Miracle-dz/UniFAR-FTUs huggingface dataset:
Graph Coloring via Locally-Active Memristor Oscillatory Networks

This manuscript provides a comprehensive tutorial on the operating principles of a bio-inspired Cellular Nonlinear Network, leveraging the local activity of NbOx memristors to apply a spike-based computing paradigm, which is expected to deliver such a separation between the steady-state phases of its capacitively-coupled oscillators, relative to a reference cell, as to unveal the classification of the nodes of the associated graphs into the least number of groups, according to the rules of a non-deterministic polynomial-hard combinatorial optimization problem, known as vertex coloring. Besides providing the theoretical foundations of the bio-inspired signal-processing paradigm, implemented by the proposed Memristor Oscillatory Network, and presenting pedagogical examples, illustrating how the phase dynamics of the memristive computing engine enables to solve the graph coloring problem, the paper further presents strategies to compensate for an imbalance in the number of couplings per oscillator, to counteract the intrinsic variability observed in the electrical behaviours of memristor samples from the same batch, and to prevent the impasse appearing when the array attains a steady-state corresponding to a local minimum of the optimization goal. The proposed Memristor Cellular Nonlinear Network, endowed with ad hoc circuitry for the implementation of these control strategies, is found to classify the vertices of a wide set of graphs in a number of color groups lower than the cardinality of the set of colors identified by traditional either software or hardware competitor systems. Given that, under nominal operating conditions, a biological system, such as the brain, is naturally capable to optimise energy consumption in problem-solving activities, the capability of locally-active memristor nanotechnologies to enable the circuit implementation of bio-inspired signal processing paradigms is expected to pave the way toward electronics with higher time and energy efficiency than state-of-the-art purely-CMOS hardware.
Physical Model Study of the Seismic Performance of Highway Embankments with and without Geotextile

In order to ensure structural safety and integrity in earthquake conditions, it may be useful or even necessary to increase the seismic safety of the highway embankments with reinforcement inclusions. The inclusion of geosynthetics in highway embankments may provide an additional tensile strength and durability to construct more stable and earthquake resistant embankments. In this study, the contributions of the primary factors as inclusion of the geotextile reinforcement, slope inclination and dynamic motion characteristics affecting the seismic performance of the highway embankments are evaluated. Shake table models of the unreinforced and geosynthetic reinforced highway embankments with different slope inclinations are designed. An extensive series of shake table tests were performed under dynamic motions with different predominant frequencies. Test results revealed that inclusion of geotextiles in the embankment model causes deamplification of the transmitted accelerations traveling through the reinforced embankment models. Thus, the geosynthetic reinforcement successfully enhances the seismic performance and mitigates earthquake-related hazards. Contribution of this study to the literature is that the efficiency of the geosynthetic reinforcement by means of energy absorption properties is highly dependent on the dynamic motion characteristics but less dependent to the degree of slope inclination.
To Compare the Effect of Lumbar Stabilization Exercise and Conservative Treatment in Lowback Pain for Healthcare Professionals

Introduction: Lumbar stabilization exercise provides a greater support to spine and helps in preventing low back pain. Lumbar stabilization exercise includes pelvic tilting, Knee to chest position, lumbar rotation stretch, transverse abdominis tuck, hip bridging exercises. Aim: The aim of the study is to determine the effectiveness of lumbar stabilization exercises and conservative treatment in low back pain for health care professionals. Method: 30 subjects were selected based on the inclusion and exclusion criteria. Group A Consist of 15 subjects were given lumbar stabilization exercise with interferential therapy. Group B Consists of 15 subjects were given conservative treatment with interferential therapy. The outcome factor used is NPRS (Numerical pain rating scale) and Modified Oswestry low back pain disability Questionnaire. The collected data was tabulated & analyzed using descriptive & inferential statistics. Result: paired t-test revealed that the mean are statistically significant between pre-test and post test in lunbar stabilization group with p<0.05 and the unpaired t-test conducted between group A and B resulted that there was a significant difference between the groups with the p value of 0.0001. Conclusion: This study concluded that lumbar stabilization exercises with interferential therapy (Group A) is more effective than conservative management with interferential therapy (Group B) in the management of low back pain among healthcare professionals.
ADVERTISEMENT ALLOCATION AND TRUST MECHANISMS DESIGN IN SOCIAL NETWORKS

