Miracle-dz/UniFAR-FTUs huggingface dataset:
Achieving Reliable and Sustainable Next-Generation Memories

Conventional memory technology scaling has introduced reliability challenges due to dysfunctional, improperly formed cells and crosstalk from increased cell proximity. Furthermore, as the manufacturing effort becomes increasingly complex due to these deeply scaled technologies, holistic sustainability is negatively impacted. The development of new memory technologies can help overcome the capacitor scaling limitations of DRAM. However, these technologies have their own reliability concerns, such as limited write endurance in the case of Phase Change Memories (PCM). Moreover, emerging system requirements, such as in-memory encryption to protect sensitive or private data and operation in harsh environments create additional challenges that must be addressed in the context of reliability and sustainability. This dissertation provides new multifactor and ultimately unified solutions to address many of these concerns in the same system. In particular, my contributions toward mitigating these issues are as follows. I present GreenChip and GreenAsic, which together provide the first tools to holistically evaluate new computer architecture, chip, and memory design concepts for sustainability. These tools provide detailed estimates of manufacturing and operational-phase metrics for different computing workloads and deployment scenarios. Using GreenChip, I examined existing DRAM reliability techniques in the context of their holistic sustainability impact, including my own technique to mitigate bitline crosstalk. For PCM, I provided a new reliability technique with no additional storage overhead that substantially increases the lifetime of an encrypted memory system. To provide bit-level error correction, I developed compact linked-list and Bloom-filter-based bit-level fault map structures, that provide unprecedented levels of error tabulation, combined with my own novel error correction and lifetime extension approaches based on these maps for less area than traditional ECC. In particular, FaME, can correct N faults using N bits when utilizing a bit-level fault map. For operation in harsh environments, I created a triple modular redundancy (TMR) pointer-based fault map, HOTH, which specifically protects cells shown to be weak to radiation. Finally, to combine the analyses of holistic sustainability and memory lifetime, I created the LARS technique, which adjusts the GreenChip indifference analysis to account for the additional sustainability benefit provided by increased reliability and lifetime.
Improving the information transfer between engineering and installation; case study at AS Nymo

Engineering, Procurement, Construction and Installation (EPCI) projects for the offshore oil and gas industry become more and more complex, with a reduced timeframe, and increased demand for cost savings in the industry. The result is reduced profit margins; therefore, the need for increased productivity is higher than ever. Some of the aspects important for productivity include material flow, information flow, sound planning, and organizational structure. This paper focuses on the information transfer between the engineering team and the installation phase of the fabrication at AS Nymo. Feedback from stakeholders, previous research and lessons learned from completed projects pinpoints that this handover has a potential for improvement. We analyzed historical data and involved key stakeholders in an iterative process to identify insignificant elements in the handover format. By removing this insignificant information, we found that it is possible to reduce the number of handover revisions by 60%. Additionally, we found that improving the handover could give a 67% reduction in time spent for the receiving stakeholders to find the specific information they seek. To verify our results, we suggest further testing for verification before validation through a full‐scale project execution testing for future research.
Qualitative assays and quantitative determinations of xylanolytic enzymes of wood rot fungi from Dagaga and Gambo forests, Ethiopia

Xylan is a second widely available polysaccharide in nature and can be enzymatically degraded for the production of sugars. The complete biodegradation of xylan needs synergistic action of different xylanolytic enzymes. In this research, potential xylanolytic activities of the wood rot basidiomycete fungi from Dagaga and Gambo forests were screened. Xylanases of the potential fungi were also quantitatively determined. Clear zones round the cultures on xylan supplemented agar media of isolate 011-1D (Trametes gibbosa) and 030-1D (Phellinus tremulae) were significantly wider than other isolates. The fungal isolates differently responded to the incubation days both in submerged and solid-state fermentations and most isolates gave higher xylanase yield in solid-state fermentation than in submerged fermentation. The enzymes were active and stable in the temperature range of 40 to 55oC and pH range of 4.0 to 6.0. Incubation temperature of 30 to 35oC and pH of 5.0 to 7.0 were found to be suitable for production of the xylanases from the fungal isolates. Among the supplemented carbon sources, carboxymethylcellulose, xylan and sucrose were found suitable for xylanase productions but most isolates differently responded to the nitrogen source supplementations. MgSO4, ZnSO4 and CaCl2 were also found to be suitable divalent metallic ions for the productions of the enzymes. The isolates could be used for hydrolysis lignocellulosic xylan to 5-carbon sugars by optimizing their growth conditions.
Detecting cyber-physical threats against autonomous robotic systems in routine missions

