Open Model Research Articles

City-Level Solar Photovoltaic Potential Using Integrated Surface Models and Himawari Satellite in Jakarta and Bandung Indonesia

This research focuses on the detailed modeling of solar PV (Photovoltaic) in urban areas by integrating a detailed reconstructed digital surface model (DSM) and high-temporal-resolution satellite data. This study introduces enhancing method for open digital surface model from medium to high resolution to capture building height details, and integrating the new DSM with high-temporal satellite data to get detail spatial and temporal resolution of solar PV. The DSM reconstruction, building heights are determined using a combination of multi-data and multi-machine learning regression approaches to achieve building height results closely aligned with actual height. In Jakarta, building heights ranged from 5 to 223 m, while in Bandung, they ranged from around 3.58 to 254 m. The combination scenarios had a mean absolute error of 1.584 m, and the coefficient of determination (R2) was 0.754. The integration of new DSM detail data and high-temporal data employs an approach to integrate surface solar irradiance by shadow, sky view factor, and reflectance irradiance from surrounding object. The annual average energy potential in Jakarta and Bandung ranges from 260 to 420 W/Wp. Areas near tall buildings exhibit lower potential because of the shadow effect and sky view factor. This research hopefully can contribute to urban planning for carbon neutrality by providing a more detailed understanding of solar PV potential in urban areas in the absence of detailed data limitations.

Causes and consequences of language manipulation with the concept of «patriotism» and criteria its distinction with nationalism

INTRODUCTION. The concepts of “nationalism” and “patriotism”, “nazification” and “denazification” are used in the modern context without taking into account the history of their formation, which increases the possible escalation of social conflicts. The purpose of study – is to identify the causes and consequences of linguistic manipulation of the concept of “patriotism” and the criteria for its distinction with the concept of “nationalism”.MATERIALS AND METHODS. The studied facts of history examine the stages of development of nationalism and patriotism in the countries of Europe, the Russian Empire, the USSR and in the post-Soviet space. To study their interaction, a comparative historical method of understanding reality is used.RESEARCH RESULTS. The types of states that are built on different principles depending on the attitude of the power elites to patriotism and nationalism are analyzed: (1) protonationalism of Ancient Greece, formed on the basis of slavery; (2) nationalism in Europe with an amendment to the inviolability of property and individual freedom in bourgeois states, justifying the colonization of “unenlightened” peoples; 3) patriotism in the Russian Empire, established on the basis of Orthodoxy and citizenship, taking into account national and territorial covertness; (4) Soviet patriotism, built on the ideology of internationalism, equality and unity of national republics; (5) neopatriotism, which excludes nationalism as an ideology of superiority “titular” of a nation or state.CONCLUSION. The signs of nationalism are determined, revealing its destructive essence and making it possible to consolidate the social essence of patriotism in the structure of personal, state and interethnic relations. the significance of the model of openness of cultures, economies, religions and languages that create conditions for the formation of multipolar civilizations is substantiated.

Implementing open innovation in a closed biopharmaceutical industry

Over the last decade, biopharmaceuticals’ research, development, production, and sale have involved high risks and costs for companies. Hence companies have moved toward reaping the benefits of open innovation models. Open innovation is a paradigm that forces the company to use internal and external ideas to accelerate and upgrade its technology and product innovation. This study attempts to identify and explain the open innovation model in the biopharmaceutical industry by studying the successful experiences of two prominent Iranian companies. Also, 22 companies were identified and 19 questionnaires were completed finally. The results of this study showed that the value chain in this industry consists of four major links (including research/discovery, development, production, and sales) and nine sub-links. Based on this, the conceptual model of open innovation in the value chain of Iran's biopharmaceutical industry is drawn with emphasis on four main actors including foreign patent companies, accelerators, large bio-companies, and distribution companies. Meanwhile, despite numerous problems, this industry has been able to move in the direction of open innovation.