Title of dissertation: ADVERTISEMENT ALLOCATION AND TRUST MECHANISMS DESIGN IN SOCIAL NETWORKS Peixin Gao Dissertation directed by: Professor John S. Baras Dept. of Electrical & Computer Engineering Social network sites (SNS), such as Facebook, Google+ and Twitter, have attracted hundreds of millions of users daily since their appearance. Within SNS, users connect to each other, express their identity, disseminate information and form cooperation by interacting with their connected peers. The increasing popularity and ubiquity of SNS usage and the invaluable user behaviors and connections give birth to many applications and business models. We look into several important problems within the social network ecosystem. The first one is the SNS advertisement allocation problem. The other two are related to trust mechanisms design in social network setting, including local trust inference and global trust evaluation. In SNS advertising, we study the problem of advertisement allocation from the ad platform’s angle, and discuss its differences with the advertising model in the search engine setting. By leveraging the connection between social networks and hyperbolic geometry, we propose to solve the problem via approximation using hyperbolic embedding and convex optimization. A hyperbolic embedding method, HyperCubeMap, is designed for the SNS ad allocation problem, and several components are introduced to realize the optimization formulation. We show the advantages of our new approach in solving the problem compared to the baseline integer programming (IP) formulation. In studying the problem of trust mechanisms in social networks, we consider the existence of distrust (i.e. negative trust) relationships, and differentiate between the concept of local trust and global trust in social network setting. In the problem of local trust inference, we propose a 2-D trust model. Based on the model, we develop a semiring-based trust inference framework. In global trust evaluation, we consider a general setting with conflicting opinions, and propose a consensus-based approach to solve the complex problem in signed trust networks. ADVERTISEMENT ALLOCATION AND TRUST MECHANISMS DESIGN IN SOCIAL NETWORKS
Cardiac Biomarkers in Patients with Acute Pulmonary Embolism

Pulmonary embolism is a frequent and potentially fatal disease. The major challenge of initial management lies in prognostic stratification. Since 2014, the European recommendations on the diagnosis and management of acute pulmonary embolism are based on assessing the risk stratification regarding hemodynamic status first, then on a combined risk assessment model using a clinical score, an imaging evaluation of right heart size and the concentration of a serum cardiac biomarker. Usual biomarkers cover cardiac ischemia (troponin and derivates) and dilatation (BNP and derivates). The aim of this review is to offer a practical update on the role of the Troponins and BNPs families of biomarkers and the prognosis of pulmonary embolism, and furthermore, to provide a brief overview of their place in current management.
Capturing High Rate Satellite Data. An Analysis of Lossless, Persistent Reception, Local Storage and Transmission of High Rate Satellite Data From Time Window Based Datastream

Satellites generate data through their instruments as they hover in orbit. Satellite data is widely used in weather forecasts, environmental science, for military purposes, earth observation and more. The world depend on satellite data, for many purposes. As satellite technology moves forward, the amount of data generated per orbit increases. Satellites are not equipped with unlimited storage capacity, meaning that the generated data must be transmitted to a ground station at some point in orbit. Satellites transmit data through the use of radio waves, and have the later years used X-, S-, L-band, among others. An increase in generated data, require an increase in the transfer rates between the satellite and ground station. Therefore, the satellite industry will, in near future, build satellites using KA-band using a higher frequency area providing larger bandwidth. The increase in generated data forces the increase in data transmission rate, which require high performance ground stations that can capture incoming high rate data. A ground station’s purpose is to capture the received satellite data,without data loss. Until today several capturing systems provide rates between 1 and 3gbps, depending on the band used, modulation, whether near real-time processing is offered or not andwhether data is actually captured and stored within the same chassis[60, 4, 73, 36]. With KA-band, the rates can exceed 10gbps, and it is the industry mission to provide systems that can capture such data rates. This thesis evaluate the next generation technology used to capture data, determining the bottleneck in the setup used today through the analysis tool developed, and further resolving them. The changes suggested in this thesis are tested and evaluated, and show that the next generation servers can capture 10gbps with the hardware and software available, which is higher than any other related system found.
Optical Coherence Tomography Angiography for the Evaluation of Retinal and Choroidal Vasculature in Retinitis Pigmentosa: A Monocentric Experience

