cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10057868
title: ВO-ПАРАМЕТРИЧЕСКИЙ АНАЛИЗ. АНАЛИЗ СИЛЫ ДИФФУЗИИ ВЕЙБУЛЛА В СОВРЕМЕННЫХ КЕРАМИЧЕСКИХ МАТЕРИАЛАХ.
DOI: 10.5281/zenodo.10057867
title: ВO-ПАРАМЕТРИЧЕСКИЙ АНАЛИЗ. АНАЛИЗ СИЛЫ ДИФФУЗИИ ВЕЙБУЛЛА В СОВРЕМЕННЫХ КЕРАМИЧЕСКИХ МАТЕРИАЛАХ.
DOI: 10.5281/zenodo.10057886
title: FOREIGN EXPERIENCES OF AGROTURISM ACTIVITY DEVELOPMENT AND APPLICATION OF ACTIVITY DEVELOPMENT MODELS IN THEM
DOI: 10.5281/zenodo.10057885
title: FOREIGN EXPERIENCES OF AGROTURISM ACTIVITY DEVELOPMENT AND APPLICATION OF ACTIVITY DEVELOPMENT MODELS IN THEM
DOI: 10.23728/b2share.4d664fbbf9ea42908adb32fb67cac166
title: EUDAT Brochure - B2HANDLE
DOI: 10.5281/zenodo.10057900
title: ASSESSMENT OF RESOURCE COMPETENCE IN THE DEVELOPMENT OF AGRO-TOURISM ACTIVITIES IN FERGANA PROVINCE
DOI: 10.5281/zenodo.10057899
title: ASSESSMENT OF RESOURCE COMPETENCE IN THE DEVELOPMENT OF AGRO-TOURISM ACTIVITIES IN FERGANA PROVINCE
DOI: 10.6084/m9.figshare.24427441.v2
title: 数据 （1）.xlsx

description: <b>Influences of phytoplankton, zooplankton, and bacteria on DMSP and DMS distributions in the South China Sea</b>
DOI: 10.6084/m9.figshare.24465607
title: 13 group discussion transcripts in MandarinFocus group discussions transcripts in Simplified Chinese

description: Original transcripts of 13 focus group discussions
DOI: 10.6084/m9.figshare.24466648
title: Medaka Gene Model version 2

description: Modified gene model derived from the GTF file from NCBI
DOI: 10.6084/m9.figshare.24466636
title: COI dataset Geisler et al. 2023

description: COI dataset for the delimitation of <i>Philonthus splendens</i> and <i>Philonthus sideropterus</i>
DOI: 10.6084/m9.figshare.24466636.v1
title: COI dataset Geisler et al. 2023

description: COI dataset for the delimitation of <i>Philonthus splendens</i> and <i>Philonthus sideropterus</i>
DOI: 10.14768/apd.cbqc-fv77
title: African Pollen Database: Nigeria_Adekanmbi_2007 4 months_trans fossil pollen dataset
DOI: 10.14768/apd.cx52-tn42
title: African Pollen Database: Nigeria_Njokuocha_TOTAL 1993_1994 fossil pollen dataset
DOI: 10.14768/apd.xfp8-y506
title: African Pollen Database: Nigeria_Agwu_TOTAL_1992_trans fossil pollen dataset
DOI: 10.5281/zenodo.10057914
title: CHOOSING THE DEVELOPMENT MODEL OF AGRO-TOURISM ACTIVITY IN THE REGIONS BASED ON ASSESSMENT OF THE EFFECTS OF FACTORS
DOI: 10.14768/apd.5a9s-ff40
title: African Pollen Database: Nigeria_Njokuocha_1993_1994_trans fossil pollen dataset
DOI: 10.14768/apd.1sg9-pw65
title: African Pollen Database: Niger_Caratini_1988_trans fossil pollen dataset
DOI: 10.14768/apd.2jk4-3z74
title: African Pollen Database: Niger_Caratini_TOTAL YEAR_1988_trans fossil pollen dataset
DOI: 10.14768/apd.yg04-hy45
title: African Pollen Database: Nigeria_Agwu_months_2001_trans fossil pollen dataset
DOI: 10.14768/apd.29fh-xn07
title: African Pollen Database: Tanzania_Schuler_2014_trans fossil pollen dataset
DOI: 10.5517/ccdc.csd.cc1z2l9y
title: CCDC 1819740: Experimental Crystal Structure Determination

