Separate Projects Research Articles

Efficient blind super-resolution imaging via adaptive degradation-aware estimation

Single image super-resolution (SISR) has achieved prominent success based on deep learning. However, most SISR methods based on the specific degradation pattern, e.g., bicubic interpolation with a bulky network structure, are unsuitable for real-world images reconstructed on edge devices. To mitigate the above limitations, unlike the majority of blind super-resolution methods, which consist of a separate complex degradation kernel projection network and a SR reconstruction network, we propose an end-to-end lightweight multi-degradation oriented network that not only can estimate degradation kernel but also reconstructs HR image fast and accurately. The core components of the designed network adopt a lightweight SR model with region non-local feature similarity learning, i.e., Region Non-Local Feature Block (RNLFB), to establish region-wise global feature correlation. Concretely, more and fewer RNLFBs are used to learn more sophisticated feature representation and relatively simple degradation representation. Then, a degradation kernel projector is equipped to fulfill adaptive degradation-aware estimation from the degradation representation. With the help of the encoded degradation kernel, the reconstruction model can learn to restore a high-resolution image from the feature representation. By doing so, the degradation kernel estimation task and the HR image reconstruction task can be accomplished without designing two complex networks separately, which guides more stable and effective network training under low computational resource costs. Extensive experiments on synthetic and real-world datasets demonstrate that our method can fulfill precise degradation kernel prediction and HR image reconstruction compared with other state-of-the-art SR methods with lower model complexity.

Agricultural ethics of biofuels: big science and global climate ethics

ABSTRACT In the first decade of the twenty-first century, biofuels were recognized as an important element in the overall strategy to reduce climate-forcing greenhouse gases, especially carbon dioxide. Yet scientific research to more fully realize the potential of agricultural crops for liquid transportation fuel requires the coordination of many separate projects housed in different disciplines. Studies predicting and documenting adverse social impacts of plant-based ethanol and biodiesel led to the inclusion of social science components within research teams seeking to develop biofuels. A 2008 rise in global food prices became a centerpiece of this research, leading to a search for non-food crops that could serve as energy feedstocks. Although coordinated scientific research teams have made significant strides toward incorporating social dimensions and broader impacts into what was originally a purely biophysical research effort, a simplistic diagnosis of the tension between agricultural production for food use and agricultural production intended for energy production continues to prevail. Some of the hard questions in the global development of the agricultural sector have been obscured as a result.

Proposal and design of 81.25 MHz heavy ion drift tube linacs for BISOL

Based on the design requirements proposed by the Beijing On-Line Isotope Separation project (BISOL), four Sn22+-based, 81.25 MHz continuous wave (CW) drift tube linac (DTL) cavities have been designed. These DTLs are capable of accelerating Sn22+ of 0.1 pmA from 0.5 MeV/u to 1.8 MeV/u over a length of 7 m, with an output longitudinal normalized RMS emittance of 0.35π·mm·mrad, and transmission efficiency higher than 95%. The dynamics design adopted the KONUS (Kombinierte Null Grad Struktur Combined 0° Structure) scheme. Comprehensive error study implies that these DTLs can accommodate a wide range of non-ideal beams and cavity alignment errors while maintaining high transmission efficiency. The electromagnetic design employed a Cross-bar H-mode (CH) structure for superior water-cooling characteristics, and a detailed tuning analysis was conducted to derive an optimal tuning scheme. The results of the multiple-physics analysis indicate that the frequency shift of each cavity is within an acceptable range. Comparing the dynamics requirements with the RF design results, similar particle output phase distribution, equivalent energy gain and consistent emittance growth are observed. Detailed designs will be presented in this manuscript.