Autonomous cyber physical systems are increasingly common in a wide variety of application domains, with a correspondingly wide range of functionalities and types of sensing and actuation. At the same time, the variety and frequency of cyber attacks is increasing in correspondence with the increasing popularity and functionality of these systems, from in-vehicle driver assistance to smart city infrastructure and robotics. These technologies rely on a variety of sensors, actuating nodes and control communications. Each sensor adds context by which the autonomous system can better understand its environment, but each sensor also provides opportunities for attack, as has been observed in a variety of attacks on different systems. Cyber-physical threats are increasing significantly because society is increasingly dependent on cyber-physical and Internet of things systems and devices. Cyber-physical attacks are executed by people with different motivations, intentional or not. A robotic vehicle testbed has been built and used as a testbed to develop a methodology that is capable of identifying possible threats and their causes. The design of the robotic vehicle testbed is documented with explanations in terms of its sensors, actuators and it operates. A key goal has been to develop a methodology that can automatically characterise the behaviour of the robotic testbed and be able to identify cyber-physical threats in a real-world environment. This testbed environment has met all the requirements for the experimental scenarios that we have identified. A model to observe signal characteristics, including noise level patterns on sensor data streams and incorporating this information to characterise normal or abnormal behaviour of a robotic vehicle is introduced. Following a learning phase, where the vehicle is trained in a non-attack state on the values that are considered normal, it is then subjected to a series of different cyber attacks that have physical impact (cyber-physical attacks) and physical attacks that have cyber impact (physical-cyber attacks). The problem has been approached as a binary classification problem as to whether the robot is able to self-detect if and when it is under attack. The experimental results show that the approach is promising for most attacks that the vehicle is subjected to.
Protein Adsorption on Metal Oxide Nanoparticle Surfaces: Effects of Various Influences on Protein-Surface Interactions and Protein Structure

Author(s): Xu, Zhenzhu | Advisor(s): Grassian, Vicki H | Abstract: With the development of nanoscience and nanotechnology, the biocompatibility of nanomaterials is becoming increasingly important. As one of the most prevalent nanomaterials, metal oxide nanoparticles in particular are receiving growing attention due to their potential negative impacts to the environmental and human health upon exposure. Nanoparticles, once introduced in biological fluids, can adsorb proteins forming protein corona, which can cause protein conformational change and function loss. Although many studies have been focusing on the above effects, details of protein interaction with nanoparticles and consequential structural change on nanoparticle surfaces still remain unclear as these processes can be affected by various factors. Therefore, a systematic study on the impacts of influential factors on the behavior of proteins at the nano-bio interface is strongly desired. The research in the present dissertation pursues a greater understanding of the effects of various parameters on the protein-nanoparticle surface interactions and protein structural change upon adsorption. Specifically, nanoparticle- and environmental-related factors including nanoparticle surface chemistry, pH, co-adsorption of phosphate, and temperature were explored. Spectroscopic and thermogravimetric analysis of bovine serum albumin (BSA) adsorption on TiO2 and SiO2 nanoparticles as a function of pH highlighted the importance of both pH and nanoparticle surface chemistry on protein behavior at nano-bio interfaces. The study shows that protein interaction is strongest on TiO2 surface. Especially, at acidic pH, BSA is completely denatured on TiO2 and protein surface coverage was a factor of three to ten times higher than on SiO2. Detailed secondary structural analysis of BSA adsorption with and without the presence of phosphate indicates that the co-adsorption of phosphate could prevent surface-induced denaturation at very acidic conditions. Furthermore, the effects of surface adsorption on temperature-dependent conformational change of BSA and fibrinogen (Fib) on TiO2 nanoparticles was investigated. Adsorbed BSA exhibits much less change in its secondary structure with increasing temperature than its solution phase, whereas Fib in dissolved and adsorbed states display very similar trend in their structural change as a function of temperature. Moreover, to complement our understanding of protein adsorption on nanoparticles, hydrogen/deuterium exchange mass spectrometry was carried out as a novel method to investigate the role of specific amino acid residues in protein-surface interaction.Thus, the research in this dissertation provide important insights into understanding the behavior of proteins at the nano-bio interface, specifically the effects of various influences on protein-surface interaction and protein structure.
Response of watermelon cultivated under different levels of water and nitrogen

