cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24763701.v1
title: AOCG

description: <pre>### The replication package of AOCG<br><br>The repository is divided into two parts: datasets and the code of our AOCG method.<br><br><br>### Requirements<br>```<br>- python 3.8<br>- Java 1.8.0<br>- transformers 4.5.1<br>- tree-sitter 0.2.2<br>- Pytorch 1.7.1<br>```<br><br>### Data Preprocessing<br>```<br>Experimental datasets contain the API_SUM dataset, the Hearthstone dataset, and the MBPP dataset. We use tree sitter tool to automatically extract the API terms and sketches of programs.<br><br>Take the MBPP dataset as an example:<br><br>To extract API terms, run 'data_process/api_extract.py' and acquire the 'api_terms.jsonl' <br><br>To extract sketches, run 'data_process/sketch_extract.py' and acquire the 'sketches.jsonl' <br><br>Put the API terms, sketches, complete codes, and requirements into the 'final_train.jsonl' and 'final_test.jsonl'.<br><br>```<br><br><br>### Training<br>Given a specific requirement, the APIer predicts API terms, and the Sketcher outputs corresponding the sketch based on the API terms and requirements. And the Coder fills the sketch to a complete program according to the API terms, sketch and requirement.<br><br>```<br>export CUDA_VISIBLE_DEVICES=0<br><br>python AOCG_finetune.py \<br>--stage_1 nl_pp \<br>--stage_2 nl_pp_ss \<br>--stage_3 nl_ss_pp_code \<br>--local_rank -1 <br><br>```<br><br><br>### Inference<br>The AOCG predicts code snippets in a progressive generation manner, and write the predicted codes into 'xx.output'.<br><br>```<br>export CUDA_VISIBLE_DEVICES=0<br><br>python AOCG_inference.py \<br>--stage_1 nl_pp \<br>--stage_2 nl_pp_ss \<br>--stage_3 nl_ss_pp_code \<br>--local_rank -1 <br><br>```<br><br><br>### Evaluation<br>```<br>After acquiring the generated codes, evaluate the programs by running 'evaluator/evaluation.py'.<br><br>```</pre>
DOI: 10.6084/m9.figshare.24763680
title: Replication Package for the ECSA Post proceedings. Pragmatic Architectural Framework.

description: To-Share_Data-Extraction_NAS Cocerns_Form: is an Excel file containing extracted data from the papers plus a description of each non-architecturally significant requirement (NAS)
DOI: 10.6084/m9.figshare.24763680.v1
title: Replication Package for the ECSA Post proceedings. Pragmatic Architectural Framework.

description: To-Share_Data-Extraction_NAS Cocerns_Form: is an Excel file containing extracted data from the papers plus a description of each non-architecturally significant requirement (NAS)
DOI: 10.48364/isimip.571080
title: ISIMIP2a Simulation Data from the Regional Water Sector

description: This dataset contains ISIMIP2a (https://www.isimip.org, Schewe et al. 2019) simulation data from 22 regional water models models: ECOMAG (Motovilov 1999a, Motovilov 1999b), HBV-IWW, HBV-JLU, HBV-PIK, HYMOD-JLU, HYMOD-UFZ (Boyle 2001, Vrugt et al. 2005, Moore et al. 2010), HYPE (Lindstrom et al. 2010, Donelly et al. 2016, Pechlivanidis et al. 2015), mHM (http://www.ufz.de/mhm, Samaniego et al. 2010, Rakovec et al. 2015, Kumar et al. 2013), SWAP (Gusev et al .2003, Gusev et al. 2006), SWAT-CMA, SWAT-SGGW, SWAT-TAMU, SWAT-UFZ, SWAT-VUB (Arnold et al. 2007, Krysanova & Wechsung 2006), SWIM-CMA, SWIM-NVE (Krysanova et al. 1998, Krysanova & Wechsung 2006), SWIM-PIK (https://gitlab.pik-potsdam.de/swim/swim), VIC-CMA, VIC-HHU, VIC-IITGN (https://vic.readthedocs.io/en/master/, Liang et al. 1994), VIC-NVE (https://vic.readthedocs.io/en/master/, Huang et al. 2017), VIP, and WaterGAP3.<br>With version 2.0 of this dataset, the DOI page moved to the new ISIMIP repository.
description: The ISIMIP2a regional water outputs are based on simulations from regional water models according to the ISIMIP2a protocol (https://www.isimip.org/protocol/2a/). A more detailed description of the models and model-specific amendments of the protocol are available at https://www.isimip.org/impactmodels.
DOI: 10.6084/m9.figshare.24763770
title: Arrhenia bryophthora and Bryopistillaria clavarioides

description: Alignements of the ITS and LSU based RAxML tree is provided for both species.
DOI: 10.15128/r2000000048
title: Patterning and dynamics of membrane adhesion under hydraulic stress [dataset]

