Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on digital governance in urban sustainable development

At present, the wave of digitalization represented by the new generation of information technologies such as Internet, cloud computing, big data, AI and IoT has swept the world, and networking, informationization, digitalization and intelligence have become the main direction of global development in the information age. Digital governance of cities is similar to smart cities. Solving public problems is the most direct pursuit, which requires complete and rapid solutions, as is the core of the government. In this paper, the methods of literature analysiss, empirical research, comparative research and social investigation are used to study the digital governance in the sustainable development of China. This paper evaluates and classifies digital governance in various regions of China from the perspective of quantitative demonstration. Through the analysis of the maturity of digital governance, the development of digital cities is found to be very uneven, and there are advantages and disadvantages in the development of polarized areas in the southeast coastal area, northwest area and central area. The results of maturity analysis of digital governance provide an important basic concept support for the establishment of governance model, which eliminates blindness and has rules to follow, and improves the quality, construction success rate and cycle of digital cities.
Research on sustainable development pathway of sharing economy

Sharing economy is a new form of economic organization that has emerged in recent years. As a new form of business under the internet model in China, sharing economy has made important contributions in boosting supply-side structural reform, resolving the problem of overcapacity and protecting the ecological environment, also the transformation and development of China's economy is guiding to a higher quality, more efficient, fairer and more sustainable by sharing economy. In order to achieve the goal of “double carbon”, China is actively developing the sharing economy, and the development trend is better, but it also faces some problems. Therefore, it is necessary to correctly understand the factors of affecting the sustainable development of the sharing economy such as the defects of the trust mechanism and the disorderly competition of enterprises, that a standardized trust mechanism should be established, the legal supervision system should be improved, orderly competition of enterprises should be advocated, which will be promoted for the sustainable development of the sharing economy.
Establishment of equivalent model of motor shell and analysis of its acoustic radiation characteristics

The motor shell is the main structure of the electric vehicle driving motor radiating noise to the outside. To reduce the noise with a definite aim, it is necessary to study the acoustic radiation characteristics of the motor shell. However, due to the geometric structure of the motor shell, such as stiffeners and irregular sections, it is difficult to solve the radiated noise by analytical method, while the modeling by finite element method and boundary element method is difficult to promote. Therefore, it is necessary to discuss the regular equivalent model of motor shell. Firstly, according to the solid structure of the motor shell, the weighted thickness and the thickness parameters of different weight coefficients are calculated by using the weighted average method, and the equivalent model of the cylindrical shell with different thickness is obtained. Then, by comparing and analyzing the acoustic radiation characteristics, the equivalent cylindrical shell model which is consistent with the modal parameters of the motor shell is determined. Finally, the feasibility of the equivalent model is verified by experiments. The experimental results show that the difference between the root mean square value of sound pressure level of the equivalent cylindrical shell model and the motor shell at 200~1000Hz is less than 5%, and the sound radiation characteristics are highly consistent. The research results provide some reference basis for the prediction of acoustic radiation and noise reduction optimization of motor shell parts.
Research on power system de-carbonization technology based on carbon flow analysis

In recent years, many explorations have been made in carbon reduction, but in order to further avoid ineffective energy resource waste and carbon emissions, sustained efforts from multiple channels are needed Niu Guimin introduced that the rigid construction demand of urban development may bring significant pressure to the total carbon control of buildings. In addition, there is also pressure to improve the energy-saving, carbon reduction, and renovation of existing buildings. "We should make concerted efforts from the aspects of strict control at the source, incremental greening, stock greening, and strict prevention at the end to realize the development of ultra-low energy consumption buildings and Prefabricated building in the direction of standardization, scale, and serialization. Not long ago, the 14th Five Year Plan for Energy Conservation in Tianjin was issued and implemented. It is estimated that by 2025, the energy consumption of Tianjin's 10000 yuan Gross regional product will be 14.5% lower than that of 2020. During the 14th Five Year Plan period, the proportion of green building areas in newly built urban buildings in the city reached 100%, and the proportion of green travel in the central urban area reached 75%. During the 14th Five Year Plan period, Tianjin implemented ten key projects, conscientiously implemented the dual control system for energy consumption, promoted energy conservation and consumption reduction, promoted high-quality development, and helped achieve carbon peak and carbon neutrality, "said the relevant person in charge of the Tianjin Development and Reform Commission.
Comparative study on the stability of small wave buoy

The small wave buoy is a kind of buoy which can observe the wave and wave direction for a long time. It is worth studying which form of standard structure is more stable in waves. In this paper, two kinds of common small wave buoys, cylindrical and spherical, are compared and analyzed. The stability of the two by using Inventor 3D modeling software and Maxsurf stability analysis software, it is found that the spherical buoy has higher stability and better wave-following performance, which provides a basis for subsequent structural design and theoretical research.
Study on rapid ecological restoration of mechanized construction of power grid construction projects