Purpose: We investigated the chorioretinal microvascular changes in patients with retinitis pigmentosa (RP) by optical coherence tomography angiography (OCTA). Methods: Twenty-six patients (52 eyes) affected by RP were compared with 19 healthy controls (38 eyes). OCTA 3 mm × 3 mm macular scans were performed in all subjects. We evaluated the vessel density (VD) of the superficial capillary plexus (VD SCP), deep capillary plexus (VD DCP), choriocapillaris (VD CC), and choroid (VD choroid). We also evaluated the foveal avascular zone (FAZ) area, and the correlation between clinical and OCTA parameters. We also measured central retinal thickness (CRT) and subfoveal choroidal thickness (CT). Results: RP patients compared to healthy controls showed significantly lower VD SCP values (27.56% ± 15.37 vs. 49.39% ± 1.55; p-value < 0.0001), lower VD DCP values (38.43% ± 15.23 vs. 3.34% ± 0.26; p-value < 0.0001), lower VD CC values (46.02% ± 1.293 vs. 50.63% ± 0.4274; p-value = 0.0040), and lower VD choroid values (38.48% ± 15.23 vs. 3.34% ± 0.26; p-value < 0.0001). Even the FAZ area was significantly lower in RP patients (0.45 mm2 ± 0.35 vs. 0.26 mm2 ± 0.13; p-value < 0.0001). The FAZ area was larger with increasing age, both in control (r = 0.42; p = 0.012) and RP group (r = 0.46; p-value = 0.009). In RP patients, there was a statistically significant correlation between best-corrected visual acuity and VD SCP (r = 0.24, p-value = 0.04) and VD DCP (r = 0.52; p-value = 0.0004) and between subfoveal choroidal thickness and VD SCP (r = 0.43, p-value < 0.001) and VD DCP (r = 0.35, p-value < 0.001). Conclusions: In our study, OCTA reported relevant vascular alterations in RP patients in comparison with the healthy controls, in agreement with the published literature. These abnormalities were associated with choroidal atrophy and related to visual acuity loss. OCTA provided clinically significant information and may represent a reliable tool for the management of RP patients.
Phytoplankton Toxins and Their Potential Therapeutic Applications: A Journey toward the Quest for Potent Pharmaceuticals

Phytoplankton are prominent organisms that contain numerous bioactive substances and secondary metabolites, including toxins, which can be valuable to pharmaceutical, nutraceutical, and biotechnological industries. Studies on toxins produced by phytoplankton such as cyanobacteria, diatoms, and dinoflagellates have become more prevalent in recent years and have sparked much interest in this field of research. Because of their richness and complexity, they have great potential as medicinal remedies and biological exploratory probes. Unfortunately, such toxins are still at the preclinical and clinical stages of development. Phytoplankton toxins are harmful to other organisms and are hazardous to animals and human health. However, they may be effective as therapeutic pharmacological agents for numerous disorders, including dyslipidemia, obesity, cancer, diabetes, and hypertension. In this review, we have focused on the properties of different toxins produced by phytoplankton, as well as their beneficial effects and potential biomedical applications. The anticancer properties exhibited by phytoplankton toxins are mainly attributed to their apoptotic effects. As a result, phytoplankton toxins are a promising strategy for avoiding postponement or cancer treatment. Moreover, they also displayed promising applications in other ailments and diseases such as Alzheimer’s disease, diabetes, AIDS, fungal, bacterial, schizophrenia, inflammation, allergy, osteoporosis, asthma, and pain. Preclinical and clinical applications of phytoplankton toxins, as well as future directions of their enhanced nano-formulations for improved clinical efficacy, have also been reviewed.
Computationally-efficient finite-element-based thermal and electromagnetic models of electric machines

