Miracle-dz/UniFAR-FTUs huggingface dataset:
A Realistic Evaluation of Universal Water Metering in the United Kingdom's South East

An increasing number of regions in the United Kingdom (UK) are experiencing water shortages. The universal installation of household water meters has been identified as one way to reduce demand on limited supplies. The general consensus among policy- makers and water practitioners is that meters 'work' by providing a financial incentive to residents to use less water. Recent studies however, suggest that mechanisms that drive changes in water-user behaviours are more complex and context-dependent. Using an approach developed in the field of program evaluation, this paper examines policy-maker and water practitioner understandings of how a current universal metering program in the south east of the UK 'works'. These understandings are then compared to how water meters are managed and accepted at a household level. The findings demonstrate how 'Realistic Evaluation' (Pawson & Tilley, 1997) can be used to gain a deeper understanding of how technological interventions 'work' in complex social systems.
THO and TRAMP complexes prevent transcription-replication conflicts, DNA breaks, and CAG repeat contractions

Expansion of structure-forming CAG/CTG repetitive sequences is the cause of several neurodegenerative disorders and deletion of repeats is a potential therapeutic strategy. Transcription-associated mechanisms are known to cause CAG repeat instability. In this study, we discovered that Thp2, an RNA export factor and member of the THO complex, and Trf4, a key component of the TRAMP complex involved in nuclear RNA degradation, are necessary to prevent CAG fragility and repeat contractions in a S. cerevisiae model system. Depletion of both Thp2 and Trf4 proteins causes a highly synergistic increase in CAG repeat fragility, indicating a complementary role of the THO and TRAMP complexes in preventing genome instability. Loss of either Thp2 or Trf4 causes an increase in RNA polymerase stalling at the CAG repeats and genome-wide transcription-replication conflicts (TRCs), implicating impairment of transcription elongation as a cause of CAG fragility and instability in their absence. Analysis of the effect of RNase H1 overexpression on CAG fragility and TRCs suggests that co-transcriptional R-loops are the main cause of CAG fragility in the thp2Δ mutants. In contrast, CAG fragility and TRCs in the trf4Δ mutant can be compensated for by RPA overexpression, suggesting that excess unprocessed RNA in TRAMP4 mutants leads to reduced RPA availability and high levels of TRCs. Our results show the importance of RNA surveillance pathways in preventing RNAPII stalling, TRCs, and DNA breaks, and show that RNA export and RNA decay factors work collaboratively to maintain genome stability.
Time delay control of a shape memory alloy actuator

Shape memory alloy (SMA) actuators have attractive advantages such as high power to volume ratio. However, they also have hard nonlinearities including backlash-like hysteresis and saturation. These nonlinearities result in steady-state errors and limit cycle problems when conventional controllers are used for trajectory control. In this paper, time delay control (TDC) is applied to SMA actuators. The TDC is a well-known robust nonlinear controller and does not require a precise mathematical plant model. The dynamics of an SMA actuator was derived based on Liang's model. This dynamics does not only describe the characteristics of SMA actuators very effectively but also helps tune the TDC gains. A control strategy for the SMA actuator was established and examined from the point of view of the influence of an anti-windup scheme and high gain tuning on the control performance. We also conducted experiments on the position control of the SMA actuator and show the results of the TDC in comparison with other control schemes.
From Static to Dynamic Electric Power Network State Estimation: The Role of Bus Component Dynamics

This thesis addresses the challenge of accurately and robustly estimating the network state on an electric power network despite its large size, infrequent measurement updates, and high likelihood of corrupted data. This is especially important as electrical transmission operators are increasingly being asked to operate the networks at their maximum allowable capacity. Accurate knowledge of the state is necessary to ensure adequate margin to these operating limits should a fault occur. This thesis provides the following contributions. 1. Models describing the dynamics of slow machinery attached to and coupled via the electric power network were used to allow dynamic state estimation. 2. The detail of the coupled dynamic network model was evaluated to determine the level of modeling complexity required to achieve significant state estimation performance gains. 3. Improvements to bad data detection and identification by using information from the dynamic state estimator were demonstrated and evaluated. 4. The improvements to network static observability were discussed and evaluated.
Blind estimation of time and frequency offset for PCC-OFDM

This paper presents blind estimation methods for timing and frequency offset in polynomial cancellation coded orthogonal frequency division multiplexing (PCC-OFDM) systems. The estimations are carried out in the frequency domain. The correct timing point is calculated by maximizing a timing metric and the frequency offset estimate is obtained by using pairs of demodulated subcarriers at the fast Fourier transform (FFT) output. No training symbols, pilot tones or cyclic prefix extensions are required. The methods can also be used in OFDM, however a training symbol is required.
Active control of sound transmission through a stiffened panel using a hybrid control strategy