Because certain environmental problems will appear in the process of urban power grid construction, this paper believes that these environmental problems should be solved from the source of planning and specific construction schemes. It is the best way to solve the environmental problems of the abandoned land by renewing and transforming the abandoned land of power grid construction projects through landscape design. Based on the reality and the current situation of urban power grid construction in China, this paper comprehensively evaluates and analyzes the impact of power transmission and transformation projects on the environment, and puts forward the countermeasures for rapid ecological restoration of mechanized construction of power grid construction projects. Through the practice of ecological restoration in power grid construction project area, the soil in power grid construction project area was jointly restored by sludge+topsoil conversion+vegetation planting, and the ecology of power grid construction project area was restored. The adaptability of plants is the basis of practical application of soil bioengineering, which provides some support for the future ecological restoration of rivers in power grid construction project areas.
Influence of Growth Regulators Combined with Chemicals to Improve PostharvestFruit Quality in Banana cv. Nendran (Musa AAB)

A study was undertaken at TNAU, Coimbatore to envisage the effect of different chemicals and growth regulators in combination with Thiabendazole (Fungicide) on post-harvest quality and shelf life of banana cv. Nendran (French Plantain Musa AAB). Various concentration of, GA3, BA, CaCl2 and Hot water treatment either alone or in combination with Thiabendazole was applied to fruits after harvest to study their impact on post-harvest quality and shelf life. Exogenous application of chemicals, growth regulators in combination with Thiabendazole significantly decreased post-harvest disease incidence leading to increase in post- harvest fruit quality and shelf life. Among the treatments, post-harvest dipping of fruits in 150 ppm GA3 + 200 ppm Thiabendazole significantly increased firmness (3.70 kg/cm2) titrable acidity (0.09%) and storage life of fruits (18.00 days). While the parameters like PLW (13.53%), TSS (25.45oB), total sugars (18.88%), reducing sugars (17.11%) and percent disease incidence (5.55) was observed minimum in the same treatment after 12th day of storage.
The classroom implementation of indigenous knowledge in the science curriculum by science teachers in the Western Cape province, South Africa

iv ACKNOWLEDGEMENTS. vii LIST OF ABREVIATIONS. ix LIST OF TABLES. x LIST OF FIGURES. xi CHAPTER 1: GENERAL INTRODUCTION 1.1 Background and rationale. 1 1.2 Problem statement. 7 1.3 Aims and objectives. 8 1.4 Significance of the study. 9 1.5 Clarification of terms. 10 1.6 Context of the study. 11 1.6. 1 Cultural relevance of the new curriculum. 12 1.7 Overview of the thesis. 14 CHAPTER 2: LITERATURE REVIEW 2.
A VeReMi-based Dataset for Predicting the Effect of Attacks in VANETs

Vehicular Ad Hoc Networks (VANETs) have received considerable attention because of their potential to improve road safety. However, reactive security approaches in VANETs are of concern; thus, proactive security is needed to prevent cyberattacks. The current VANET datasets are limited in their ability to evaluate proactive security approaches, limiting research in this area. This paper presents a VeReMi-based dataset named VeReMi for Attack Prediction (VeReMiAP). Developed from the Framework For Misbehavior Detection (F2MD). VeReMiAP incorporates three key elements: Cooperative Awareness Messages (CAMs), a new class of attacks known as Fake Reporting Attacks, and an evaluation of the impact of this attack, which in this case manifests as a road hazard. The ripple effect of this attack goes beyond the targeted vehicle, making it a threat to the overall security and reliability of VANETs. The VeReMiAP dataset evaluates cyberattack prediction techniques and generates countermeasure solutions for VANET attacks. To test the dataset, we conducted a temporal analysis to observe the effect of the attack on velocity and a geospatial analysis to enhance our understanding of the spatial distribution of hazards within the road network. Results show that VeReMiAP is a potential tool to advance security research in VANETs.
Federated Learning for V2X Misbehavior Detection System in 5G Edge Networks

The emergence of 5G Cellular Vehicle-to-Everything (C-V2X) has made it the predominant technology for enabling Vehicle-to-Everything (V2X) communications. As a result, this has created an opportunity for telecommunications service providers to leverage their pre-existing 5G network infrastructure, enabling them to provide Vehicle-to-Network (V2N) services. In this paper, we propose a new approach that enhances the security of 5G V2N services through the implementation of a Federated Learning V2X misbehavior detection system within the 5G core network. The proposed system aims to protect V2X application servers (V2X ASs) that are located in 5G edge networks against potential V2X attacks while leveraging the privacy and scalability advantages of Federated Learning. Our proposed model is compared, using extensive emulations, to other centralized and distributed approaches, achieving excellent results, which makes it feasible for deployment. Our proposal achieved a notable accuracy of 98.4%, while scoring an impressive 99.3% precision and 96.9% detection rate.
Research Directions in Network Architectures and Protocols for Intelligent Digital Infrastructures