COMPUTATIONALLY-EFFICIENT FINITE-ELEMENT-BASED THERMAL AND ELECTROMAGNETIC MODELS OF ELECTRIC MACHINES by Kan Zhou Chair: Heath F. Hofmann With the modern trend of transportation electrification, electric machines are a key component of electric/hybrid electric vehicle (EV/HEV) powertrains. It is therefore important that vehicle powertrain-level and system-level designers and control engineers have access to accurate yet computationally-efficient (CE), physicsbased modeling tools of the thermal and electromagnetic (EM) behavior of electric machines. In this dissertation, CE yet accurate thermal and EM models for electric machines, which are suitable for use in vehicle powertrain design, optimization, and control, are developed. This includes not only creating fast and accurate thermal and EM models for specific machine designs, but also the ability to quickly generate and determine the performance of new machine designs through the application of scaling techniques to existing designs. With the developed techniques, the thermal and EM performance can be accurately and efficiently estimated. Furthermore, powertrain or system designers can easily and quickly adjust the characteristics and the performance of the machine in ways that are favorable to the overall vehicle performance.
3D Convolutional Neural Networks for Dendrite Segmentation Using Fine-Tuning and Hyperparameter Optimization

Dendritic microstructures are ubiquitous in nature and are the primary solidification morphologies in metallic materials. Techniques such as x-ray computed tomography (XCT) have provided new insights into dendritic phase transformation phenomena. However, manual identification of dendritic morphologies in microscopy data can be both labor intensive and potentially ambiguous. The analysis of 3D datasets is particularly challenging due to their large sizes (terabytes) and the presence of artifacts scattered within the imaged volumes. In this study, we trained 3D convolutional neural networks (CNNs) to segment 3D datasets. Three CNN architectures were investigated, including a new 3D version of FCDense. We show that using hyperparameter optimization (HPO) and fine-tuning techniques, both 2D and 3D CNN architectures can be trained to outperform the previous state of the art. The 3D U-Net architecture trained in this study produced the best segmentations according to quantitative metrics (pixel-wise accuracy of 99.84% and a boundary displacement error of 0.58 pixels), while 3D FCDense produced the smoothest boundaries and best segmentations according to visual inspection. The trained 3D CNNs are able to segment entire 852 x 852 x 250 voxel 3D volumes in only ~60 seconds, thus hastening the progress towards a deeper understanding of phase transformation phenomena such as dendritic solidification.
Software Risk Identification for Interplanetary Probes

The need for a systematic and effective software risk identification methodology is critical for interplanetary probes that are using increasingly complex and critical software. Several probe failures are examined that suggest more attention and resources need to be dedicated to identifying software risks. The direct causes of these failures can often be traced to systemic problems in all phases of the software engineering process. These failures have lead to the development of a practical methodology to identify risks for interplanetary probes. The proposed methodology is based upon the tailoring of the Software Engineering Institute's (SEI) method of taxonomy-based risk identification. The use of this methodology will ensure a more consistent and complete identification of software risks in these probes.
Design strategy: Towards a post-rational, practice-based perspective

This paper critically reflects on the concept of design strategy as deployed in design management literature. It starts by describing current discourses in the wider field of strategy research and then discusses how, by conforming to orthodox theories in strategic management, design management literature has tended to overlook alternative streams of strategy research. In many instances, studies in design strategy adopt taken-for-granted assumptions from rational planning approaches, and analyses of firm performance tend to take precedence over actors and their actions. Thus, it highlights the need for new lines of inquiry grounded in practice, letting go of the economic rationality and theoretical abstractions that have permeated mainstream strategy research. Hence, for future studies, it suggests a post-rational, practice-based perspective to advance our understanding of strategy as it relates to design management.
Fun for All: Translation and Accessibility Practices in Video Games