The effect of four irrigation levels (50; 75; 100 and 150% of the evaporation in the class A pan) and four levels of N (0,075; 0,150; 0,225 and 0,300 kg -1 ), were evaluated on productivity and components of production of the watermelon 'Charleston Gray'. The experiment was conducted under fi eld conditions, from October/2003 to January/2004, using a randomized split-plot design, with the factor depths in plot and depths of N in split-plot. It was verifi ed that the factors water and nitrogen presented a highly signifi cant effect in the yield of watermelon, while the interaction among the factors was not signifi cant. The maximum productivity of the watermelon (68.59 Mg ha -1 ) was obtained with 421 mm of water and 267 kg ha -1 of N. The water was more effi ciently used with increments in dosage of N, being the maximum value observed of 279.54 kg ha -1 mm -1 , obtained with a depth of water of 205 mm and a depths of N of 225 kg ha -1 . The maximum effi ciency of the use of the water for the nitrogen was 221 kg ha -1 mm -1 , for 249 kg ha -1 of N. The sugar content of the watermelon, measured in degrees
Dusted animal food

Dusted pet food kibble, as well as supplying a pet food kibble in the form of a core matrix and powder containing a first ingredient that can contain active ingredients such as probiotic microbial particles A method for dusting a pet food kibble, comprising: dusting a powder onto a pet food kibble to form a kibble. The dusting may be substantially free of binder. Animal feed containing kibbles in the form of cores dusted with active ingredients.
Measurement of L X-ray production cross sections and relative intensities of some lanthanide compounds depending on the temperature

Abstract L X-ray intensity ratios for CeO2, Sm2(SO4)3, Ho2O3, and Yb2O3 compounds were experimentally investigated. The measurements were gauged following excitation by 59.54 keV γ-rays from a 100 mCi 241Am radioactive annular source at different temperatures in situ. Temperature change occurred between 50 °C and 400 °C. L X-ray emission spectra were obtained by using a solid-state Si(Li) X-ray detector. L X-ray production cross sections, intensity ratios, and full-width half maximum (FWHM) values for the compounds were determined by evaluating the emission spectra varying with the temperature. According to the results obtained, it was observed that Lβ1 X-rays were less influenced in comparison with Lα X-rays while Lα X-rays were also less influenced in comparison with Lβ2 X-rays.
A Novel Edge-Cloud Interworking Framework in the Video Analytics of the Internet of Things

This letter proposes a novel edge-cloud interworking framework in the video analytics of the Internet of Things (IoT) that consists of cost-effective job load balancing and scheduling schemes for computation-intensive video analytics applications. The proposed framework aims to minimize the cost of cloud resource usage while guaranteeing deadlines when conducting concurrent operations. A formulation of a two-stage mixed-integer problem and its heuristic greedy algorithms is presented, which captures all intertwined goals. From the numerical analysis, we reveal that the proposed framework outperforms the existing schemes in terms of monetary cost and service latency with a practical complexity bound.
An Overview of the Development of Mobile Wireless Communication Technologies