This article presents active control laws for sound transmission through a stiffened panel in the low-frequency range. A stiffened panel mounted on a metallic box is used to simulate aircraft fuselage and cabin system. A loudspeaker located outside the box is driven by band-limited white noise to exert acoustic excitation. Dynamic properties of the stiffened panel are characterized through a series of modal testing. Sound isolation performance is evaluated both analytically and experimentally for further efficient control algorithms design. Based on the analysis of these results, a hybrid control strategy combining both feedback and feedforward control is proposed, which utilizes a high-authority/low-authority control architecture. The low-authority control loop is positive position feedback control and high-authority control loop is filtered-X control. When positive position feedback is implemented, active damping is added on the secondary path, which makes filtered-X least mean square more robust, accelerates convergence rates, and reduces residue errors. In the end, the effectiveness of the hybrid control is verified through a serious of closed-loop control experiments. These results demonstrate that sound pressure level could be lowered by a maximum of 15.9 dB at the first resonance frequency. In addition, the overall sound reduction in the cabin is more than 7 dB.
Anaerobic Digestion of Agricultural Wastes: A Potential Remedy for Energy Shortfalls in Nigeria

We live in a world where wastes are generated on a daily basis, while some of the wastes are generated on a seasonal basis, such as agricultural wastes. Agricultural wastes are produced seasonally in large quantities and readily available after every post-harvest operation. These wastes have the potential to be converted to useful products which can aid life and increase economy by creating jobs, particularly in Nigeria, but sometimes they are left unused and litter the environment, afterward, causing environmental degradation. These wastes can produce power through anaerobic digestion by the metabolic splitting of matter which is organic in nature into chemical components in the absence of oxygen. The dry anaerobic digestion process is an innovative waste-recycling method to treat high-solid-content bio-wastes. The wastes are passed through hydrolysis, fermentation, acetogenesis and methanogenesis metabolic reactions thereby decomposing them to usable state where they can be used in biogas production. Nigeria has the potential of generating daily 6.8 million m 3 of biogas through animal waste, which will be profitable in eliminating or reduction of waste menace and nuisance of both local and urban waste. Furthermore, the production of biogas from agricultural wastes and biomass in Nigeria would be suitable for various fuel requirements in the household, industrial and agricultural sectors such as in cooking, lighting, water heating, running refrigerators, water pumps at home and in the farms; and electric generators domestically. Industrially, it could be utilized in drying rooms, running of internal combustion engines for shaft power needs and in small-scale industrial operations for direct heating applications such as in scalding tanks.
Investigation of the forces developed when using high-temperature superconductors with linear electric machines

The proposed research of investigating the interaction between high-temperature superconductors and linear motors is introduced. Background on levitated transportation, high-temperature superconductor applications and superconductor theory is given. An analytical model is developed for calculating thrust and levitation forces produced by 3-phase windings on a pair bulk hightemperature superconductors. Results produced by this model for a spacing of 1 pole-pitch and 1 2 pole-pitch are presented. In order to verify the analytical model a prototype system is built from a linear motor primary and vehicles containing 2 rows of superconductors. Two vehicles are built with different spacing between the rows of superconductors in order to investigate the effect of their positioning, with respect to the pole-pitch, on the thrust forces produced. Measured forces on these two vehicles are then compared with predicted values showing that the model predicts the forces with less than 5% error. Problems with the analytical model are also discussed. Finally it is concluded that the model developed provides insight to the relationship between high-temperature superconductors and travelling magnetic waves, and that a 1 pole-pitch separation between superconductors produces higher forces. Recommendations for further development of the prototype system are also given.
Speeded Up Robust Features Based Real Time Hand Gesture Recognition for Indian Sign Language

Development of an automatic sign language recognition system to solve the communication problems of speech and hearing impaired people is challenging task. It is modern part of research in the area of human computer interaction. In this paper, we propose such recognition system for hand gestures of Indian Sign Language (ISL). Based on computer vision and image processing algorithms, the system accurately recognizes gestures from stored images and live camera. The recognized gestures are then converted into text and voice. The system is built using the state of art machine learning model - Bag of Visual Words (BOVW) with Speeded Up Robust Features (SURF) features. Four different classifiers such as K-Nearest Neighbors (KNN), Neural Network (NN), Support Vector Machine (SVM) and Linear Discriminant Analysis (LDA) have been trained. Experiments are carried out on these classifiers with different feature size and results are presented. During experiments it is observed that the system provided invariance with respect to scale, translation and rotation. It achieved recognition rate up to 99.40% using SVM classifier.
Towards Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games