Video games have evolved to become a pervasive format which is beyond entertainment, enjoyed by a broad group of people rather than as a niche activity by hardcore gamers. However, to date, academic studies focusing on game localization and accessibility are few and far between, despite the fact that further research in localization and accessibility would be beneficial to all. The different contributions in this pioneering volume address the emerging fields of Game Accessibility and Game Localization from different angles, providing insightful information about these relatively unexplored academic areas with such close tights to the industry. The volume is divided in two sections: the first section includes four contributions on Game Accessibility, dealing with issues such as universally accessible games and guidelines for promoting accessibility. The second section of the book includes nine contributions focussing on different issues affecting game translation and localization, such as case studies, culturalization, fan translation, and terminology management for the game localization industry.
Insights on Shear Transfer Efficiency in “Brick-and-Mortar” Composites Made of 2D Carbon Nanoparticles

Achieving high mechanical performances in nanocomposites reinforced with lamellar fillers has been a great challenge in the last decade. Many efforts have been made to fabricate synthetic materials whose properties resemble those of the reinforcement. To achieve this, special architectures have been considered mimicking existing materials, such as nacre. However, achieving the desired performances is challenging since the mechanical response of the material is influenced by many factors, such as the filler content, the matrix molecular mobility and the compatibility between the two phases. Most importantly, the properties of a macroscopic bulk material strongly depend on the interaction at atomic levels and on their synergetic effect. In particular, the formation of highly-ordered brick-and-mortar structures depends on the interaction forces between the two phases. Consequently, poor mechanical performances of the material are associated with interface issues and low stress transfer from the matrix to the nanoparticles. Therefore, improvement of the interface at the chemical level enhances the mechanical response of the material. The purpose of this review is to give insight into the stress transfer mechanism in high filler content composites reinforced with 2D carbon nanoparticles and to describe the parameters that influence the efficiency of stress transfer and the strategies to improve it.
How to Increase Per-Session Throughput in Distress Hours if Grey Hole attack Is In-Avertible

A Mobile ad hoc network (MANET) is a decentralized type of wireless network. Perhaps the most widespread notion of a mobile ad-hocnetwork is a network formedwithout any central administration whichconsists of mobile nodes that use a wirelessinterface to send packet data. Since the nodesin a network of this kind can serve as routersand hosts, they can forward packets on be-half of other nodes and run user applications.The network is called ad-hoc because it does not rely on anyexisting infrastructure, such as routers in wired networks or access points in wireless networks. In addition to the classic routing, ad hoc networks can use flooding for forwarding data. In this paper, we explore the effect on per session throughput of an ad-hoc network consisting of fixed and mobile non- malicious-nodes, by mobile and fixed malicious nodes called grey hole. To simulate grey attack, 5, 10 and 14 malicious nodes were created for different scenarios. The simulation consists of 50 fixed/mobile non-malicious and 5, 10, 14 malicious nodes. All the simulations are made in same environment.
A prototype system for human-computer interaction logging, post-processing, and data visualization for the Project54 system

Police officers and other emergency responders have been using the Project54 system in their vehicles for many years. Over this time it is likely that certain trends have developed regarding how they use the system to make their daily tasks easier and safer. This thesis examines the use of human-computer interaction logging, post-processing and data visualization techniques to quantify and graphically present how police officers utilize the Project54 system. Specifically, data was retrieved from two deployed police cruisers that identified their use of Project54's speech user interface (SUI) and graphical user interface (GUI), as well as the vehicles' original hardware controllers. That information was then analyzed and five different sets of data visualizations were generated based on the analysis results. The visualizations were reviewed by eight members of the Project54 design team, whose feedback indicated that the visualizations were successful at relaying conclusive results from the quantitative analysis.