Complete System Research Articles

Adaptive and automatic aerial image restoration pipeline leveraging pre-trained image restorer with lightweight Fully Convolutional Network

Earth observation and remote sensing necessitate the use of aerial imaging, and unmanned aerial vehicles (UAVs) are widely utilized for this purpose. Although UAVs can be costly, using inexpensive components could result in issues such as noise, defocusing, and motion blur. Utilizing advanced deep learning algorithms, these images can be effectively restored. However, this necessitates the use of physical effort since each image must be restored manually. Our work introduces a new pipeline that can automatically categorize the degradation types of aerial images and subsequently apply the necessary restoration techniques on degraded images. A lightweight adaptive degradation classifier model was proposed to handle input from images of varying sizes and provide guidance to a image restoration model for achieving the desired task. The degradation classifier is a Fully Convolutional Network capable of categorizing images of any size into 3 distinct classes. It offers guidance to the subsequent image restorer. The restoration model is a pre-trained transformer-based model that efficiently restores different types of image degradations. In addition, we have implemented a pipeline loss to assess the performance of our complete system. To build the system, a dataset is created by extracting cropped patches from high-resolution images obtained through Google Earth. Subsequently, the clean patches were artificially deteriorated by applying different filters to replicate the image degradations. The degradation classifier achieved a mean accuracy of 96.71% across 6 different test scenarios, with a standard deviation of 2.97. The mean pipeline loss was 24.95, with a standard deviation of 1.79. Furthermore, we showcased the efficacy of our pipeline in a practical implementation involving aerial imagery, specifically in the domain of vehicle detection. We conducted training on an object detection model and then evaluated the detection performance on both degraded and automatically restored images. Our experiments demonstrate the efficient performance of our method in automatically restoring degraded aerial images, even though the restoration models were not specifically trained on aerial images. In addition, we examined current limitations and difficulties in creating such systems and offered comprehensive perspectives on future advancements.

A Comprehensive Review on Chemistry and Contribution of Chinese Herb Epimedium brevicornum Maxim in Medicine

Background: Traditional Chinese medicine (TCM) is a complete medical system that has been used for more than 2,000 years and it is effective to use Epimedium Brevicornum (EB) Maxim, one of the Chinese herbs belonging to the family Berberidaceae is of major use because of its bioactive compound Icariin (ICA). Objective: This review aims on providing a collective report of the description, taxonomy, therapeutic uses, bioactive compounds, and the different pharmacological activities of the plant EB for future research. Methods: Data was obtained from various informative tools like PubMed, ScienceDirect, Google Scholar, and the botanical information sites for different plants. Results: This literature review shows that the Chinese herb EB possesses various therapeutic effects and can be used in the prophylaxis of different ailments. The extract of different parts of EB contains many bioactive compounds such as phenols, flavonoids, and lignans. They show a wide range of pharmacological activities which include anti-inflammatory, anti-infertility, anti-cancer, and effective against Alzheimer’s disease and osteoporosis. ICA was found to be the major constituent of this herbal plant aiding in almost every pharmacological activity . Conclusion: The review covers every activity the plant holds and indicates that the plant is a useful source in eradicating a variety of ailments. Researchers have performed invitro and invivo experiments to explore plant capabilities. The plant could be of very much use in botanical and pharmacological fields. For experts aiming to research EB, this review could be a great source of information.

Anti-seasonal flooding drives substantial alterations in riparian plant diversity and niche characteristics in a unique hydro-fluctuation zone.