description: Related Article: Qi-Pin Qin, Bi-Qun Zou, Fei-Long Hu, Guo-Bao Huang, Shu-Long Wang, Yun-Qiong Gu, Ming-Xiong Tan|2018|MedChemComm|9|1639|doi:10.1039/C8MD00247A
description: Related Article: Vladislav Yu. Kudrya, Tian-Yu Zhang, Ming-Xiong Tan, Antonina P. Naumenko|2023|J.Lumin.|266|120242|doi:10.1016/j.jlumin.2023.120242
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.34740/kaggle/dsv/6844891
title: 2021 World Population (updated daily)
DOI: 10.5517/ccdc.csd.cc2fmxcc
title: CCDC 2253463: Experimental Crystal Structure Determination

description: Related Article: Abdollah Neshat, Atiyeh Mahdavi, Mohammad Reza Yousefshahi, Mahdi Cheraghi, Vaclav Eigner, Monika Kucerakova, Michal Dusek, Forough Rezaie, Babak Kaboudin|2023|Inorg.Chem.|62|16710|doi:10.1021/acs.inorgchem.3c01759
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.14768/apd.ty45-kf64
title: African Pollen Database: South-Africa_Olatoyan_2023 fossil pollen dataset
DOI: 10.5517/ccdc.csd.cc2fhh4l
title: CCDC 2249209: Experimental Crystal Structure Determination

description: Related Article: Satbir Mor|2023|CSD Communication|||
description: Related Article: Satbir Mor, Ravinder Punia, Mohini Khatri, Deepak Kumar, Ashwani Kumar, Deepak Kumar Jindal, Namita Singh, Renuka Sharma, Manzoor Ahmed, Sanket Shukla, Komal Jakhar|2024|J.Mol.Struct.|1296|136759|doi:10.1016/j.molstruc.2023.136759
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fhh5m
title: CCDC 2249210: Experimental Crystal Structure Determination

description: Related Article: Satbir Mor|2023|CSD Communication|||
description: Related Article: Satbir Mor, Ravinder Punia, Mohini Khatri, Deepak Kumar, Ashwani Kumar, Deepak Kumar Jindal, Namita Singh, Renuka Sharma, Manzoor Ahmed, Sanket Shukla, Komal Jakhar|2024|J.Mol.Struct.|1296|136759|doi:10.1016/j.molstruc.2023.136759
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.34740/kaggle/dsv/6844897
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.6084/m9.figshare.24466891
title: 2023_INL320_Theme 8 slides_Part4(1).pdf

description: File
DOI: 10.6084/m9.figshare.24466891.v1
title: 2023_INL320_Theme 8 slides_Part4(1).pdf

description: File
DOI: 10.5281/zenodo.10057921
title: ГЕОГРАФИЯ ДАРСЛАРИДА МУСТАҚИЛ ТАЪЛИМНИ ТАШКИЛ ҚИЛИШДА ИНТЕРФАОЛ МЕТОДЛАРДАН ФОЙДАЛАНИШ
DOI: 10.5281/zenodo.10057920
title: ГЕОГРАФИЯ ДАРСЛАРИДА МУСТАҚИЛ ТАЪЛИМНИ ТАШКИЛ ҚИЛИШДА ИНТЕРФАОЛ МЕТОДЛАРДАН ФОЙДАЛАНИШ
DOI: 10.5281/zenodo.10057936
title: THE FORMATION OF CONCEPTS ABOUT FAMILY IN MYTHOLOGICAL IMAGINATIONS
DOI: 10.5281/zenodo.10057937
title: THE FORMATION OF CONCEPTS ABOUT FAMILY IN MYTHOLOGICAL IMAGINATIONS
DOI: 10.5281/zenodo.10057947
title: СОВРЕМЕННЫЕ ПРОБЛЕМЫ И ВОЗМОЖНОСТИ ИСПОЛЬЗОВАНИЯ КОНЦЕПЦИЙ ЛИДЕРСТВА В РАЗВИТИИ РЕГИОНОВ
DOI: 10.5281/zenodo.10057946
title: СОВРЕМЕННЫЕ ПРОБЛЕМЫ И ВОЗМОЖНОСТИ ИСПОЛЬЗОВАНИЯ КОНЦЕПЦИЙ ЛИДЕРСТВА В РАЗВИТИИ РЕГИОНОВ
DOI: 10.6084/m9.figshare.24100590
title: Supplementary Material for: Comparisons of insulin resistance- and steatosis-based scores in monitoring metabolic associated fatty liver disease treatment response