Navigating institutional demands: Organizational responses to institutional complexity in megaproject delivery

Megaprojects are commonly exposed to multiple, conflicting institutional demands, making them notoriously difficult to manage. Drawing on organizational institutional theory, the paper explores organizational responses to deal with institutional complexity on a transnational pipeline project spanning China, Kazakhstan, Uzbekistan, and Turkmenistan. The findings show how conflicting institutional demands across the involved countries were dealt with through the establishment of distinct organizational strategies and structures when a large Chinese petroleum organization entered into two separate project companies, each responsible for a section of the pipeline. One relied on a manipulation strategy where institutional complexity was reconciled by selectively coupling to certain institutional demands. The other handled competing demands through a compromise strategy involving the creation of a compartmentalized organizational structure. While these results confirm findings from prior work that the nature and internal representation of demands exerted on an organization shape its response strategy, we contribute further by showing how distinct contextual characteristics of megaprojects influence the specific responses adopted to deal with institutional complexity.

An improved analogy-rule based software effort estimation using HTRR-RNN in software project management

To complete a software project, the most realistic effort required is predicted by the process called Software Effort Estimation (SEE). Effort Estimation (EE) in software development is considered a complicated task owing to the variability of variables. Thus, numerous Software Development EE (SDEE) models have been developed; nevertheless, these models' accuracy rates are not good enough, and the variations among software functionalities were not focused for SEE. Therefore, by considering it as the research gap in Software Project Management (SPM), an enhanced analogy-rule-centric SEE utilizing Hyperbolic Tangent Recurrent Radial − Recurrent Neural Networks (HTRR-RNN) algorithm is proposed in this work. Initially, regarding the project size, the projects are partitioned. Next, the highly vital features are extracted as of the separated projects. By employing Levy Flight-Rock Hyraxes Swarm (LH-RHS) optimization, the selective quantity of features is chosen from the extracted features. By deploying the Mamdani Method − Fuzzy (MM-Fuzzy) algorithm, the rules are created regarding the selected features. Lastly, the number of efforts needed for the software development process is determined by the classification algorithm regarding the rules being created. COCOMO81, MAXWELL, and China are the openly accessible datasets utilized in this methodology. Then, the proposed method’s results are contrasted with the prevailing algorithms. As per the experimental results, the proposed methodology performs SEE with a better accuracy rate; thus, it surpassed the other existing methodologies.

Engaging diverse voices across sites of curriculum making in Australia: realities and possibilities

AbstractResearch to date has pointed out that during periods of curriculum reform, public debate gets politicised resulting in an over-emphasis on top-down approaches to curriculum making. As a group of curriculum inquiry researchers, we are concerned that teachers, students, school leaders and community organisations are often side-lined as integral curriculum actors in curriculum making processes. This paper challenges top-down, discipline-siloed conceptualisations of curriculum making by bringing together three separate curriculum projects, as illustrations, for the purpose of rendering diverse articulations of curriculum as a social process. We apply Priestley et al.’s (Priestley et al., Curriculum making in Europe: Policy and practice within and across diverse contexts, Emerald Publishing Limited, 2021) sites of curriculum making as a conceptual frame, to articulate the diversity of curriculum making activities, curriculum actors and sites of curriculum making in primary and secondary settings. The three illustrations include examining how teachers and students participate in curriculum making about Asia and Australia’s engagement with Asia at macro and meso sites; how listening to secondary students as curriculum actors allows them to contribute to shaping school History beyond the nano sites of the classroom and how community and arts-based approaches empower primary students to engage in nano curriculum making (e.g. Hannigan & Kelly, Hannigan and Kelly, Lin et al. Sinner et al. Irwin (eds), Community arts education: Transversal global perspectives, Intellect, 2023). By engaging a collaborative approach that uses illustrations to draw a complementary transdisciplinary picture of the realities and possibilities of curriculum making across different sites, this paper makes a novel methodological contribution to the field of curriculum inquiry.