Human-induced disturbances such as dam construction and regulation have led to widespread alterations in hydrological processes and thus substantially influence plant characteristics in the hydro-fluctuation zones (HFZs). To reveal utilization of limited resources and mechanisms of inter-specific competition and species co-existence of plant communities based on niche breadth and overlap under the different HFZs of the Three Gorges Reservoir (TGR) in China, we conducted a field investigation with 368 quadrats on the effects of hydrological alterations on plant diversity and niche characteristics. The results showed anti-seasonal flooding precipitated the gradual disappearance of the original diverse niches, resulting in the reduction of plant species richness and functional diversity and more obvious competition among plant species with similar resource requirements. Annuals, perennials and shrubs accounted for 71.23%, 27.39% and 1.37%, respectively, suggesting that annuals and flood-tolerant riparian herbs were favored under such novel flooding conditions. A consistent increase in species number, Shannon-Wiener diversity index and Simpson dominance index with altitude was inconsistent with hump-shaped diversity-disturbance relationship of the intermediate disturbance hypothesis, while the opposite trend was observed for the Pielou evenness index. This species distribution pattern might be caused by several synergetic attributes (e.g., the submergence depth, plant tolerant capacity to flooding, life form, dispersal mode and inter-specific competition). Vegetation types shifted from xerophytes to mesophytes and eventually to hygrophytes with the increasing flooding time in the HFZs. Hydrological alterations proved to be the paramount driver of vegetation distribution in the different HFZs. The niche analysis provided the first insights on the mechanisms of resource utilization and inter-specific competition, of which annuals could germinate quickly after soil drainage to achieve the greatest competitive advantages and occupy a larger niche space than other plants. Vegetation was still in the early stage of primary succession in the novel riparian forests. Therefore, vegetation restoration strategies should be biased towards herbaceous plants, due to annuals with better environmental adaptability, supplemented by shrubs and small trees. To establish a complete reference system for vegetation restoration, natural vegetation monitory plots in the different succession stages should be established in the different HFZs of the TGR, and their environmental conditions, community structures and inter-specific relationships further analyzed.

Bringing the Value Chain for High-Impact Weather Warnings into the Classroom

Abstract University students can learn about weather warnings and contribute to a database for the World Meteorological Organization (WMO) project on value chain approaches to evaluate the end-to-end warning chain. The project offers students a way to understand how information about high-impact weather is created, shared, and used within a complete warning system for a selected event. Their contributions are intended to inform researchers and practitioners on what has and what has not worked well in the warning process. The students use a structured questionnaire designed to collect information on observations, forecasting, hazards, impacts, warning communications, and responses.

PERFORMANCE EVALUATION OF A 67.2 KWP SI-POLY PHOTOVOLTAIC SYSTEM CONNECTED TO THE GRID USING PVSYST TOOL

This paper presents the simulated performance evaluation of a 67.2 kWp grid-connected Si-poly photovoltaic system. This study was carried out to assess the feasibility of installing a photovoltaic system to supply the electrical loads at the Alioune DIOP University of Bambey, Senegal, a public institution. Indeed, the UADB is facing load shedding problems caused by its exorbitant energy consumption. The study system comprises 240 Si-poly modules. Each module has a rated output of 280 Wp. All photovoltaic modules are connected in 12 strings, each string consisting of 20 modules in series. Three solar inverters, each rated at 20 kW, are used for interconnection with the grid via a public meter. For the case study, PVsyst 7.4 is used for simulation. PVsyst 7.4 is a PC software package for the design, dimensioning and data analysis of complete photovoltaic systems. Meteonorm 8.1 meteorological data sets on solar radiation, ambient temperature, wind speed and humidity from the PVsyst database were used for this analysis. In this study, the parameters evaluated were the photovoltaic arrays effective energy production, the energy injected into the grid, the performance rate and the normalized energy production per kWp installed. The 67.2 kWp photovoltaic system generates 111.287 MWh/year of DC energy, of which 108.980 MWh/year of AC energy is fed into the grid. The systems annual performance rate is around 81.5%, and the loss diagram over the whole year is also computed.