description: Background: Quantitative measurements of liver fat contents (LFCs) by magnetic resonance imaging derived-proton density fat fraction (MRI-PDFF) are accurate but limited by availability, convenience, and expense in the surveillance of metabolic associated fatty liver (MAFLD). Insulin resistance (IR) and steatosis-associated serum indices are useful in screening for MAFLD, but their value in monitoring MAFLD with or without chronic hepatitis B virus (CHB) infection remains unclear and we aimed to evaluate these scores in predicting changes in LFC. Methods: We conducted a prospective study between January, 2015 and December, 2021 with 620 consecutive participants with MAFLD (212 participants with CHB) who received a 24-week lifestyle intervention. The homeostasis model assessment of insulin resistance (HOMA-IR), HOMA2 index, Glucose insulin ratio, Quantitative Insulin Sensitivity Check Index, Fasting Insulin Resistance Index, Fatty liver index (FLI), Hepatic steatosis index (HSI), Liver fat score (LFS), Visceral Adiposity Index, and Triglycerides * Glucose were calculated. Results: When using endpoints such as LFS improvements of ≥5% or 10% or escalations of ≥5%, LFS had the highest area under the curve (AUC) values at all endpoints for MAFLD alone (0.756, 95% CI: 0.707–0.805; 0.761, 95% CI: 0.705–0.818; 0.807, 95% CI: 0.713–0.901, all P&lt;0.05, respectively). With CHB, the FLI (AUC=0.750) and HIS (AUC=0.770) exhibited the highest AUCs between the former two outcomes, respectively, but no score could predict LFC escalation of ≥5%. Conclusion: Among IR and steatosis scores, changes in LFC through lifestyle interventions can be captured with LFS possessing moderate precision but not in those with CHB.
DOI: 10.4121/4008754b-e1d5-4510-80d2-99604dd06731.v2
title: NEESI: Numerical Experiments of Estuarine Salt Intrusion dataset

description: The dataset contains the processed data of 1252 simulations using Delft3D Flexible Mesh (DFM) in which estuaries were designed using a parametric design. Every estuary design is based on thirteen (13) input parameters: three (3) boundary conditions, and ten (10) geomorphological characteristics. The output is represented by two (2) variables: (1) the salt intrusion length, 'L'; and (2) the salt variability, 'V'. Simulations are carried out over a span of nine (9) days of which the first eight (8) are considered spin-up; i.e., one (1) day of the simulation is used for further post-processing. The salt intrusion length is a depth- and tide-averaged estimation of the salt intrusion of this last day; and the salt variability an estimate of the difference between the maximum salinity and the minimum salinity over the tide, depth- and spatially- averaged. The various settings of the simulations are drawn using machine learning techniques.
DOI: 10.6084/m9.figshare.19915315
title: SARS-CoV-2 variants and COVID-19 vaccines: Current challenges and future strategies