A Study of Efficiency and Economic Value of Grade Separated Construction Project: Case Study of Grade Separated Without Ramp across The Sri Ayutthaya Intersection Bangkok

This research was conducted to analyze the efficiency and economic value of grade separated construction projects in a large city due to heavy traffic volumes. This is consistent with the current situation where traffic volumes are continually increasing. In order to reduce fuel consumption, accidents and travel time. In this research, the efficiency and economic value of grade separated without ramp across Sri Ayutthaya intersection will be studied, Bangkok (Thailand), is considered in the form of an underpass through the intersection by using the VISSIM program to create and develop micro simulation traffic models. Then, the economic cost-benefit analysis of the project is evaluated by considering the economic worthiness of the project from a comparison between the case with the project and without the project. The economic worthiness of the project is analyzed by using Net Present Value (NPV), Benefit-Cost Ratio (B/C ratio) and Internal Rate of Return (IRR). From the results of this study, it was found that after developing the current area, which is a ground level intersection into an underpass. Traffic at intersections will be more efficient. And helps reduce traffic congestion at intersections. This is because the average delay of each type of vehicle decreased after the project. Performance measures at intersections can be summarized as the average vehicle delay in the project start year (2027) for motorcycles decreased from 364.48 seconds/vehicle to 85.93 seconds/vehicle, passenger cars decreased from 369.35 seconds/vehicle to 78.42 seconds/vehicle, trucks decreased from 282.19 seconds/vehicle to 78.96 seconds/vehicle, and buses decreased from 420.47 seconds/vehicle to 65.07 seconds/vehicle. And it can be concluded that the project of grade separated construction in the form of an underpass across Sri Ayutthaya Intersection. It is economically worthwhile and suitable for investment. Because the net present value (NPV) in the 15th year of the project (2041) is equal to 1,752.18 million baht, which is greater than 0, the benefits-costs ratio (B/C Ratio) in the 15th year of the project (2041) is equal to 3.61, which is greater than 1, and the internal rate of return (IRR) at the 15th year of the project (2041) is equal to 42%, which is greater than 12%.

Assessment of intracranial aneurysm rupture risk using a point cloud-based deep learning model.

Background and Purpose: Precisely assessing the likelihood of an intracranial aneurysm rupturing is critical for guiding clinical decision-making. The objective of this study is to construct and validate a deep learning framework utilizing point clouds to forecast the likelihood of aneurysm rupturing. Methods: The dataset included in this study consisted of a total of 623 aneurysms, with 211 of them classified as ruptured and 412 as unruptured, which were obtained from two separate projects within the AneuX morphology database. The HUG project, which included 124 ruptured aneurysms and 340 unruptured aneurysms, was used to train and internally validate the model. For external validation, another project named @neurIST was used, which included 87 ruptured and 72 unruptured aneurysms. A standardized method was employed to isolate aneurysms and a segment of their parent vessels from the original 3D vessel models. These models were then converted into a point cloud format using open3d package to facilitate training of the deep learning network. The PointNet++ architecture was utilized to process the models and generate risk scores through a softmax layer. Finally, two models, the dome and cut1 model, were established and then subjected to a comprehensive comparison of statistical indices with the LASSO regression model built by the dataset authors. Results: The cut1 model outperformed the dome model in the 5-fold cross-validation, with the mean AUC values of 0.85 and 0.81, respectively. Furthermore, the cut1 model beat the morphology-based LASSO regression model with an AUC of 0.82. However, as the original dataset authors stated, we observed potential generalizability concerns when applying trained models to datasets with different selection biases. Nevertheless, our method outperformed the LASSO regression model in terms of generalizability, with an AUC of 0.71 versus 0.67. Conclusion: The point cloud, as a 3D visualization technique for intracranial aneurysms, can effectively capture the spatial contour and morphological aspects of aneurysms. More structural features between the aneurysm and its parent vessels can be exposed by keeping a portion of the parent vessels, enhancing the model's performance. The point cloud-based deep learning model exhibited good performance in predicting rupture risk while also facing challenges in generalizability.