description: Fixed corrupt data file, 2023-12-07.
description: Hydraulic fracturing plays a major role in the formation of biological cavities during embryonic development, when the accumulation of pressurized fluid leads to the opening of microlumens that fracture cell-cell contacts and later evolve to form a single large lumen. However, the fundamental physical mechanisms behind these processes remain masked by the complexity and specificity of biological systems. Here, we show that adhered lipid vesicles subjected to osmotic stress form hydraulic microlumens similar to those in cells. Combining vesicle experiments with theoretical modelling and numerical simulations, we provide a physical framework for the hydraulic reconfiguration of cell-cell adhesions. We map the conditions for microlumen formation from a pristine adhesion, the emerging dynamical patterns and their subsequent maturation. We demonstrate control of the fracturing process depending on the applied pressure gradients, and the type and density of membrane bonds. Our experiments further reveal an unexpected, passive transition of microlumens to closed buds that suggests a physical route to adhesion remodeling by endocytosis.
DOI: 10.5281/zenodo.10283646
title: Results of the Claude-based real estate ontology population
DOI: 10.5281/zenodo.10283647
title: Results of the Claude-based real estate ontology population
DOI: 10.3886/e195643
title: ExMAT Conjoint

description: Between July 2020 and May 2021, we conducted a randomly sampled, cross-sectional survey that included PWID with OUD who were on OAT, previously on OAT and never on OAT; a CBC survey was included along with other items. Trained Ukrainian research assistants administered the survey through a computer-assisted survey instrument (CASI) in private rooms in five cities of Ukraine (Dnipro, Kyiv, L’viv, Mykolaiv, Odesa).
DOI: 10.3886/e195643v1
title: ExMAT Conjoint

description: Between July 2020 and May 2021, we conducted a randomly sampled, cross-sectional survey that included PWID with OUD who were on OAT, previously on OAT and never on OAT; a CBC survey was included along with other items. Trained Ukrainian research assistants administered the survey through a computer-assisted survey instrument (CASI) in private rooms in five cities of Ukraine (Dnipro, Kyiv, L’viv, Mykolaiv, Odesa).
DOI: 10.6084/m9.figshare.24763773
title: Divergent geographic variation in above- versus belowground secondary metabolites of Reynoutria japonica

description: Secondary metabolites, trait and environmental data for this study are available.
DOI: 10.6084/m9.figshare.24763773.v1
title: Divergent geographic variation in above- versus belowground secondary metabolites of Reynoutria japonica

description: Secondary metabolites, trait and environmental data for this study are available.
DOI: 10.6084/m9.figshare.24763791
title: Algal short-term greenhouse effect

description: In eutrophic lakes, the proliferating algae sequester atmospheric carbon dioxide (CO<sub>2</sub>) and store it in the form of biomass organic carbon (OC). The high biodegradability of this endogenous OC, however, can generate anaerobic conditions and facilitate methane (CH<sub>4</sub>) production. This process of sequestered CO<sub>2</sub> to higher radiative forcing CH<sub>4</sub> has the potential to add CO<sub>2</sub>-equivalents (CO<sub>2</sub>-eq) to the atmosphere. This study conducted the first analysis of carbon budgets associated with algae in eutrophic lakes from a life cycle perspective and predicted the impact of future climate warming and nutrient reduction on this effect using machine learning.
DOI: 10.5281/zenodo.10276709
title: Model simulation data used in "Impacts of ice-nucleating particles on cirrus clouds and radiation derived from global model simulations with MADE3 in EMAC" (Beer et al., Atmos. Chem. Phys., 2024)

description: This dataset contains the namelist setup and the output of the EMAC global model simulations analysed and discussed in Beer et al. (Atmos. Chem. Phys., 2024). For details see the README.md file and Table 2 in the paper.
DOI: 10.5281/zenodo.10276710
title: Model simulation data used in "Impacts of ice-nucleating particles on cirrus clouds and radiation derived from global model simulations with MADE3 in EMAC" (Beer et al., Atmos. Chem. Phys., 2024)

description: This dataset contains the namelist setup and the output of the EMAC global model simulations analysed and discussed in Beer et al. (Atmos. Chem. Phys., 2024). For details see the README.md file and Table 2 in the paper.
DOI: 10.5281/zenodo.7828163
title: tFood: Semantic Table Annotations Benchmark for Food Domain

description: tFood is a dataset for tabular data to knowledge graph matching. It is derived for the Food domain and has two types of tables. On the one hand, <strong>Horizontal Relational Tables</strong> are where each table represents a collection of entities. On the other hand, <strong>Entity Tables </strong>are where each of which represents a single entity. We supported ground truth data from Wikidata as a target knowledge graph (KG). The supported tasks for semantic table annotations are: Topic Detection (<strong>TD</strong>) links the entire table to an entity or a class from the target KG. Cell Entity Annotation (<strong>CEA</strong>) maps individual table cells to entities from the target KG. Column Type Annotation (<strong>CTA</strong>) links individual table columns to classes from the target KG. Column Property Annotation (<strong>CPA</strong>) detects the relations between column pairs from the target knowledge graph. This dataset version will be used during SemTab 2023 - Round 1. So, the ground truth data for the test set is currently hidden. We will add such ground truth after the conclusion of the challenge.
DOI: 10.6084/m9.figshare.12496805
title: The broad-spectrum antiviral recommendations for drug discovery against COVID-19