Measuring and promoting policy diversity is critical for solving games with strong non-transitive dynamics where strategic cycles exist, and there is no consistent winner (e.g., Rock-Paper-Scissors). With that in mind, maintaining a pool of diverse policies via open-ended learning is an attractive solution, which can generate auto-curricula to avoid being exploited. However, in conventional open-ended learning algorithms, there are no widely accepted deﬁnitions for diversity, making it hard to construct and evaluate the diverse policies. In this work, we summarize previous concepts of diversity and work towards offering a uniﬁed measure of diversity in multi-agent open-ended learning to include all elements in Markov games, based on both Behavioral Diversity (BD) and Response Diversity (RD) . At the trajectory distribution level, we re-deﬁne BD in the state-action space as the discrepancies of occupancy measures. For the reward dynamics, we propose RD to characterize diversity through the responses of policies when encountering different opponents. We also show that many current diversity measures fall in one of the categories of BD or RD but not both. With this uniﬁed diversity measure, we design the corresponding diversity-promoting objective and population effectivity when seeking the best responses in open-ended learning. We validate our methods in both relatively simple games like matrix game, non-transitive mixture model, and the complex Google Research Football environment. The population found by our methods reveals the lowest exploitability, highest population effectivity in matrix game and non-transitive mixture model, as well as the largest goal difference when interacting with opponents of various levels in Google Research Football .
PUF-based IoT Device Authentication Scheme on IoT Open Platform

Recently, it is predicted that interworking between heterogeneous devices will be accelerated due to the openness of the IoT (Internet of Things) platform, but various security threats are also expected to increase. However, most IoT open platforms remain at the level that utilizes existing security technologies. Therefore, a more secure security technology is required to prevent illegal copying and leakage of important data through stealing, theft, and hacking of IoT devices. In addition, a technique capable of ensuring interoperability with existing standard technologies is required. This paper proposes an IoT device authentication method based on PUF (Physical Unclonable Function) that operates on an IoT open platform. By utilizing PUF technology, the proposed method can effectively respond to the threat of exposure of the authentication key of the existing IoT open platform. Above all, the proposed method can contribute to compatibility and interoperability with existing technologies by providing a device authentication method that can be effectively applied to the OCF Iotivity standard specification, which is a representative IoT open platform.
SOFTWARE-DEFINED RESOURCE MANAGEMENT FOR INDUSTRIAL INTERNET OF THINGS

The Industrial Internet of Things (IIoT) and Industry 4.0 aim to streamline production processes and keep manufacturing viable and profitable. This presents enterprises with the opportunity to boost productivity while improving efficiency and safety and reducing costs. With heightened interest from both researchers and industry experts, IIoT has witnessed remarkable advances over the recent years thanks to developments in related technologies such as Industrial Wireless Networks (IWNs), Software-Defined Networking (SDN), cloud computing, and Multi Access Edge Computing (MEC). Despite the proven ability of these technologies to advance the course of IIoT and Industry 4.0, an equally important but less investigated problem is ensuring that the resources upon which these technologies depend are optimally allocated and efficiently utilized. This doctoral dissertation proposes a software-defined approach towards improving resource management and efficiency in IIoT systems. First, an SDN-based data offloading scheme is designed to coordinate data offloading for IIoT applications. This will enable constrained IIoT devices to relay their more demanding operations for energy and resource optimization. Second, a system model is developed to leverage the synergy between SDN, MEC, and containerization technologies in advancing IIoT applications for better resource management, more specifically for containerized edge microservices. Third, a novel SDN-enabled Resource Management (SDRM) scheme is developed based on Satisfiability Modulo Theory (SMT) constraint programming. With this scheme, SDRM will be able to automatically compute the optimal resource allocation for different IIoT network models and dynamically adjust assigned resources based on predefined constraints to ensure Service Level Agreements (SLAs). Lastly, the effects of collaborative edgecloud computing for such SDN-based IIoT implementations are examined. The results from our implementation models demonstrate the feasibility, efficiency, and performance improvements of utilizing SDN-based solutions for resource optimization in IIoT implementations. Hence, the outcome of this dissertation will help both researchers and system designers gravitate towards more resource-efficient IIoT solutions.
Progress in practical prediction of pressure: leakage, pressure: burst frequency and pressure: consumption relationships