Mobile wireless technologies have followed different evolutionary (generation) paths aimed at unified target related to the performance and efficiency in high mobile environment, which provides access to wide range of telecommunication services including advanced mobile services supported by mobile and fixed networks. This paper illustrate the developments of the mobile wireless communication, focus on the specification and capability for each technology to make an idea about the future technology what will offer.
Predicting Relative Forecasting Performance: An Empirical Investigation

Abstract The relative performances of forecasting models change over time. This empirical observation raises two questions. First, is the relative performance itself predictable? Second, if so, can it be exploited in order to improve the forecast accuracy? We address these questions by evaluating the predictive abilities of a wide range of economic variables for two key US macroeconomic aggregates, namely industrial production and inflation, relative to simple benchmarks. We find that business cycle indicators, financial conditions, uncertainty and measures of past relative performances are generally useful for explaining the models’ relative forecasting performances. In addition, we conduct a pseudo-real-time forecasting exercise, where we use the information about the conditional performance for model selection and model averaging. The newly proposed strategies deliver sizable improvements over competitive benchmark models and commonly-used combination schemes. The gains are larger when model selection and averaging are based on both financial conditions and past performances measured at the forecast origin date.
Exercise Training Enhances Expression of Tropomedulin-2 and ADP-Ribosylation Factor 6 in the Cerebellum of Male Wistar Rats

Background: It has been well documented that exercise training (ET) induces beneﬁcial eﬀects on the central nervous system (CNS);however,theunderlyingmechanismsarelessknown. WepresumedthatactincytoskeletonregulatoryproteinssuchasADP-ribosylation factors 6 (ARF6) and tropomodulin 2 (TMOD2) may be important elements of Exercise-Induced Neuroplasticity (EIN). We evaluated this hypothesis in the present study. Methods: We randomly divided 12 male Wistar rats into control (C) and training (T) groups. The T group was exposed to six weeks of moderate-intensity treadmill running. The ARF6 and TMOD2 gene and protein expressions in the cerebellum of male Wistar rats were assessed by the real-time PCR and western blot analysis. Results: The results showed that TMOD2 and ARF6 gene and protein expressions were signiﬁcantly higher in the T group than in the C group. Conclusions: It seems that chronic treadmill running increases TMOD2 and ARF6 gene and protein expressions in the cerebellum and these changes probably lead to the improvement of brain function.
Modeling and Analysis of Multi-Tier Clustered Millimeter-Wave Cellular Networks With User Classification for Large-Scale Hotspot Area

This paper focuses on a comprehensive framework design and performance analysis for a large-scale hotspot communication scenario where there exist large number of clustered pico base stations (P-BSs) and femto BSs (F-BSs) working on millimeter-Wave (mm-Wave). For such realistic hotspots’ deployment, to exploit the coupling between user equipments (UEs) and base stations (BSs), we model the geographical centers of UE hotspots as independent PPP around which UEs, P-BSs and F-BSs are scattered and form independent and non-homogeneous Poisson cluster processes (PCPs). However, with clustered P-BSs and F-BSs, the UEs would experience the severer intra-cluster interference so that the performance is degraded greatly. To overcome this problem in clustered networks, an effective interference management scheme is proposed by using the ratio of the first and second nearest distances of a typical UE from P-BSs so that a typical UE can be classified as either cluster-center UEs (CCUEs) or cluster-edge UEs (CEUEs). Correspondingly, the total available spectrum band is divided as CCUE-band and CEUE-band, which are occupied by P-BSs associated with CCUEs and CEUEs, respectively. Unlike P-BSs, the F-BSs randomly access the CEUE-band and CCUE-band with a given access portion factor. By using the method from stochastic geometry and the distinguishing feature of mm-Wave, such as directional beamforming with sectored antenna model and modified line of sight ball model for blockage, the UE association probability and Laplace transforms of interference are derived. This yields the derivations of downlink transmission rates. The numerical results show that the proposed clustered heterogeneous scheme with the cluster-UE classification outperforms the traditional ones without the UE classification. This approach not only captures the UE-BS coupling and the non-homogeneous nature of multi-tier networks, but also restricts the severe intra-cluster interference due to clustered BSs.
Ramjet Compression System for a Hypersonic Air Transportation Vehicle Combined Cycle Engine