Interweaving Melody and Beat -Specialties of Japanese and Korean Pop Music Styles and Development from Yonezu Kenshi and Han JiSung

Currently, in Asia and around the world, Japanese and Korean popular music cultures have a large number of fans and imitators. These two pop music cultures have their own characteristics, both of which have extremely distinctive style characteristics, complete and standardized industrial systems and a large number of creative, young and energetic practitioners. Therefore, the author tries to explore the style and development characteristics of Japanese and Korean pop music. In order to be more precise and efficient, the author selected two representative musicians, Yonezu Kenshi (Japan) and Han JiSung (South Korea) for the study. The author's research method is as follows. The author makes full use of previous theoretical research on Japanese and Korean pop music, combined with professional knowledge of music, and collects statements and social interviews of relevant authors in order to have a comprehensive understanding of their representative music works. Then the author makes a coded analysis and statistical drawing of the melody, rhythm and emotional expression of his representative works. After the study, the author found that the development of Japanese and Korean popular music cultures are similar but also significantly different. Mainly, the former is relatively conservative and traditional, focusing on melody; the latter is more open and tolerant, focusing on rhythm; at the same time, there are quite a lot of similarities and differences between the two in terms of emotional expression and lyrical characteristics. Finally, based on the summarized developmental characteristics, the author draws some inspirations for the development of Chinese pop music.

Study on the Targeting and Practical Path of Cultivating Young Cadres in the Party in the New Era

The General Secretary has gradually formed a complete theoretical system for cultivating young cadres in the course of long-term observation and reflection, the most important of which is the goal-oriented theory that puts forward clear requirements for young cadres and the specific path and methodology formed through the efforts of party organisations and young cadres, which is a rich and comprehensive theory.The goal of cultivation is a guide for the cultivation of young cadres in the new era, pointing out the direction for the Marxist party to cultivate young cadres. The General Secretary has repeatedly mentioned the standards of good cadres, which include core standards, selection standards, competence standards and service standards. As to how to achieve the cultivation goals, the General Secretary has put forward a number of practical paths encompassing both organizational cultivation and personal struggle. These contents both reflect a lineage and realize breakthrough innovations, making great contributions to the promotion of young cadres' cultivation within the Party in the new era.

Asgard archaea defense systems and their roles in the origin of eukaryotic immunity

Dozens of new antiviral systems have been recently characterized in bacteria. Some of these systems are present in eukaryotes and appear to have originated in prokaryotes, but little is known about these defense mechanisms in archaea. Here, we explore the diversity and distribution of defense systems in archaea and identify 2610 complete systems in Asgardarchaeota, a group of archaea related to eukaryotes. The Asgard defense systems comprise 89 unique systems, including argonaute, NLR, Mokosh, viperin, Lassamu, and CBASS. Asgard viperin and argonaute proteins have structural homology to eukaryotic proteins, and phylogenetic analyses suggest that eukaryotic viperin proteins were derived from Asgard viperins. We show that Asgard viperins display anti-phage activity when heterologously expressed in bacteria. Eukaryotic and bacterial argonaute proteins appear to have originated in Asgardarchaeota, and Asgard argonaute proteins have argonaute-PIWI domains, key components of eukaryotic RNA interference systems. Our results support that Asgardarchaeota played important roles in the origin of antiviral defense systems in eukaryotes.

A gene-rich mitochondrion with a unique ancestral protein transport system

Mitochondria originated from an ancient endosymbiosis involving an alphaproteobacterium.1,2,3 Over time, these organelles reduced their gene content massively, with most genes being transferred to the host nucleus before the last eukaryotic common ancestor (LECA).4 This process has yielded varying gene compositions in modern mitogenomes, including the complete loss of this organellar genome in some extreme cases.5,6,7,8,9,10,11,12,13,14 At the other end of the spectrum, jakobids harbor the most gene-rich mitogenomes, encoding 60-66 proteins.8 Here, we introduce the mitogenome of Mantamonas sphyraenae, a protist from the deep-branching CRuMs supergroup.15,16 Remarkably, it boasts the most gene-rich mitogenome outside of jakobids, by housing 91 genes, including 62 protein-coding ones. These include rare homologs of the four subunits of the bacterial-type cytochrome c maturation system I (CcmA, CcmB, CcmC, and CcmF) alongside a unique ribosomal protein S6. During the early evolution of mitochondria, gene transfer from the proto-mitochondrial endosymbiont to the nucleus became possible thanks to systems facilitating the transport of proteins synthesized in the host cytoplasm back to the mitochondrion. In addition to the universally found eukaryotic protein import systems, jakobid mitogenomes were reported to uniquely encode the SecY transmembrane protein of the Sec general secretory pathway, whose evolutionary origin was however unclear. The Mantamonas mitogenome not only encodes SecY but also SecA, SecE, and SecG, making it the sole eukaryote known to house a complete mitochondrial Sec translocation system. Furthermore, our phylogenetic and comparative genomic analyses provide compelling evidence for the alphaproteobacterial origin of this system, establishing its presence in LECA.