Relation Extraction in Underexplored Biomedical Domains: A Diversity-optimised Sampling and Synthetic Data Generation Approach

Abstract The sparsity of labeled data is an obstacle to the development of Relation Extraction (RE) models and the completion of databases in various biomedical areas. While being of high interest in drug-discovery, the literature on natural products, reporting the identification of potential bioactive compounds from organisms, is a concrete example of such an overlooked topic. To mark the start of this new task, we created the first curated evaluation dataset and extracted literature items from the LOTUS database to build training sets. To this end, we developed a new sampler, inspired by diversity metrics in ecology, named Greedy Maximum Entropy sampler (https://github.com/idiap/gme-sampler). The strategic optimization of both balance and diversity of the selected items in the evaluation set is important given the resource-intensive nature of manual curation. After quantifying the noise in the training set, in the form of discrepancies between the text of input abstracts and the expected output labels, we explored different strategies accordingly. Framing the task as an end-to-end Relation Extraction, we evaluated the performance of standard fine-tuning (BioGPT, GPT-2, and Seq2rel) and few-shot learning with open Large Language Models (LLMs) (LLaMA 7B-65B). In addition to their evaluation in few-shot settings, we explore the potential of open LLMs as synthetic data generators and propose a new workflow for this purpose. All evaluated models exhibited substantial improvements when fine-tuned on synthetic abstracts rather than the original noisy data.We provide our best performing (F1-score = 59:0) BioGPT-Large model for end-to-end RE of natural products relationships along with all the training and evaluation datasets. See more details at https://github.com/idiap/abroad-re.

Experimental and Numerical Investigation of Roughness Structure in Wind Turbine Airfoil at Low Reynolds Number

This paper experimentally and numerically investigates the effects of suction side surface roughness on the aerodynamic performances of the NACA 0015 turbine blade profile. Three different NACA 0015 turbine blade configurations, which are smooth (K0), single roughness (K1), and double roughness (K2), are considered. The experimental studies were conducted using the HM-170 GUNT open wind tunnel model. The aerodynamic characteristics of these three blade configurations are evaluated in terms of their lift coefficient (CL), drag coefficient (CD), and aerodynamic efficiency (CL/CD). The maximum CL (CL,max) for K0 was obtained at 25°, whereas the CL,max angles for the K1 and K2 roughness blade profiles were reduced to 22.5°, utilizing the rough surfaces on the suction side. The experimental analysis revealed that the K2 profile demonstrated a 21% and 19% enhancement in maximal CL over the K0 and K1 profiles, respectively. The highest CL/CD was observed with K1, except at low attack of angle (αoα), where the smooth blade profile resulted in slightly better performance. Experimental analysis showed peak CL/CD at αoα of 7.5° for K0, and 12.5° for both K1 and K2, with K1's optimal CL/CD being 2.85% and 8.5% higher than K0 and K2, respectively. Numerical analysis indicated that the CL/CD,avg for K1 was observed to be 11% and 8% higher than that of K0 across all αoα.

Informality, rule-of-thumb consumers, and the effectiveness of monetary policy in emerging economies

This paper investigates how the presence of a large fraction of rule-of-thumb consumers and an informal sector and (henceforth, informality) impact on the effectiveness of monetary policy in developing/emerging economies. We develop a small open economy New-Keynesian model, which is estimated using data on selected Sub-Saharan African countries where the coexistence of these two frictions is widespread - Burundi, Malawi and Rwanda. The results reveal that (i) rule-of-thumb consumption enhances the dominance of demand shocks and makes inflation stabilization a challenge; (ii) the presence of an informal sector causes supply shocks to be dominant, creating a trade-off between stabilizing inflation and output; (iii) rule-of-thumb consumption weakens the transmission mechanism of monetary policy while its interaction with informality worsens the situation in most of the selected countries; (iv) informality amid a large population of rule-of-thumb consumers causes the nominal interest rate to counterintuitively decline in response to a contractionary monetary policy shock; (v) in some of the selected countries, a positive productivity shock counterintuitively triggers a nominal exchange rate appreciation when informality interacts with rule-of-thumb consumption behavior; (vi) the coexistence of informality and rule-of-thumb consumption behavior amplifies country-risk premium shocks and; (vii) rule-of-thumb consumption behavior is welfare enhancing. These findings are informative to policymakers, particularly in emerging economies, on the priority reforms as they transition to inflation targeting frameworks. Direct policy implications emerge regarding financial inclusion, the size of the informal sector, and farm input subsidy programs.