Queer breaches and normative devices: language learners queering gender, sexuality, and the L2 classroom

ABSTRACT Cisgender and heterosexual norms permeate every level of language classrooms, from textbooks to classroom discourse to teachers’ actions, constraining queer/trans learners’ ability to be themselves. Yet queer/trans and non-queer/trans learners alike may challenge cisheteronormativity within the language classroom and create new possibilities. We investigate the possibilities of queer/trans learners’ agency within these normative structures by bringing together three cases from larger separate projects, examining the context and actions of learners in each setting as they attempt to queer their classrooms to make them habitable. Drawing from Ahmed’s queer phenomenology, we analyze the devices that orient students to classroom cisheteronormativity, actions that students and their accomplices may take to breach these norms, and the reactions to and potential of such breaches within the L2 classroom context. We find that orienting devices, including curricular representation, language use, and grading practices, convey implicit and explicit messaging that can limit expressions of gender and sexuality. Yet queer breaches, when not subject to straightening, can lead to new classroom possibilities for expression, playfulness, and identity validation. We conclude by considering the implications of this analysis for practice.

SYNTHESIS OF VHDL-MODEL OF A FINITE STATE MACHINE WITH DATAPATH OF TRANSITIONS

Context. The problem of building a program model of a finite state machine with datapath of transitions using VHDL language is considered. The model synthesis process is identified with the synthesis of this type of finite state machine, since the built model can be used both for the analysis of the device’s behavior and for the synthesis of its logic circuit in the FPGA basis. The object of the research is the automated synthesis of the logic circuit of the finite state machine with the datapath of transitions, based on the results of which numerical characteristics of the hardware expenses for the implementation of the state machine circuit can be obtained. This makes it possible to evaluate the effectiveness of using this structure of the finite state machine when implementing a given control algorithm.
 Objective. Development and research of a VHDL model of a finite state machine with datapath of transitions for the analysis of the behavior of the state machine and the quantitative assessment of hardware expenses in its logic circuit.
 Method. The research is based on the structural diagram of a finite state machine with datapath of transitions. The synthesis of individual blocks of the structure of the state machine is carried out according to a certain procedure by the given graph-scheme of the con-trol algorithm. It is proposed to present the result of the synthesis in the form of a VHDL description based on the fixed values of the states codes of the state machine. The process of synthesizing the datapath of transitions, the block of formation of codes of transitions operations and the block of formation of microoperations is demonstrated. VHDL description of that blocks is carried out in a synthesizable style, which allows synthesis of the logic circuit of the finite state machine based on FPGA with the help of modern CAD and obtaining numerical characteristics of the circuit, in particular, the value of hardware expenses. To analyze the correctness of the synthesized circuit, the process of developing the behavioral component of the VHDL model, the function of which is the generation of input signals of the finite state machine, is considered. The classical combination of the synthesizable and behavioral parts of the model allows presenting the results of the synthesis of a finite state machine with datapath of transitions as a separate project that can be used as a structural component of the designed digital system.
 Results. Using the example of an abstract graph-scheme of the control algorithm, a VHDL model of a finite state machine with datapath of transitions was developed. With the help of CAD AMD Vivado, a synthesis of the developed model was carried out and behavioral modeling of the operation of the finite state machine circuit was carried out. The results of the circuit synthesis made it possible to obtain the value of hardware expenses when implementing the circuit in the FPGA basis. According to the results of behavioral modeling, time diagrams were obtained, which testify to the correctness of the implementation of the functions of transitions and outputs of the synthesized state machine.
 Conclusions. In traditional VHDL models of finite state machines, the states do not contain specific codes and are identified using literals. This allows CAD to encode states at its own discretion. However, this approach is not suitable for describing a finite state machine with datapath of transitions. The transformation of states codes using a set of arithmetic and logic operations requires the use of fixed values of states codes, which determines the specifics of the VHDL model proposed in this paper. This and similar models can be used, in particular, in the study of the effectiveness of a finite state machine according to the criterion of hardware expenses in the device circuit.