This report assesses the performance characteristics of a ramjet compression system in the application of a hypersonic vehicle. The vehicle is required to be self-powered and perform a complete flight profile using a combination of turbojet, ramjet and scramjet propulsion systems. The ramjet has been designed to operate between Mach 2.5 to Mach 5 conditions, allowing for start-up of the scramjet engine. Multiple designs, including varying ramp configurations and turbo-ramjet combinations, were investigated to evaluate their merits and limitations. Challenges arose with attempting to maintain sufficient pressure recoveries and favourable flow characteristics into the ramjet combustor. The results provide an engine inlet design capable of propelling the vehicle between the turbojet and scramjet phase of flight, allowing for the completion of its mission profile. Compromises in the design, however, had to be made in order to allow for optimisation of other propulsion systems including the scramjet nozzle and aerodynamics of the vehicle; it was concluded that these compromises were justified as the vehicle uses the ramjet engine for a minority of the flight profile as it transitions between low supersonic to hypersonic conditions.
Metabolism of oligodendrocytes and its involvement in axo‐glia interaction

In white matter, axonal energy homeostasis critically depends on glial support. Failure in glial-mediated delivery of metabolic substrates into the axonal compartment results in axonal energy deficit and may anticipate axonal degeneration observed in myelin disorders and several neurodegenerative diseases. In mice, transgenic expression of an ATP-sensor in neurons allowed us to visualize axonal energy content in acutely isolated optic nerves while simultaneously performing electrophysiological compound action potentials (CAP) recordings. The real-time monitoring of activity-dependent axonal ATP revealed a strong correlation between axonal energy fluctuations and nerve conduction. Importantly, upon pharmacological inhibition of endogenous lactate metabolism while under continuous glucose supply, ATP-CAP correlation was disrupted, suggesting that the axonal glycolysis products alone were insufficient to maintain axonal mitochondrial energy metabolism during spiking activity. To determine possible metabolic consequences of myelin defects we monitored ATP and CAP in Plp1-null optic nerves. Genetic ablation of Plp1, encoding a myelin membrane protein, serves as a model of spastic paraplegia type-2, where functional but structurally destabilized myelin sheaths lead to secondary axonal loss. We found that the energy metabolism of myelinated axons of Plp1-null optic nerves is perturbed long before the onset of clinical symptoms and major pathological changes. These observations motivated us to assess the metabolic properties of spinal cord fibres in vivo to allow long-term studies involving demyelination and remyelination models. The parallel monitoring of axonal ATP and CAP is a powerful tool to study white matter metabolism and metabolic support mechanisms under physiological conditions and in models of neurodegenerative disorders.
Assessing the digital competence of educators in social studies: An analysis in initial teacher training using the TPACK-21 model

Fostering the digital competence of educators is a key aspect that can be addressed in initial teacher training. The TPACK model (Mishra & Koehler, 2006) can be complemented with an approach that takes the Digital Competence of Educators framework (Redecker & Punie, 2017) and 21st century competences into account. This study analysed the practical utility of this conceptual model, and the effectiveness of a teaching intervention in a university setting, during two academic years, with social studies secondary education prospective teachers. Using a quantitative approach and the TPACK-21 questionnaire (Valtonen et al., 2017), the study examined the starting point and evolution of the participants. Results indicate the adequacy of the framework and instrument used and favourable progress towards competence after the assessment of seven factors. Although pre-service teachers showed a low degree of confidence regarding their capabilities of integrating technological with pedagogical and content knowledge, especially in three of the components, this obstacle was overcome after the intervention. It is possible to conclude that the pedagogical and conceptual orientation of the teaching proposal has shown a positive effect, evidencing the effectiveness of a comprehensive approach capable of adapting to the specificity and challenges of social studies education.