Research on Hospital Archive Management from the Perspective of Public Administration

This paper explores the transformation of hospital archive management from a public administration perspective, emphasizing the shift towards an open model and public administration paradigm. By analyzing the concepts of publicness, service-orientedness, and collaborative governance, it proposes new management ideas of public responsibility, comprehensive development, and fair service. It also introduces practical paradigms such as document integration, resource management, and public participation, as well as implementation paths for enhancing awareness, institutional construction, cultural creation, and mechanism improvement. The aim is to promote the modernization of hospital archive management through the combination of theory and practice, efficiently serving society and public health.

Power system investment optimization to identify carbon neutrality scenarios for Italy

In 2021 the European Commission has proposed the Fit-for-55 policy package, requiring European countries to reduce their CO2 emissions by 55% with respect to 1990 by the year 2030, a first step to achieve carbon neutrality by 2050. Energy system modeling can be a valuable tool for national policymakers to choose the most appropriate technologies to achieve these goals efficiently. This article presents a model of the Italian power system realized employing the open energy modeling framework, Oemof. A linear programming optimization is implemented to evaluate how to minimize system costs at decreasing CO2 emissions in 2030. The developed tool is applied to evaluate different research questions: (i) pathway towards full decarbonization and power self-sufficiency of the electricity sector in Italy, (ii) relevance of flexibility assets in power grids: li-ion batteries, hydrogen storage and transmission lines reinforcement. A 55% CO2 emissions reduction for the actual Italian power sector can be achieved through an increase of 30% of the total annual system cost. Achieving complete decarbonization and self-sufficiency increases significatively annual expenditures. However, cost mitigation is plausible through the integration of sector coupling methodologies or the adoption of a broader spectrum of technological solutions. Flexibility measures appear instrumental for decarbonization, particularly transmission lines, demanding a substantial expansion beyond the stated plans for 2030. This infrastructure is crucial in Italy to facilitate the transfer of renewable electricity generated in the Southern regions to the Northern areas, where a large portion of the electricity demand is located.

Inherent Thermal-Noise Problem in Addressing Qubits

Qubit-specific measurement in a superconducting quantum processor requires physical interconnects that traverse 4 orders of magnitude in temperature from 293 K to 10 mK. Although the quantum processor can be thermalized and shielded from electromagnetic noise, the interconnects themselves introduce an unavoidable remote heat bath that causes decoherence of quantum states. In the present work, we report quantitative and device-independent measurements of the power radiated to the quantum processor from its control lines. Our results have been obtained using a calibrated bolometer that operates within a millikelvin environment with time-resolved measurement capability. In the limit of zero applied power, the noise power emitted to the quantum processor is equivalent to that of a blackbody with temperature 63–71 mK for the prototypical drive lines in the study. Experimentally, we increase the applied power of a simulated control signal to map out the resulting temperature rise and thermal time constant of five prototypical drive-line varieties. We input the data to an open quantum system model to demonstrate the trade-off between dissipated signal power, transmon-qubit lifetime, pure dephasing, gate fidelity, and the implied decoherence rates due to self-heating during microwave operations. Beyond explaining dephasing rates observed in the literature, our work sets the stage for accurate noise modeling in novel quantum computer interfacing methods due to our device-agnostic approach. Published by the American Physical Society 2024

In Situ Imaging of Parachute Textile Micromechanics Under Tensile Load

Micromechanics of parachute fabrics under tensile loads are studied using in situ x-ray microtomography. Results are presented for two nylon textiles commonly used in parachute systems, MIL-C-7020H Type III and MIL-C-44378(GL) Type II. Textiles are subjected to incremental tension using a custom apparatus that loads the fabric radially, and the microstructure is imaged sequentially at steady load conditions. Microtomography images are processed using learning-aided segmentation and a custom processing pipeline that tracks the locations and morphological properties of individual tows on 3D datasets. Results are used to reconstruct tow microscale properties and meso-scale strains. Our findings reveal a direct relation between the fabric architecture and the meso-scale mechanics. Warp tow pretensioning during manufacturing is found to affect decrimping and the anisotropy of the textile strains. Areal porosity increase with tension is quantified, and a geometric model for pore opening under incremental load is validated.