A communication platform demonstrator for new generation railway traffic management systems: Testing and validation

Current rail traffic management and control systems cannot be easily upgraded to the new needs and challenges of modern railway systems because they do not offer interoperable data structures and standardized communication interfaces. To meet this need, the Horizon 2020 Shift2Rail OPTIMA project has developed a communication platform for testing and validating the new generation of traffic management systems (TMS), whose main innovative features are the interoperability of the data structures used, standardization of communications, continuous access to real-time and persistent data from heterogeneous data sources, modularity of components and scalability of the platform. This paper presents the main components, their functions and characteristics, then describes the testing and validation of the platform, even when federated with other innovative TMS modules developed in separate projects. The successful validation of the system has confirmed the achievement of the objectives set and allowed a new set of objectives to be defined for the reference platform for the railway TMS/Traffic Control systems.

An Integration of Business Processes and Information Management for Improving the Efficiency and Reliability of Infrastructure

The construction industry has increasingly adopted digital construction processes and technologies, fueled in part by governmental mandates aimed at modernizing construction workflows. While these advancements promise efficiency across different phases of a project, the efficacy of the digitally generated information often remains contingent on its alignment with the specific information exchange requirements of individual organizations. Current efforts to establish interoperable data schemas have made strides, yet challenges persist, particularly when tailoring information to meet the unique needs of organizations responsible for the operation and management of built assets. This paper dissects the outcomes of standard digital construction processes applied to a linear infrastructure project, highlighting observed shortcomings such as information overload and the difficulty of adapting the information for asset management needs. Building upon these findings, this paper introduces a framework aimed at streamlining the production of essential project information. This framework was developed through a series of expert workshops and subsequently tested on a separate infrastructure project, offering insights into its potential benefits and limitations.

Abstract LB_B02: Novel PAMs from somatic mutations produce numerous pancreatic cancer-specific CRISPR-Cas9 targets for selective cell elimination: A novel gene therapy approach for cancer

Abstract Somatic mutations accumulate as we age and are mostly found within the noncoding regions which make up of 98% of the human genome. CRISPR-Cas9, on the other hand, can be designed to induce double strand breaks (DSBs) at specific locations in the genome, and DSBs are known to be cytotoxic. CRISPR-Cas9 requires the presence of a 3-5 nucleotide protospacer adjacent motif (PAM) to serve as a binding signal for Cas9, in which Cas9 would not bind nor cut the target in its absence. We hypothesized that we could identify a large number of somatic 5’-NGG-3’ PAMs that arise from single base substitutions (SBSs) in pancreatic cancers (PCs; e.g. NCG -> NGG), and these novel PAMs could serve as cancer-specific CRISPR-Cas9 targets for selective cell elimination. First, we performed whole genome sequencing (WGS) of three PC cell lines and their corresponding normal cell lines followed by tumor-normal (T-N) subtraction to identify somatic SBSs. PAMfinder, a software designed for somatic PAM discovery, was executed to identify somatic PAMs in each case. On average, 4548 somatic SBSs were found per PC case, in which 417 of them produced somatic PAMs (9.2% of total SBSs). PAMs with >95% variant allele frequency (VAF) and that produced sgRNAs with minimal off-target activity (based on CRISPOR) were further validated through Sanger sequencing, which resulted in an average of 32/33 confirmed targets per cell line. Mutational signature analyses also revealed that clock-like signatures were predominant, suggesting that aging itself could give rise to novel PAMs. We subsequently tested the specificity and selectivity of our patient-specific sgRNAs derived from two PC cases and showed that on-target mutations were only detected in the target cell lines and not in the corresponding normal or other PC cell lines lacking the targets. This result was further substantiated by comprehensive WGS analyses in a negative control cell line which demonstrated no off-target activity. Then, two PC cell lines were co-cultured and transduced with patient-specific sgRNAs identified from one of the PC cell lines, and showed >75% selective cell killing via flow cytometry. Finally, to examine the prevalence of somatic PAMs in different tumor types, we obtained 591 T-N subtracted variant call files from ICGC and performed tumor purity correction and PAMfinder analyses for each sample. We found that in two separate PC projects (APGI-AU and PACA-CA), the number of novel PAMs were 703 (N=44) and 863 (N=130), respectively, on average; in the lung cancer (LUCA-KR) and esophageal cancer (OCCAMS-GB) projects, an average of 3319 (N=29) and 4739 (N=388) novel PAMs were discovered, respectively. Overall, our results showed that adult solid tumors harbor hundreds, if not thousands, of somatic PAMs, and these PAMs could serve as novel CRISPR-Cas9 targets to selectively kill cancer cells. Citation Format: Selina Shiqing K Teh, Kirsten Bowland, Alexis Bennett, Eitan Halper-Stromberg, Alyza Skaist, Aparna Pallavajjala, Jacqueline Tang, Fidel Cai, Hong Liang, Sarah Wheelan, Robert B Scharpf, Nicholas J Roberts, James R Eshleman. Novel PAMs from somatic mutations produce numerous pancreatic cancer-specific CRISPR-Cas9 targets for selective cell elimination: A novel gene therapy approach for cancer [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr LB_B02.