The availability of vast computing resources today allows us to reimagine how wireless networks and the Internet at large could operate if far more machine intelligence were used inside the networks themselves, rather than just at the servers and clients using them, and to develop new network architectures and protocols for intelligent digital infrastructures. This paper describes some results of how communication protocols can be reimagined taking into account much larger amounts of working memory capacity and machine intelligence, and outline a research agenda for the development of protocols for intelligent digital infrastructures.
Djenne: Dependable and Decentralized Computation for Networked Embedded Systems

How should we build applications for large-scale networked embedded systems -- now in the incarnation of the Internet of Things -- when we do not want to rely on the existence of a persistent connection to a remote data center? We present the design and implementation of a system, which we call Djenne, that can aggregate the computational power of the distributed devices because the increased capacity of these devices does allow for substantial work closer to the devices. The challenge that we overcome with Djenne is dependability: how can we cope with failures and the dynamics of wireless network links in such systems? Our design uses the actor model of computation and relies on replicated services to improve reliability and to create opportunities for parallelism that increase task throughput. The key innovations in our work are the use of adaptive mechanisms for rerouting data when system conditions change significantly as well as a holistic recovery approach when computations need to be repeated in the distributed system. Via experimental evaluation, we find that Djenne can improve throughput by 30% to 190% for different use cases while ensuring resilience in the face of intermittent failures.
Scheduling "Last Minute" Updates for Timely Decision-Making

We consider a setting where requests for updates regarding time-varying processes are required prior to making a sequence of decisions. Each request has a finite length time window during which the update should be received. The end of the window reflects the time at which a decision is to be made, while the start of the window models the earliest possible time at which a useful update could be sent. An update scheduled as near to the end of the window as possible is deemed the best, i.e., reflects the most timely information about the process' state. This is modelled by a reward depending on the time difference between the decision point and the last scheduled update. Requests arrive arbitrarily and share a limited communication resource, e.g., a single request can be scheduled per time slot, hence not all decisions can be based on the latest possible update. We consider update scheduling policies which maximize the overall reward rate. In particular we consider an adversarial request model and evaluate proposed algorithms via their Competitive Ratio (CR). Specifically, we first derive a lower bound on the CR of any causal policy. We then propose two scheduling policies, denoted adversarial and greedy, and provide further analysis and insights on regimes where one might be superior to the other. We validate these observations via simulation for a setting with stochastic arrivals.
Multi-task Learning for Joint Re-identification, Team Affiliation, and Role Classification for Sports Visual Tracking

Effective tracking and re-identification of players is essential for analyzing soccer videos. But, it is a challenging task due to the non-linear motion of players, the similarity in appearance of players from the same team, and frequent occlusions. Therefore, the ability to extract meaningful embeddings to represent players is crucial in developing an effective tracking and re-identification system. In this paper, a multi-purpose part-based person representation method, called PRTreID, is proposed that performs three tasks of role classification, team affiliation, and re-identification, simultaneously. In contrast to available literature, a single network is trained with multi-task supervision to solve all three tasks, jointly. The proposed joint method is computationally efficient due to the shared backbone. Also, the multi-task learning leads to richer and more discriminative representations, as demonstrated by both quantitative and qualitative results. To demonstrate the effectiveness of PRTreID, it is integrated with a state-of-the-art tracking method, using a part-based post-processing module to handle long-term tracking. The proposed tracking method, outperforms all existing tracking methods on the challenging SoccerNet tracking dataset.
Relative Boundary Modeling: A High-Resolution Cricket Bowl Release Detection Framework with I3D Features