Activity-based and agent-based transport model of Melbourne: an open multi-modal transport simulation model for Greater Melbourne

Activity- and agent-based models for simulating transport systems have attracted significant attention in recent years. However, building these types of models at a city-wide level and including motorized (i.e. cars and public transport) and non-motorized (i.e. walk and bicycle) modes of transport is a complicated and involved task. This paper presents an open workflow for creating large-scale multi-modal agent-based transport simulation models. The workflow brings together a number of external tools, for example, an activity-based demand generation tool and a road network generation tool, and a set of tools developed for the agent-based model parameter estimation, calibration, and simulation post-processing. We used this workflow to create an activity- and agent-based model for Melbourne and compared the output of the simulation model with observations from the real world in terms of mode share, road volume, travel time, and travel distance. Through these comparisons, we showed that our model is suitable for studying mode choice and road usage behavior of travelers. The calibrated model could be used to test road network change interventions. In addition, a similar workflow can be applied for building simulation models for other cities or could be expanded to include more complicated travel behaviors.

Methods of countering attacks and organizing the choice of channel protection tools when controlling aviation robotic devices

The purpose of the research is identification of organizational and technical methods of countering attacks on command and telemetry data transmission lines between aviation robotic devices and ground control points, as well as the formation of comprehensive information protection of the communication channels under consideration.Methods. The scientific article substantiates methods for mitigating and countering attacks at the physical level of the ISO/OSI open systems interaction model for organizing communication using the MAVLINK protocol for the purpose of controlling aviation robotic devices (noise-resistant coding with a high code rate (using the example of the most common code - Viterbi), extension method Frequency Hopping Spectrum (FHSS), Direct Sequence Spread Spectrum (DSSS), Multiple Input Multiple Output (MIMO) technology). A method for organizing the selection of protection and countermeasures when controlling aviation robotic devices is outlined, which consists of assessing the risks and consequences of the implementation of vulnerabilities in order to introduce countermeasures there and in such quantities that they have the greatest benefit.Results. The article discusses the main possibilities for intentional interference on the control and data transmission channels of consumer aviation robotic devices, an algorithm for assessing the risk of "leaving the route" is considered; a risk assessment option is provided in relation to the risk of an aircraft going off route, indicating the name of the attack, its likelihood, impact and resulting risk, as well as the acceptability of this risk and recommendations regarding the urgency of mitigating it; recommendations for countermeasures are presented in accordance with the acceptability of likelihood and impact; describes the relationship between risk and countermeasures used to reduce unauthorized exposure, in accordance with weighting coefficients.Conclusion. The scientific article discusses the main methods of countering attacks and unauthorized access when controlling autonomous robotic devices. The risk coefficients of attacks and countermeasures taken are considered.

Analysis of methods of data flow management in mobile radio communication means

The article analyzes the existing methods of managing data flows in mobile radio communications. During the analysis, the peculiarities of the functioning and construction of these networks were considered. It has been established that such networks have features different from other networks, such as mobility, dynamic topology, independent organization, use of mobile means of communication, lack of fixed data transmission routes, etc. The task of providing routing in mobile radio communication devices, mobile radio networks, and the types of routing in communication networks are considered. The conditions for the implementation of the routing task and the features that characterize the routing process have been established. The levels of the OSI open systems model and the most well-known protocols that work at these levels and are used in data flow management are considered. Data flow management methods are classified by type and a list of requirements for the process of data flow transmission in mobile radio networks is defined, taking into account the peculiarities of the functioning of mobile radio communication means, which must be taken into account when building a mobile radio network management system. It has been established that at the current stage of information technology development, data flow management methods are mostly adapted for use in computer, wired or fixed networks and do not take into account the conditions of use in mobile radio communication devices. It has been established that the construction and operation of an effective data flow control subsystem in the control systems of mobile radio networks and mobile radio communication means requires the use of the latest technologies and modern approaches in the development of data flow control methods and methods that will ensure the functioning of the corresponding data flow control subsystem. When choosing protocols, methods, methods of managing data flows, it is proposed to focus on adaptation, modification of approaches or their combined use based on the target function, taking into account the peculiarities of the functioning of mobile radio networks and mobile radio communication means.