Monitoring the nutrient content of packaged food: Design of the German product monitoring

Abstract Introduction To review ongoing reformulation efforts and identify further leverage points for reducing the sugar, fat, or salt content in packaged food, an overview of the nutrient content of nationally available packaged food is essential. This can be achieved through a regular product monitoring, as it is conducted in Germany. Methods & Data Analysis In Germany, the product monitoring started in 2016 with a market overview of the energy and nutrient content of 19 food groups. Since 2019, it has been continued as an annual monitoring of selected frequently consumed food groups. A special emphasis within each food group lies on products targeting at children. Product information such as mandatory nutrition declaration and ingredient list is predominantly gathered manually from manufacturers’ websites and managed with FoodCASE. To facilitate data collection, a system to extract and organise the relevant food product information from websites automatically is currently being developed in a separate research project. The system combines web-scraping, artificial intelligence, generic and rule-based approaches to compile and compare data over time. Analyses of the energy and nutrient content are done on the level of food groups and subgroups. Range, mean, median, and quartiles are calculated and shown in tables and boxplots. A monitoring interval of 2-3 years allows analysing for significant changes over time by using Welch's t-test or -ANOVA. Furthermore, monitoring data is introduced into the EU Joint Action Best-ReMaP, which aims to implement a standardized monitoring system across the EU to better evaluate different national reformulation efforts. Conclusions Continuous product monitoring as done in Germany is an essential and effective tool to assess and guide ongoing reformulation efforts. Steps towards more harmonized monitoring across Europe will help to compare nutrient content of packaged food between different countries and identify best practices in reformulation.

Caught Between Epistemology and Field-Conditions: Travails of Young Qualitative Policy Researchers in India

The qualitative approach is immensely helpful in policy research as it provides a comprehensive, contextually grounded, and nuanced understanding of policy processes and issues. It is characterized by certain epistemological imperatives that demand the collection of rich, diverse data and a thick description of the context. However, conducting fieldwork to collect data required to fulfill these imperatives poses diverse and stiff challenges, especially for young policy researchers in the Indian context. In this background, this paper argues that, while epistemological principles require qualitative researchers to collect rich and diverse data, the researcher’s social identity and the socio-political ground reality in the field pose significant challenges for young policy researchers in collecting field data. More specifically, the paper discusses the challenges posed by different elements of the researcher’s social identity like economic class, caste, gender, and education. It also discusses the challenges posed by different elements of the socio-political ground reality in the field such as socio-economic inequality, gatekeeping, and by politics played by field-level actors like primary contacts, community leaders, participant groups, and public bureaucrats. It draws from the thematic analysis of fieldwork experiences documented (in the form of fieldnotes and different types of memos) by three Indian researchers (including two females) who were collecting qualitative data for three previous and separate qualitative research projects. This fieldwork was carried out in two different states in India. The discussion in this paper will prove helpful, especially to young qualitative researchers, in planning and executing their fieldwork in developing countries, especially in India.