The Value of Digital Narrative in Oral Second Language Teaching

Digital Narrative has long been formed, developed and mature in foreign countries, but the domestic attention to it is still less, the lack of a complete theoretical system and practical model, so it is rarely used in classroom practice. As the product of the combination of digital information technology and traditional narrative, Digital Narrative is derived from video teaching. The initial form of Digital Narrative is relatively simple, based on the cognitive theory of multimedia learning and the theory of multiple literacy. In practice, Digital Narrative can be mediated by extra-curricular activities, network platforms, and theme competitions, which is of great value in oral second language teaching due to its unique advantages of novelty, diversity and situationality.

A Comparative Study of the Divorce Systems of the Tang Dynasty and Japan at the same Era

The system of divorce, which is a very important part of the marriage system, also formed a complete system and developed to its peak in the feudal era of the Tang Dynasty. In the process of economic, cultural and political exchanges between the Tang Dynasty and other countries, the divorce system of the late Asuka Period, the Nara Period and the early Heian Period in Japan, which corresponded to the Tang Dynasty, had a certain influence. This paper mainly combines the historical material "Tang Laws and Regulations" and Japanese "Pension Laws", "Household Marriage Laws" and other laws to carry out theoretical research, literature research method, and comparative research method. In the process of transplantation of Chinese law, it also reflects the different social ideologies of two different countries for the divorce system, and it produces a certain difference for the maintenance of harmonious family relations, social stability, and the sense of well-being of the divorce system to different.

Comparing LLMs using a Unified Performance Ranking System

Large Language Models (LLMs) have transformed natural language processing and AI-driven applications. These advances include OpenAI’s GPT, Meta’s LLaMA, and Google’s PaLM. These advances have happened quickly. Finding a common metric to compare these models presents a substantial barrier for researchers and practitioners, notwithstanding their transformative power. This research proposes a novel performance ranking metric to satisfy the pressing demand for a complete evaluation system. Our statistic comprehensively compares LLM capacities by combining qualitative and quantitative evaluations. We examine the advantages and disadvantages of top LLMs by thorough benchmarking, providing insightful information on how they compare performance. This project aims to progress the development of more reliable and effective language models and make it easier to make well-informed decisions when choosing models.

Numerical analysis of dynamic behaviors of underwater towed system with hydrofoil manipulations

This paper addresses the dynamic characteristics of an underwater towed system under manipulations of synchronous hydrofoils, considering the coupling of instantaneous fluid forces on the complete systems and hydrofoil control, which is usually difficult to solve with existing methods. A hydrodynamic model coupled with hydrofoil control algorithms is presented, wherein the hydrodynamic forces on the hydrofoils and Underwater Towed Vehicle (UTV) are simulated using the Computational Fluid Dynamics (CFD) method, and the fluid forces on the Towing Cable (TC) are described using a flexible cable dynamic model. The dynamic behaviors of the underwater towed system under depth-undulating, depth-tracking, and depth-keeping controls of hydrofoils are analyzed using the proposed model. The results show that the towing speed has a significant effect on the control efficiency of the hydrofoils. The dynamic responses of the underwater towed system increase or decrease more significantly in submerged depth control operations than in freely towing operations. The hydrofoils can achieve satisfactory effects in submerged depth control for the UTV at an appropriate towing speed, whereas it fails at a lower towing speed and noticeable dynamic response oscillations occur simultaneously. This study is expected to provide guidance on both hydrodynamic and control issues of underwater towed systems.