Cricket Bowl Release Detection aims to segment specific portions of bowl release actions occurring in multiple videos, with a focus on detecting the entire time window of this action. Unlike traditional detection tasks that identify action categories at a specific moment, this task involves identifying events that typically span around 100 frames and require recognizing all instances of the bowl release action in the video. Strictly speaking, this task falls under a branch of temporal action detection. With the advancement of deep neural networks, recent works have proposed deep learning-based approaches to address this task. However, due to the challenge of unclear action boundaries in videos, many existing methods perform poorly on the DeepSportradar Cricket Bowl Release Dataset. To more accurately identify specific portions of the bowl release action in videos, we adopt a one-stage architecture based on Relative Boundary Modeling. Specifically, our method consists of three stages. In the first stage, we use the Inflated 3D ConvNet (I3D) model to extract spatio-temporal features from the input videos. In the second stage, we utilize Temporal Action Detection with Relative Boundary Modeling (TriDet) to model the boundaries of the bowl release action's specific portions based on the relative relationships between different time moments, thereby predicting the action's time window. Lastly, as the target events typically span around 100 frames and the predicted time windows may exhibit overlapping regions based on confidence scores, we implement a post-processing step to merge and filter these outputs, resulting in the final submission results. We conducted extensive experiments to demonstrate that our proposed method achieves superior performance. Additionally, we evaluated the training techniques of existing approaches. Our proposed method achieves a PQ score of 0.519, an SQ score of 0.822, and an RQ score of 0.632 on the challenge set of the DeepSportradar Cricket Bowl Release Dataset. Through this approach, our team, USTC\_IAT\_United, won the third place in the first phase of the DeepSportradar Cricket Bowl Release Challenge.
Current management of neonatal abstinence syndrome: a survey of practice in the UK and Ireland

Objective To study the current management practices of neonatal abstinence syndrome (NAS) throughout the UK and Ireland and identify changes in practice from the most recent survey in 2008. Design Postal questionnaire to a consultant paediatrician or neonatologist in all 215 neonatal units in the UK and Ireland in January 2020. Results Response rate was 62%. An objective scoring tool was used in 97% of units and the Finnegan score was favoured by 70%. Morphine sulfate use as first line for the treatment of opiate withdrawal was almost universal and 70% used a dose of 40 µg/kg every 4 hours (240 µg/kg/day). Phenobarbitone administration as a second-line agent for opiate withdrawal increased to 61% of units with significant reductions in chloral hydrate and chlorpromazine use compared with the previous survey. Morphine sulfate and phenobarbitone remain the preferred first-line and second-line agents, respectively, for polysubstance withdrawal. There was a significant increase in chlorpromazine use as first line for polydrug withdrawal (1.5–14.2%). The practice of units discharging infants’ home on medication increased to 46% from 29%. All units now permit breastfeeding in mothers taking methadone, compared with 81% previously. Conclusion and relevance Compared with the previous survey, improvements in evidence-based practices were noted, highlighting the benefits of this type of research. Nonetheless, significant variation still exists in some aspects of the management of NAS. Post-discharge follow-up varies widely, with particular deficits in ophthalmology follow-up.
Mononuclear cells from patients with rhupus are influenced by TNF in their production of gp130/sIL-6Rb and APRIL

Objective Rhupus is a rare disease that shares characteristics of systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). While several studies have explored the clinical and immunological profiles of patients with rhupus, the underlying cause of the disease remains unknown due to its complex pathogenesis. The objective of this study was to investigate the role of tumour necrosis factor (TNF) in the production of inflammatory molecules by peripheral blood mononuclear cells (PBMCs) from patients with rhupus. Methods The study involved five healthy controls, seven patients with rhupus and seven patients with SLE. PBMCs were obtained from each participant and stimulated with recombinant human TNF for 24 hours. The levels of various molecules secreted by the cells, such as cytokines and chemokines, were measured using immunobead-based assays on xMAP technology. Results The production levels of some molecules were higher in TNF-stimulated PBMCs from patients with rhupus and SLE than in unstimulated cells. In addition, the levels of certain molecules, including gp130/sIL-6Rb, a proliferation-inducing ligand (APRIL), interferon-β, matrix metalloproteinase-3 and interleukin (IL)-12, were higher in PBMCs from patients with rhupus even without TNF stimulation. Similarly, the levels of gp130/sIL-6Rb and APRIL were higher in TNF-stimulated PBMCs from patients with rhupus than in healthy controls. These results were further validated against patients with RA using enzyme-linked immunosorbent assay. Conclusions These findings suggest that the spontaneous production of molecules by cells from patients with rhupus may contribute to the development of the disease, and that TNF may play a role in this process by regulating the secretion of gp130/sIL-6Rb and APRIL.
Study of Motor Unit Action Potential Conduction Velocity and Firing Rate in Low Force Contractions using Empirical Mode Decomposition

Arrays of surface electrodes may be used to record individual motor unit action potential (MUAP) trains from the skin surface. Processing of the later gives access to direct estimation of instantaneous conduction velocity and firing rate of individual MUAPs, which are informative physiological features. However, the estimation of conduction velocity and firing rate may be sensitive to additive noise, which is always present in surface EMG recordings. In this paper, we propose to use the Ensemble Empirical Mode Decomposition (EEMD) to represent individual MU instantaneous conduction velocity and firing rate time-series as a sum of components (intrinsic mode functions) and to omit the components with energy lower than the expected noise level. This approach enables to denoise the conduction velocity and firing rate time-sequencies, extracted from the surface EMG recordings, and to unmask a physiological relationship between them.