description: The ongoing COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global threat. Despite strict control measures implemented worldwide and immunization using novel vaccines, the pandemic continues to rage due to emergence of several variants of SARS-CoV-2 with increased transmission and immune escape. The rapid spread of variants of concern (VOC) in the recent past has created a massive challenge for the control of COVID-19 pandemic via the currently used vaccines. Vaccines that are safe and effective against the current and future variants of SARS-CoV-2 are essential in controlling the COVID-19 pandemic. Rapid production and massive rollout of next-generation vaccines against the variants are key steps to control the COVID-19 pandemic and to help us return to normality. Coordinated surveillance of SARS-CoV-2, rapid redesign of new vaccines and extensive vaccination are needed to counter the current SARS-CoV-2 variants and prevent the emergence of new variants. In this article, we review the latest information on the VOCs and variants of interest (VOIs) and present the information on the clinical trials that are underway on evaluating the effectiveness of COVID-19 vaccines on VOCs. We also discuss the current challenges posed by the VOCs in controlling the COVID-19 pandemic and future strategies to overcome the threat posed by the highly virulent and rapidly transmissible variants of SARS-CoV2. The COVID-19 is a contagious respiratory disease caused by a virus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that emerged in 2019. The COVID-19 has now spread to all part of the world and has become a global threat. Even after the strict control measures and immunization programs to prevent the disease, COVID-19 is still causing destruction due to appearance of new strains of SARS-CoV-2 that transmit faster and capable of escaping the immunity. The faster spread of the new strains of viruses that cause more severe disease is the biggest challenge to control the COVID-19 pandemic by using the presently available vaccines. To control the COVID-19 pandemic we urgently need safe and effective vaccines against the corona viral variants. This can be achieved by tracking the appearance of new viral types, design and rapid production and supply of new vaccines against the virus. This article presents the latest information on the new types of SARS-CoV-2, and on the status of vaccine trials and their effectiveness against these viruses. Similarly, the information on the challenges posed by the new viral strains in controlling the COVID-19 and future strategies to overcome the threat posed by corona viruses is also provided.
DOI: 10.6084/m9.figshare.19915315.v1
title: SARS-CoV-2 variants and COVID-19 vaccines: Current challenges and future strategies

description: The ongoing COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global threat. Despite strict control measures implemented worldwide and immunization using novel vaccines, the pandemic continues to rage due to emergence of several variants of SARS-CoV-2 with increased transmission and immune escape. The rapid spread of variants of concern (VOC) in the recent past has created a massive challenge for the control of COVID-19 pandemic via the currently used vaccines. Vaccines that are safe and effective against the current and future variants of SARS-CoV-2 are essential in controlling the COVID-19 pandemic. Rapid production and massive rollout of next-generation vaccines against the variants are key steps to control the COVID-19 pandemic and to help us return to normality. Coordinated surveillance of SARS-CoV-2, rapid redesign of new vaccines and extensive vaccination are needed to counter the current SARS-CoV-2 variants and prevent the emergence of new variants. In this article, we review the latest information on the VOCs and variants of interest (VOIs) and present the information on the clinical trials that are underway on evaluating the effectiveness of COVID-19 vaccines on VOCs. We also discuss the current challenges posed by the VOCs in controlling the COVID-19 pandemic and future strategies to overcome the threat posed by the highly virulent and rapidly transmissible variants of SARS-CoV2. The COVID-19 is a contagious respiratory disease caused by a virus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that emerged in 2019. The COVID-19 has now spread to all part of the world and has become a global threat. Even after the strict control measures and immunization programs to prevent the disease, COVID-19 is still causing destruction due to appearance of new strains of SARS-CoV-2 that transmit faster and capable of escaping the immunity. The faster spread of the new strains of viruses that cause more severe disease is the biggest challenge to control the COVID-19 pandemic by using the presently available vaccines. To control the COVID-19 pandemic we urgently need safe and effective vaccines against the corona viral variants. This can be achieved by tracking the appearance of new viral types, design and rapid production and supply of new vaccines against the virus. This article presents the latest information on the new types of SARS-CoV-2, and on the status of vaccine trials and their effectiveness against these viruses. Similarly, the information on the challenges posed by the new viral strains in controlling the COVID-19 and future strategies to overcome the threat posed by corona viruses is also provided.
DOI: 10.4121/b008dd74-020d-4ea4-a8ba-7bb60769d224.v1
title: IndustReal Dataset of Egocentric Videos for Procedure Understanding