Court rules against housing authority

The plaintiff was a former New York City Housing Authority janitor who filed a suit after she was fired in 2017, and one of her claims was a hostile work environment, in violation of Title VII because of her status as a Chinese American, at each of three separate housing projects where she worked.

Designing and manufacturing custom-made 3D printed assistive devices: A comparison of three workflows

BACKGROUND: Do-it-yourself technologies such as 3D printing offer interesting opportunities for creating custom-made assistive devices for people with disabilities. Although these opportunities are increasingly acknowledged, it remains unclear how 3D printing technology should be implemented in assistive devices delivery processes. OBJECTIVE: In three separate action research projects carried out in Belgium, Italy and The Netherlands, workflows were designed and evaluated that incorporate 3D printing as a standard option for providing clients with suitable assistive devices. METHODS: In this paper we describe and compare the three workflows that were conceived simultaneously, yet independently from each other. RESULTS: Based on the evaluations of these workflows, and the experiences of the researchers who developed the workflows, we provide recommendations for implementing 3D printing as a common approach in assistive device delivery processes in practice. Most importantly, designing and manufacturing should be done by means of a client-centered co-creation process by interdisciplinary teams of clinicians, clients, and 3D printing experts. We provide several recommendations for facilitating and supporting collaborations within such teams. CONCLUSIONS: The three workflows presented in this paper are strikingly similar and therefore provide a convincing starting point for interdisciplinary design teams who wish to embark on 3D printing custom-made assistive devices.

Legal principles of venture investment into startups as innovative product

Problem setting. The article is focused on determining legal principles of venture investment into startups as innovative product. The relevance of the topic is due to the fact that the main obstacle for the development of startups in Ukraine is the lack of permanent and systematic investments, the development of venture entrepreneurship, scientific research in the area of venture investment. analysis of recent researches and publications. Economists, in particular I. V. Lytvyn and Y. V. Bulak, drew attention to the state of venture capital entrepreneurship under martial law. The problem of venture capital investment was studied in detail by Y. M. Zhornokuy, who determined that the use of venture capital to invest in innovation in Ukraine is underdeveloped. According to B. Derevyanko, Ukrainian venture capital funds do not take into account the peculiarities of the nature of venture capital investment. The origins of the legal support of venture capital investment were identified by D. V. Zadychailo. The implementation of venture relations through investment agreements was the subject of research by O. E. Simson. Purpose of the research is to determine legal principles of venture investment into startups as innovative product. article’s main body. Venture entrepreneurship is activity with a special risk, since it is aimed at making investments into scientific and technical result intelligence. It has been emphasized that venture investment in terms of the martial law acquires a special scientific and practical importance for the post-war recovery of the Ukrainian economy and the development of society. It has been proved that startup’s criteria established by the legislator are close to the criteria for protecting the objects of intellectual property rights, in particular objects of industrial property (inventions, utility models). Therefore, one of the startup’s legal features is its correlation with the corresponding object of intellectual property law, which has received state registration. At the same time, the startup, despite receiving legal protection, is not embodied in a certain production, scientific and practical intelligence is still being conducted in its regard. It has been emphasized that the lack of a sustainable practice of using startups indicates the existence of risk regarding its investment. As a result, a startup can be defined as an object with elements of risk for its further implementation. It has been argued that startups can be considered as innovative product. It has been revealed that a startup’s implementation as an innovative product has certain specific features stipulated by the economic cycles (stages) of its creation and implementation. Each of the identified stages has legal significance, since it can be correlated with the competitive selection of startups to receive investments, in particular due to financial state support. At the same time, both scientific technical and entrepreneurial activities in the field of venture investment take place at each of the stages of a startup’s implementation as an innovative product. The importance of the activities of the Innovation Development Fund (Ukrainian Startup Fund) has been emphasized, which allows startups to receive state investment, since investing into this innovation is significantly risky. Therefore, the state creates appropriate stimulating mechanisms for the creation of the startup market. conclusions and prospects for the development. Summarizing the above, we offer conclusions that startup is a new legal category that needs further scientific studies. Based on the conducted research, we have distinguished the following characteristics of a startup as an object of rights: it is the result of scientific and technical creativity; has state registration as an object of intellectual property rights; has not been implemented into systematic production; has novelty for the relevant market of goods and services; refers to objects with increased risk; has the dual legal nature both of an innovation and a separate investment project. We have offered the division of startups depending on intellectual property institutions: a) startups in the field of copyright (computer software, databases); b) patent and legal startups (inventions, utility models, industrial designs); 3) startups in the field of non-traditional intellectual property objects (new varieties of plants, layout of an integrated microcircuit).