Quantifying the abundance and survival rates of island-associated spinner dolphins using a multi-state open robust design model

Spinner dolphins (Stenella longirostris subsp.) occupy the nearshore waters of several Hawaiian Islands. Due to their constrained behavioral pattern and genetic isolation, they are vulnerable to anthropogenic threats. Their occurrence and behavior are well-described, yet a lack of data on their abundance and survival rates hinders optimal conservation action. Using design-based photo-identification surveys, this study estimated the abundance, apparent survival, and emigration of spinner dolphins off the Waiʻanae Coast of Oʻahu through multi-state open robust design (MSORD) and POPAN modelling. Eight seasonal field seasons, (two winter, spring, summer, and autumn) each comprised of six surveys of the study area, were completed during two consecutive years. Seasonal abundance estimates derived from the best fitting model ranged from 140 (± 36.8 SE, 95% CI 84–232) to 373 (± 60.0, 95% CI 273–509) individuals and were lowest during winter seasons. The MSORD estimated a survival rate of 0.95 (± 0.02 SE) and a Markovian pattern of temporary emigration. POPAN modelling estimated a super-population size of 633 (± 78 SE, 95% CI 492–798), reflecting the total number of individual dolphins that used the study area during the entire study period. Additional research on circum- and inter-island dolphin movements around and between Oʻahu and the Maui Nui region may shed light on both seasonal movement patterns and overall abundance for the Oʻahu/4-Islands stock. This work represents the first systematic mark-recapture effort to assess the abundance and survival rates of these highly exposed dolphins, providing valuable insights for conservation and management.

Open Access Models of Russian Academic Journals

Open access (OA) to publications has been a global trend in publishing academic journals for a long time. The number of OA journals, including Russian ones, is growing steadily. The purpose of this study was to determine the main trends in the implementation of open access publishing models in Russian research journals. The article presents the results of a study of 396 journals included in the Russian Science Citation Index database: title of a journal; website address; international classification code (OECD group); quartile; Science Index indicator; open access model; license type; section of a journal’s website that contains information about the absence or presence and amount of an article processing charge (APC). It is concluded that the majority of journals implement Bronze OA which, firstly, does not comply with the key principles of open access, because it does not use open licenses, and, secondly, does not provide any guarantees that open access will continue to be open. The lack of accessible and transparent information about the conditions for further use of publications can create serious legal issues for the licensee. In turn, it will most likely be a problem for authors to calculate the amount of publication fee.

Imperfect financial markets and the cyclicality of social spending

This paper explores the link between default risk and fiscal procyclicality. We show that countries with higher sovereign risk have a more procyclical fiscal expenditure policy, which is driven mostly by transfers. We build a small open economy model with income inequality, social transfers, and default risk to rationalize this fact. Without default risk transfers are countercyclical, inequality is procyclical, and external debt is used to smooth distortionary taxation. With default risk, transfers account for most of fiscal adjustment because taxation becomes costly for the government. Transfers become procyclical and inequality worsens during times when risk premia are high. We confirm the predictions of the model in the data: in recessions in economies with default risk, transfers take the bigger burden relative to government consumption, whereas the opposite is true in economies with low default risk.

The AI community building the future? A quantitative analysis of development activity on Hugging Face Hub

Open model developers have emerged as key actors in the political economy of artificial intelligence (AI), but we still have a limited understanding of collaborative practices in the open AI ecosystem. This paper responds to this gap with a three-part quantitative analysis of development activity on the Hugging Face (HF) Hub, a popular platform for building, sharing, and demonstrating models. First, various types of activity across 348,181 model, 65,761 dataset, and 156,642 space repositories exhibit right-skewed distributions. Activity is extremely imbalanced between repositories; for example, over 70% of models have 0 downloads, while 1% account for 99% of downloads. Furthermore, licenses matter: there are statistically significant differences in collaboration patterns in model repositories with permissive, restrictive, and no licenses. Second, we analyse a snapshot of the social network structure of collaboration in model repositories, finding that the community has a core-periphery structure, with a core of prolific developers and a majority of isolate developers (89%). Upon removing these isolates from the network, collaboration is characterised by high reciprocity regardless of developers’ network positions. Third, we examine model adoption through the lens of model usage in spaces, finding that a minority of models, developed by a handful of companies, are widely used on the HF Hub. Overall, the findings show that various types of activity across the HF Hub are characterised by Pareto distributions, congruent with open source software development patterns on platforms like GitHub. We conclude with recommendations for researchers, and practitioners to advance our understanding of open AI development.