description: The multi-modal IndustReal dataset, accompanying our publication "IndustReal: A Dataset for Procedure Step Recognition Handling Execution Errors in Egocentric Videos in an Industrial-Like Setting". Check out our GitHub for additional details and read-me files.<br>Unlike currently available datasets, IndustReal contains procedural errors (such as omissions) as well as execution errors. A significant part of these errors are exclusively present in the validation and test sets, making IndustReal suitable to evaluate robustness of algorithms to new, unseen mistakes. Additionally, to encourage reproducibility and allow for scalable approaches trained on synthetic data, the 3D models of all parts are publicly available.
DOI: 10.5255/ukda-sn-855647
title: Migration for Inclusive African Growth, 2020-2021

description: The data comprises two forms of data collected across four African countries; Ghana, Nigeria, Mozambique and Kenya. These were: • The results of a business survey administered to both migrant-owned and non-migrant owned businesses in the four case study countries. The survey data is contained within an Excel spreadsheet with responses organised in four separate sheets by case study country. The code '777' is used in individual cells to denote that no answer was given for that particular question. • Transcripts of, or fieldnotes from, semi-structured interviews with migrants, organisations connected to migration, host nationals working for migrant businesses and selected government Ministries and Departments connected to migration policy in the four case study countries. The interview data is organised by country and sub-divided into five separate folders categorised by key informant group; i) Government Ministries, Departments and Agencies; ii) Civil Society Organisations, iii) Migrant Community Representatives (organisations or leaders); iv) Migrant Business Owners and; v) Host Nationals Working for Migrant Business owners.
DOI: 10.5281/zenodo.10057915
title: CHOOSING THE DEVELOPMENT MODEL OF AGRO-TOURISM ACTIVITY IN THE REGIONS BASED ON ASSESSMENT OF THE EFFECTS OF FACTORS
DOI: 10.6084/m9.figshare.24466999
title: Data after normalization and batched removed, comparison between large and small vs

description: We identified 9 differentially expressed miRNAs in large VS samples: miR-7, miR-142 (-3p and -5p), miR-155, miR-342, miR-1269, miR-4664 and miR-6503 were upregulated, whereas miR-204 was significantly down-regulated in comparison to small VS samples.
DOI: 10.6084/m9.figshare.24466999.v1
title: Data after normalization and batched removed, comparison between large and small vs

description: We identified 9 differentially expressed miRNAs in large VS samples: miR-7, miR-142 (-3p and -5p), miR-155, miR-342, miR-1269, miR-4664 and miR-6503 were upregulated, whereas miR-204 was significantly down-regulated in comparison to small VS samples.
DOI: 10.6084/m9.figshare.24467002
title: INL340_2023_Demo Schedule.pdf

description: File
DOI: 10.6084/m9.figshare.24464143
title: <b>Genomic tailoring of autogenous poultry vaccines to reduce </b><b><i>Campylobacter</i></b><b> from farm to fork</b>

description: <i>Campylobacter</i> is a leading cause of food-borne gastroenteritis worldwide, linked to the consumption of contaminated poultry meat. Targeting this pathogen at source, chicken vaccines can give short term reductions in <i>Campylobacter </i>in chicken guts. However, this has not reduced <i>Campylobacter </i>in the food chain or human infection. This is because vaccines typically target only a subset of strains and rapid evolution diminishes efficacy over time. To address this, we developed an autogenous vaccine against strains harbouring genes linked to survival outside of the host, whilst remaining selectively neutral against other strains in the chicken gut. This altered the chicken microbiome in favour of strains that were less likely to persist through poultry production to infect humans. Monitoring flocks revealed a near-complete shift in the post-vaccination <i>Campylobacter </i>population with a ~50% reduction in strains harbouring extra-gut survival genes. Based on these findings, a logistic regression model predicted vaccine efficacy could target a large proportion of clinically relevant strains. Reshaping livestock microbiomes towards less harmful commensal pathogen strains, has major potential for reducing pathogens in the food production chain.
DOI: 10.6084/m9.figshare.24464143.v1
title: <b>Genomic tailoring of autogenous poultry vaccines to reduce </b><b><i>Campylobacter</i></b><b> from farm to fork</b>