Integrated Bionic Human Retina Process and In‐Sensor RC System Based on 2D Retinomorphic Memristor Array

AbstractThe rapid development of machine vision has put forward higher requirements for image perception and visual learning systems. However, limited by the von Neumann bottleneck, traditional artificial vision systems rely on complex optical and circuit designs, and the separate distribution of sensors, memory, and computing modules results in high energy consumption and high latency. Memristor‐based reservoir computing (RC) system with integrated sensing and memory functions provides a solution to effectively improve the computational efficiency of artificial vision networks. Here, a complete artificial visual recognition system based on in‐sensor RC is developed by combining the excellent optoelectronic synaptic properties of 2D WS2 memristor array. Through effectively regulating the conductance of memristors by light or electrical stimulation, image information is converted into high‐dimensional information in the reservoir layer, and the classification can be completed by simple training, significantly reducing the training complexity and cost consumption. With this system, an effective recognition of hand‐written numbers with an accuracy of 88.3% is demonstrated, and a 100% recognition of traffic signals of different colors is achieved. The proposed in‐sensor RC system advances the development and application of artificial vision recognition, paving the way for efficient machine learning and neuromorphic vision systems.

Dynamical analysis and the soliton solutions of (2+1)-dimensional Heisenberg ferro-magnetic spin chains model with beta fractional derivative

This paper investigates the soliton solutions and dynamical analysis of (2+1)-dimensional Heisenberg ferro-magnetic spin chains model with beta fractional derivative, which is transformed into the ordinary differential equation. By using the second-order complete discriminant system, the soliton solutions are presented. By utilizing the theory of planar dynamical system, the phase portraits of the dynamical system and its disturbance system are drawn. Moreover, three-dimensional, two-dimensional, and contour plots of soliton solutions for (2+1)-dimensional Heisenberg ferro-magnetic spin chains model with beta fractional derivative have also been plotted.

Introducing a comprehensive methodology for optimizing the mass of realistic roofing structural systems using cold-formed steel profiles

This study aims to introduce a comprehensive methodology for optimizing complete real structural systems for roofs involving trusses, purlins, and bracing systems jointly, taking into account realistic loads and constraints dictated by technical codes, thereby offering a more accurate representation of practical scenarios. The objective is to achieve the minimum mass through size, shape, and topology optimization of both the main truss and purlin structural subsystems. To achieve this goal, the Enhanced Particle Swarm Optimization (EPSO) algorithm is implemented. An example of a realistic case, which takes into account multiple actual constraints such as stress, displacement, buckling, and natural frequency limits, is thoroughly evaluated. After that, 144 other interactions among dimensions of the building and loads applied are simulated, and the mass of the system is obtained for each one of them. The results indicated that the graphs generated from the various simulations allow for the determination of the optimized mass for different building dimensions. Consequently, the cost and raw material consumption can be estimated for common applications. Therefore, it is concluded that this work presents a significant contribution to structural designers, as the proposed methodology enables structural optimization quickly and easily for practical engineers.

A Single-Camera-Based Three-Dimensional Velocity Field Measurement Method for Granular Media in Mass Finishing with Deep Learning.