RELATIONSHIP «RARE-EARTH METALS – ENERGY TRANSITION IN THE CONTEXT OF FULL CYCLE PROJECTS

The article examines the development of the rare earth industry in Russia. Russia has a significant resource base of this type of mineral raw materials, but it does not fully use the existing potential. Russia exports semi-products of low processing, and imports goods containing rare earth elements with high added value. The key problem of the industry is the insignificant domestic demand for rare earth metals. The growing interest in the world in renewable energy sources makes new opportunities for the development of the Russian rare earth industry and gives a chance for the transition of the Russian economy to a new technological order. At the heart of the policy to create demand for rare earth products within the country, the authors propose to use a theoretic approach based on the consideration of full-cycle projects. Three main features characterize this approach. Firstly, our approach is an extension of the traditional project approach and takes into account not so much the local aspects of a separate project for the extraction and processing of ore, but its integration into the country's economy through a system of intersectoral interactions (multiplicative effects). Secondly, as the demand for products within the country grows and the scale of the use of products based on rare earth metals expands, the process of “learning” is launched - the costs of mining, processing and production of final products are reduced. Thirdly, the approach proposes to consider rare earth ores in dumps as pseudo-financial assets with the ability to manage them as traditional economic asset

19세기 말 서원 훼철령 이후 대응과 변화

The Chugyechu clan gradually promoted royal family promotion projects by taking advantage of the royal family's preferential policies starting from the reign of King Yeongjo. As a result, their status as an aristocratic family was strengthened after the mid-19th century. After tracing, the Chu family was divided into Joseon and China, and after the Japanese invasions of Korea, the Chu Yu-gye family settled in Korea. However, because there was no distinct person, as generations passed, the clan was divided and the family lineage became weaker.
 However, after the mid-19th century, the scattered descendants were integrated to form a major head family, the family lineage was established, and the family's status steadily increased through various ancestral rite businesses. As a result, after destroying the headquarters, Daewongun was able to gather the public opinion of Cho clans and Confucian scholars across the country and launch a campaign to track down the Order of Munmyojong. Although Munmyojong failed, it served as an opportunity to publicize the chase throughout the country. Afterwards, Jo's descendants expanded their social network by interacting with influential families in each region through political and social connections, and each family carried out separate projects to honor their ancestors. As a result, Inheungseowon was rebuilt in Yeongnam in 1938 with the active cooperation of prominent families and Confucian scholars. After Daewongun's order to demolish the Seowon, the reconstruction of the Chugyechu Seowon in a situation where the Seowon was hardly rebuilt shows that the status of the Chugye Scandal has increased accordingly. The improvement of the status of the Chugyechu clan was possible not only because of projects to honor ancestors, but also because of the enlightenment and active social activities of descendants.