Substantial advances have been made in the last decade in the development of practical methods for understanding and predicting how leakage rates and burst frequencies in distribution systems, and some elements of consumption, are influenced by pressure. Members of the Pressure Management Team of the Water Losses Task Force continue to try to improve the practical methods available for analysis and prediction. The combination of existing and new material is presented under four principal topic headings: • Predicting pressure: leakage rate relationships using Power Law exponents • Extending the range of operating pressures for the UARL formula • New information on pressure: consumption relationships • Pressure: new burst frequency relationships The paper concludes with a brief listing of some practical research topics that could usefully be pursued, and explains that, by using software specifically designed for pressure management, practical predictions can usually be made rapidly without the need for network analysis models.
Using augmented reality for early literacy

Currently, augmented reality is one of the most actively developing technologies, which has also found its application in the field of education. Analysis of various publications has confirmed that AR technology opens up new opportunities for teachers and increases the attractiveness of learning for students of different ages. Mobile AR apps allow the student to see a real-world environment with overlaid or composite virtual objects. This is especially true for young children. The article identifies the activities that provide a child’s personal experience using AR technology. Comparison of existing AR applications for learning the alphabet is given. A new AR application is described, which was developed using Unity, C#, Vuforia. The developed mobile AR application provides an opportunity to study the Ukrainian alphabet, the names of numbers, the sounds of animals. Thanks to this application, the learning process is accompanied by three-dimensional visualization and sounding of each letter and number. An analysis of a survey of teachers and parents showed that when using an AR application, the interest and self-efficacy of children in learning letters and numbers significantly increased. The use of the AR application increased the speed of memorizing the material and helped to retain the child’s attention while learning a new material.
Power system stability enhancement using a new combinational load-shedding algorithm

In the recent years, operation of power systems at lower stability margins has increased the importance of system protection methods that protect the system stability against various disturbances. Among these methods, the load shedding serves as an effective and last-resort tool to prevent system frequency/voltage instability. For major combinational disturbances, the active power deficit is usually accompanied by reactive power deficit. Therefore frequency stability and voltage stability of the system are jeopardised simultaneously. For such cases, the conventional non-adaptive underfrequency load-shedding scheme cannot offer adequate protection to prevent system collapse. In this study a new combinational load shedding method is proposed to increase the security of power system during large disturbances. The proposed method uses locally measured frequency and voltage signals and does not need any communication link. Performance of the conventional scheme and the proposed load-shedding method using different load shedding criterions have been simulated in two test systems: an actual large network and a standard test system. Obtained simulation results confirm that the proposed schemes provide considerable enhancement in the power system voltage stability margin and by using the proposed method various power system blackouts could be prevented.
Blood-Brain Barrier Overview: Structural and Functional Correlation

The blood-brain barrier (BBB) is a semipermeable and extremely selective system in the central nervous system of most vertebrates, that separates blood from the brain's extracellular fluid. It plays a vital role in regulating the transport of necessary materials for brain function, furthermore, protecting it from foreign substances in the blood that could damage it. In this review, we searched in Google Scholar, Pubmed, Web of Science, and Saudi Digital Library for the various cells and components that support the development and function of this barrier, as well as the different pathways to transport the various molecules between blood and the brain. We also discussed the aspects that lead to BBB dysfunction and its neuropathological consequences, with the identification of some of the most important biomarkers that might be used as a biomarker to predict the BBB disturbances. This comprehensive overview of BBB will pave the way for future studies to focus on developing more specific targeting systems in material delivery as a future approach that assists in combinatorial therapy or nanotherapy to destroy or modify this barrier in pathological conditions such as brain tumors and brain stem cell carcinomas.
Effect of curvature on characteristics of rectangular patch antenna

The effect of curvature on the characteristics of a rectangular patch antenna is studied theoretically and experimentally. For the TM01 mode it is found that the resonant frequency is not affected by curvature. However, as curvature increases the pattern broadens, the resonant resistance decreases, the Q-factor is smaller and the bandwidth is larger. Good agreement between theory and experiment is obtained.
Investigating Collaborative Behaviors on Interactive Tabletop Displays in Complex Task Environments

A two-player, collaborative digital tabletop testbed has been developed in order to study collaborative behaviors of human operators in complex task environments such as Air Traffic Control. The game provides a means of examining interaction techniques designed to foster collaboration, and support natural communication strategies between operators in these complex environments. This paper describes key requirements for the testbed and how those requirements were met in a first version of the testbed. Finally, lessons learned from initial evaluations of its application to studying handoffs and coordination between players on an interactive tabletop display in a simulated ATC environment is presented.