Surface treatment processes such as mass finishing play a crucial role in enhancing the quality of machined parts across industries. However, accurate measurement of the velocity field of granular media in mass finishing presents significant challenges. Existing measurement methods suffer from issues such as complex and expensive equipment, limited to single-point measurements, interference with the flow field, and lack of universality in different scenarios. This study addresses these issues by proposing a single-camera-based method with deep learning to measure the three-dimensional velocity field of granular flow. We constructed a complete measurement system and analyzed the accuracy and performance of the proposed method by comparing the measurement results with those of the traditional DIC algorithm. The results show that the proposed method is very accurate in measuring spatial displacement, with an average error of less than 0.07 mm and a calculation speed that is 1291.67% of the traditional DIC algorithm under the same conditions. Additionally, experiments in a bowl-type vibratory finishing machine demonstrate the feasibility of the proposed method in capturing the three-dimensional flow of granular media. This research not only proposed a novel method for three-dimensional reconstruction and velocity field measurement using a single-color camera, but also demonstrated a way to combine deep learning with traditional optical techniques. It is of great significance to introduce deep learning to improve traditional optical techniques and apply them to practical engineering measurements.

Construction and Development of Smart Cities -- Taking Chengdu as an Example

As an important way to promote urban economic and cultural development, the smart city is an inevitable choice for future urban development. This paper first expounds on the concept and proposal of a smart city, discusses the background of the development of smart cities in China, and then introduces the current development of a smart city in Chengdu, a pilot city, and establishes a complete intelligent system to promote the operation of the city and improve people's living efficiency. Then, according to the design concept of green building, the common ground between green building and smart city development is analyzed. Taking epidemic prevention as the entry point, how to develop and play its role is discussed. The problems such as information "isolated island" and incomplete technology deployment are analyzed. Finally, some suggestions are put forward for related issues, and a bright prospect is given for the future blossoming and unlimited potential of smart cities.

The Current Situation and Prevention of AI Telecom Fraud: Starting from Personal Information Protection

AI telecom fraud is an act of using artificial intelligence deep cooperation and analysis technology to create false information to lure and deceive individuals and illegal possession of money. With the rapid development of the Internet and AI, the number of AI telecom fraud cases has exploded, so how to prevent AI telecom fraud has become an important issue in society. AI telecom fraud has led to a series of problems, such as the illegal collection and malicious disclosure of personal information, criminals using AI to analyze personal information for fraud, and the industry does not adequately supervise the collection and use of personal information by companies. This article uses case analysis, normative analysis, and comparative research methods to analyze the above three problems and proposes the solution, including establishing a complete legal regulatory system for personal information protection and the prevention and control of AI telecom fraud, and strengthening industry supervision. It is hoped that by applying the above-mentioned solutions, the protection of personal information and the prevention and control of AI telecom fraud can be strengthened, and the development of AI telecom fraud prevention and control in China can be promoted.

Heavy metal removal by porous asphalt in cyclical wetting and drying

Porous asphalt pavement (PAP) is subjected to wetting and drying cycles involving storms of varying intensity and inter-event drying periods to study the impact of continuous weather systems on heavy metal removal in runoff. Four physical models: a complete PAP system, a PAP surface, a geotextile fabric and a reservoir of cobblestone aggregate, were created at the lab-scale and tested with stormwater contaminated with dissolved Mn(Ⅱ), Zn(Ⅱ), Cu(Ⅱ), and Cr(Ⅵ). The models were exposed to repeated wetting and drying cycles spanning over 27 days in triplicate. Wetting involved light, moderate and heavy rainfall intensities. All pavement material designs performed well at removing Cu(Ⅱ) and Cr(Ⅵ). The PAP system had an overall better performance at removing Mn(Ⅱ), Zn(Ⅱ), Cu(Ⅱ), and Cr(Ⅵ) than any of the individual pavement materials but was unable to remove all of the heavy metals simultaneously to sufficiently high levels. The materials used in the filter layer and reservoir structure and their adsorption and desorption capacities should be assessed for potential contamination (leaching) of Zn(Ⅱ) and Mn(Ⅱ), respectively, prior to construction. Wetting and drying cycles had the greatest impacts on the reservoir structure’s performance versus any of the other layers. Leaching of Mn(II) observed from cobblestone aggregate was affected by the solution composition and pH. Removal of selected heavy metals was rapid in first flush and fluctuated with storm event intensity.