases of peer reviewed literature, specific journals, grey literature and references in relevant documents. Eight experts in synthesis designed to get research into policy and practice were also consulted to hone issues for consideration and ascertain key studies. In all, 24 documents were included in the literature review. From these we identified essential characteristics to consider when planning an output—Readability, Relevance, Rigour and Resources—which we then used to develop a process for matching users’ knowledge needs with an appropriate evidence synthesis output. We also identified 10 distinct evidence synthesis outputs, classifying them in the evidence synthesis framework under four domains: key features, utility, technical characteristics and resources, and in relation to six primary audience groups—professionals, practitioners, researchers, academics, advocates and policy makers. Users’ knowledge needs vary and meeting them successfully requires collaborative planning. The Framework should facilitate a more systematic assessment of the balance of essential characteristics required to select the best output for the purpose.
Feature fusion based hashing for large scale image copy detection

Most of existing approaches use only a single feature to represent an image for copy detection. However, a single feature is often insufficient to characterize the image content. Besides, with the exponential growth of online images, it's urgent to explore a way of tackling the problem of large scale. In this paper, we propose a feature fusion based hashing method which effectively utilize the correlation between two feature models and efficiently accomplish large scale image copy detection. To accurately map images into the Hamming space, our hashing method not only preserves the local structure of individual feature but also globally consider the local structures for all the features to learn a group of hash functions. The experiment results show that the proposed method outperforms the state-of-the-art techniques in both accuracy and efficiency.
9-Phenanthrol, a TRPM4 Inhibitor, Protects Isolated Rat Hearts from Ischemia–Reperfusion Injury

Despite efforts to elucidate its pathophysiology, ischemia–reperfusion injury lacks an effective preventative intervention. Because transient receptor potential cation channel subfamily M member 4 (TRPM4) is functionally expressed by many cell types in the cardiovascular system and is involved in the pathogenesis of various cardiovascular diseases, we decided to assess its suitability as a target of therapy. Thus, the aim of this study was to examine the possible cardioprotective effect of 9-phenanthrol, a specific inhibitor of TRPM4. Isolated Langendorff-perfused rat hearts were pretreated with Krebs–Henseleit (K–H) solution (control), 9-phenanthrol, or 5-hydroxydecanoate (5-HD, a blocker of the ATP-sensitive potassium channel) and then subjected to global ischemia followed by reperfusion with the K–H solution. To evaluate the extent of heart damage, lactate dehydrogenase (LDH) activity in the effluent solution was measured, and the size of infarcted area of the heart was measured by 2,3,5-triphenyltetrazolium chloride staining. In controls, cardiac contractility decreased, and LDH activity and the infarcted area size increased. In contrast, in hearts pretreated with 9-phenanthrol, contractile function recovered dramatically, and the infarcted area size significantly decreased. The cardioprotective effects of 9-phenanthrol was not completely blocked by 5-HD. These findings show that 9-phenanthrol exerts a cardioprotective effect against ischemia in the isolated rat heart and suggest that its mechanism of action is largely independent of ATP-sensitive potassium channels.
Effectiveness and clinical response rates of a residential eating disorders facility

ABSTRACT The purpose of this study was to determine the effectiveness of a residential treatment program for adults and adolescents with eating disorders across a wide spectrum of measures. Data on body mass, eating disorder severity, depression, anxiety, and two measures of quality of life were collected on 139 consecutively admitted adolescents and 111 adults at a residential treatment program (N = 250). The same measures were completed at post-treatment. Group level analyses showed that adults and adolescents improved on all measures analyzed. Only 1.7% of adolescents and 2.3% of adults were below a Body Mass Index of 18.5 at discharge. Positive results across diagnoses and ages are reported for three subscales of the Eating Disorder Inventory-3, with clinical response rates reported. Using clinical responder analyses, it was found that for all individuals struggling with secondary issues, 74.7% were responders on the Beck Depression Inventory-II, 41.0% on the Beck Anxiety Inventory, 63.5% on a measure of quality of life, and 95.8% were responders on the physical subscale and 72.6% on the mental subscale of the SF-36-v2. This study suggests that residential treatment for eating disorders is effective at the group level, and it was effective for the majority of individuals within the group.
Amplified Spontaneous Emission Noise Power in Distributed Raman Amplifiers

The noise accompanying an optically amplified signal plays an important role in understanding the basic properties of the gain medium. In this paper, we demonstrate an analytical formalism and a numerical integration of the amplified spontaneous emission (ASE) noise power for distributed Raman amplifier (DRA). Three types of distributed Raman amplifiers; forward, backward and bidirectional pumping configurations, are simulated and compared. Index Terms—Distributed Raman Amplifier (DRA), Amplified Spontaneous Emission (ASE), Bidirectional Pumping, Counter Pumping. ——————————  ——————————
StereoScan : Dense 3 D Reconstruction in Real-time

As a core subject in computer vision and robotics, 3D perception from stereo video is a practical problem and hence draws a lot of interest from researchers around the world. In the paper, the author proposes a new approach to build 3d maps from stereo sequences in real-time without expensive hardware involved. More specifically, the author combines both efficient stereo matching and multi-view linking scheme for generating consistent 3d point clouds. The experiment shows that the visual odometry part of the algorithm runs at 25 fps and the depth maps 3 to 4 fps, which is sufficient for online 3D reconstruction. This paper has three main significant contribution: real-time scene flow computation with multi-thousand feature matches, robust visual odometry algorithm proposed and solving the associated correspondence problem in 3D reconstruction in a greedy, accurate and efficient way. Even though stereo matching is part of the 3D reconstruction pipeline, it’s, however, in the scope of another paper.
When is a problem a design science problem ?

This study investigates the types of research problem for which Design Science Research (DSR) is suitable. This requires that DSR approaches are compared and contrasted with intervention-free empirical approaches, in order to determine the strengths and weakness of each approach. From this distinction, three guidelines are presented to allow Information Systems (IS) researchers to identify appropriate research problems for DSR, namely (1) when the prescriptive aspect of the research problem is less mature than the analytical, explanatory, or predictive aspect, (2) when an opportunity arises to engage with a class of design problems where effective existing solutions do not yet exist, (3) when important elements of a system may only become visible through the act of design. These three guidelines are discussed in the context of the IS design literature, and illustrated using examples of existing DSR studies.