description: <i>Campylobacter</i> is a leading cause of food-borne gastroenteritis worldwide, linked to the consumption of contaminated poultry meat. Targeting this pathogen at source, chicken vaccines can give short term reductions in <i>Campylobacter </i>in chicken guts. However, this has not reduced <i>Campylobacter </i>in the food chain or human infection. This is because vaccines typically target only a subset of strains and rapid evolution diminishes efficacy over time. To address this, we developed an autogenous vaccine against strains harbouring genes linked to survival outside of the host, whilst remaining selectively neutral against other strains in the chicken gut. This altered the chicken microbiome in favour of strains that were less likely to persist through poultry production to infect humans. Monitoring flocks revealed a near-complete shift in the post-vaccination <i>Campylobacter </i>population with a ~50% reduction in strains harbouring extra-gut survival genes. Based on these findings, a logistic regression model predicted vaccine efficacy could target a large proportion of clinically relevant strains. Reshaping livestock microbiomes towards less harmful commensal pathogen strains, has major potential for reducing pathogens in the food production chain.
DOI: 10.6084/m9.figshare.24431449
title: Predicting <i>Pseudomonas aeruginosa</i> drug resistance using artificial intelligence and clinical MALDI-TOF mass spectra

description: Dataset for the study "Predicting <i>Pseudomonas aeruginosa</i> drug resistance using artificial intelligence and clinical MALDI-TOF mass spectra"
DOI: 10.6084/m9.figshare.24431449.v2
title: Predicting <i>Pseudomonas aeruginosa</i> drug resistance using artificial intelligence and clinical MALDI-TOF mass spectra

description: Dataset for the study "Predicting <i>Pseudomonas aeruginosa</i> drug resistance using artificial intelligence and clinical MALDI-TOF mass spectra"
DOI: 10.6084/m9.figshare.24431449.v1
title: Predicting <i>Pseudomonas aeruginosa</i> drug resistance using artificial intelligence and clinical MALDI-TOF mass spectra

description: Dataset for the study "Predicting <i>Pseudomonas aeruginosa</i> drug resistance using artificial intelligence and clinical MALDI-TOF mass spectra"
DOI: 10.5281/zenodo.10057954
title: ИСПОЛЬЗОВАНИЕ КОНЦЕПЦИЙ ЛИДЕРСТВА В МЕСТНОМ САМОУПРАВЛЕНИИ
DOI: 10.5281/zenodo.10057955
title: ИСПОЛЬЗОВАНИЕ КОНЦЕПЦИЙ ЛИДЕРСТВА В МЕСТНОМ САМОУПРАВЛЕНИИ
DOI: 10.5281/zenodo.5497700
title: CPRDAT 0.1

description: The <strong>C</strong>ardio<strong>P</strong>ulmonary <strong>R</strong>esuscitation <strong>D</strong>ata <strong>A</strong>nalysis <strong>T</strong>oolbox is a software tool box developed to allow data analysis of defibrillator records of cardiopulmonary resuscitation attempts. The code originates from the project "A machine learning approach towards data-driven cardiopulmonary resuscitation” at the University of Graz. So far this toolbox contains only one algorithm which automatically detects chest compression episodes in accelerometer signals from cardiopulmonary resuscitation (CPR) attempts. Further tools will be added later. Exemplary data to illustrate the functionalities of the toolbox is also provided in this repository.
DOI: 10.5281/zenodo.10057970
title: ПРОБЛЕМЫ УСКОРЕННОГО РАЗВИТИЯ ПРОМЫШЛЕННОСТИ
DOI: 10.5281/zenodo.10057971
title: ПРОБЛЕМЫ УСКОРЕННОГО РАЗВИТИЯ ПРОМЫШЛЕННОСТИ