Predator presence influences survival and behavior of translocated stream fish in ponds

Abstract Small artificial impoundments such as farm ponds have recently been recognized as potential habitat for threatened native fish species. However, factors influencing translocation or colonization success into these environments, including connectivity to stream networks and interactions with existing fish community, are largely unknown. In this study we conducted a controlled experiment to quantify the influence of piscivorous Largemouth Bass Micropterus salmoides on the survival of a translocated native minnow species that we used as a surrogate for federally endangered Topeka Shiner Notropis topeka. We translocated or released 100 Bluntnose Minnow Pimephales notatus into each replicate treatment ponds with and without Largemouth Bass in the summers of 2020 and 2021. Each minnow was implanted with a passive integrated transponder (PIT) tag. Translocated populations were monitored using stationary and mobile passive integrated transponder antennas and estimates of apparent survival and probability of detection for each pond were derived from open population mark-recapture models. Apparent survival was nearly two times higher in ponds without bass suggesting predation by bass leads to higher mortality. Additionally, probability of detection was nearly 10 times higher in ponds without bass, suggesting reduced movement of translocated minnows when bass were present. While the direct effect of mortality impacts translocated populations, the indirect effect of altered behavior may also be impactful on translocation success. These results confirm that Largemouth Bass can limit the success of translocated minnow species.

MODL-11. LOW-GRADE GLIOMA 3D PATIENT-DERIVED ORGANOID PLATFORM AS TRANSFORMATIVE TOOL FOR TUMOR BIOLOGY AND TRANSLATIONAL RESEARCH

Abstract Unlike many high-grade tumors, low-grade glioma (LGG) has faced challenges in advancing scientific and clinical breakthroughs, affected by the limited capacity to develop representative preclinical tumor models. Major barriers to establishing traditional LGG cell culture systems have been cellular senescence and the need to introduce additional genetic modifications to obtain cultured growth. Such LGG models, while extremely valuable, require extensive periods for development and result in clonally selected lines which may not present the complexity of LGG tumor biology. To mitigate such challenges in LGG model development and address the need for three-dimensional tissue cultures, we have successfully generated organoids from fresh tissue specimens obtained from surgical resection. We have demonstrated success of this method on various pediatric brain tumor histologies and have expanded these approaches successfully to LGG. Through such efforts, we have developed 14 LGG tumors’ organoid models as well as other low-grade tumor’s models such as craniopharyngioma, schwannoma, meningioma, optic glioma, and oligodendroglioma. The tissue was processed immediately post-extraction and cultured in media solution on rotating platform. Organoid growth was observed within 1-3 weeks of initiation and tested for growth for up to 3 months. Phenotypic analysis revealed organoid cell composition representing clinical histology. The immune component was preserved in organoids for up to 40 days. MAPK pathway activity, a hallmark marker for KIAA-BRAF fusion positive pilocytic astrocytoma was preserved for up to 4 weeks. Our successful deployment of three-dimensional patient-tissue derived organoids provides for an efficient, simple workflow for the generation of unique and transformative preclinical models for the LGG field. Supported by the Children’s Brain Tumor network’s open science model, 3D organoids will provide investigations with broader resources for LGG tumor biology preclinical testing and support translational studies on behalf of the development of novel clinical trials.

A Strategy for Preparing Quantum Squeezed States Using Reinforcement Learning

AbstractA scheme leveraging reinforcement learning to engineer control fields for generating non‐classical states is proposed. It is exemplified by the application to prepare spin‐squeezed states for an open collective spin model where a linear control field is designed to govern the dynamics. The reinforcement learning agent determines the temporal sequence of control pulses, commencing from a coherent spin state in an environment characterized by dissipation and dephasing. Compared to the constant control scenario, this approach provides various control sequences maintaining collective spin squeezing and entanglement. It is observed that denser application of the control pulses enhances the performance of the outcomes. However, there is a minor enhancement in the performance by adding control actions. The proposed strategy demonstrates increased effectiveness for larger systems. Thermal excitations of the reservoir are detrimental to the control outcomes. Feasible experiments are suggested to implement this control proposal based on the comparison with the others. The extensions to continuous control problems and another quantum system are discussed. The replaceability of the reinforcement learning module is also emphasized. This research paves the way for its application in manipulating other quantum systems.