description: Despite to outbreaks of highly pathogenic beta and alpha coronaviruses including severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and human coronavirus, the newly emerged 2019 coronavirus (COVID-19) is considered as a lethal zoonotic virus due to its deadly respiratory syndrome and high mortality rate among the human. Globally, more than 3,517,345 cases have been confirmed with 243,401 deaths due to Acute Respiratory Distress Syndrome (ARDS) caused by COVID-19. The antiviral drug discovery activity is required to control the persistence of COVID-19 circulation and the potential of the future emergence of coronavirus. However, the present review aims to highlight the important antiviral approaches, including interferons, ribavirin, mycophenolic acids, ritonavir, lopinavir, inhibitors, and monoclonal antibodies (mAbs) to provoke the nonstructural proteins and deactivate the structural and essential host elements of the virus to control and treat the infection of COVID-19 by inhibiting the viral entry, viral RNA replication and suppressing the viral protein expression. Moreover, the present review investigates the epidemiology, diagnosis, structure, and replication of COVID-19 for better understanding. It is recommended that these proteases, inhibitors, and antibodies could be a good therapeutic option in drug discovery to control the newly emerged coronavirus.HighlightsCOVID-19 has more than 79.5% identical sequence to SARS-CoV and a 96% identical sequence of the whole genome of bat coronaviruses.Acute respiratory distress syndrome (ARDS), renal failure, and septic shock are the possible clinical symptoms associated with COVID-19.Different antivirals, including interferons, ribavirin, lopinavir, and monoclonal antibodies (mAbs) could be the potent therapeutic agents against COVID-19.The initial clinical trials on hydroquinone in combination with azithromycin showed an admirable result in the reduction of COVID-19.The overexpression of inflammation response, cytokine dysregulation, and induction of apoptosis could be an well-organized factors to reduce the pathogenicity of COVID-19. COVID-19 has more than 79.5% identical sequence to SARS-CoV and a 96% identical sequence of the whole genome of bat coronaviruses. Acute respiratory distress syndrome (ARDS), renal failure, and septic shock are the possible clinical symptoms associated with COVID-19. Different antivirals, including interferons, ribavirin, lopinavir, and monoclonal antibodies (mAbs) could be the potent therapeutic agents against COVID-19. The initial clinical trials on hydroquinone in combination with azithromycin showed an admirable result in the reduction of COVID-19. The overexpression of inflammation response, cytokine dysregulation, and induction of apoptosis could be an well-organized factors to reduce the pathogenicity of COVID-19.
DOI: 10.6084/m9.figshare.12496805.v1
title: The broad-spectrum antiviral recommendations for drug discovery against COVID-19

description: Despite to outbreaks of highly pathogenic beta and alpha coronaviruses including severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and human coronavirus, the newly emerged 2019 coronavirus (COVID-19) is considered as a lethal zoonotic virus due to its deadly respiratory syndrome and high mortality rate among the human. Globally, more than 3,517,345 cases have been confirmed with 243,401 deaths due to Acute Respiratory Distress Syndrome (ARDS) caused by COVID-19. The antiviral drug discovery activity is required to control the persistence of COVID-19 circulation and the potential of the future emergence of coronavirus. However, the present review aims to highlight the important antiviral approaches, including interferons, ribavirin, mycophenolic acids, ritonavir, lopinavir, inhibitors, and monoclonal antibodies (mAbs) to provoke the nonstructural proteins and deactivate the structural and essential host elements of the virus to control and treat the infection of COVID-19 by inhibiting the viral entry, viral RNA replication and suppressing the viral protein expression. Moreover, the present review investigates the epidemiology, diagnosis, structure, and replication of COVID-19 for better understanding. It is recommended that these proteases, inhibitors, and antibodies could be a good therapeutic option in drug discovery to control the newly emerged coronavirus.HighlightsCOVID-19 has more than 79.5% identical sequence to SARS-CoV and a 96% identical sequence of the whole genome of bat coronaviruses.Acute respiratory distress syndrome (ARDS), renal failure, and septic shock are the possible clinical symptoms associated with COVID-19.Different antivirals, including interferons, ribavirin, lopinavir, and monoclonal antibodies (mAbs) could be the potent therapeutic agents against COVID-19.The initial clinical trials on hydroquinone in combination with azithromycin showed an admirable result in the reduction of COVID-19.The overexpression of inflammation response, cytokine dysregulation, and induction of apoptosis could be an well-organized factors to reduce the pathogenicity of COVID-19. COVID-19 has more than 79.5% identical sequence to SARS-CoV and a 96% identical sequence of the whole genome of bat coronaviruses. Acute respiratory distress syndrome (ARDS), renal failure, and septic shock are the possible clinical symptoms associated with COVID-19. Different antivirals, including interferons, ribavirin, lopinavir, and monoclonal antibodies (mAbs) could be the potent therapeutic agents against COVID-19. The initial clinical trials on hydroquinone in combination with azithromycin showed an admirable result in the reduction of COVID-19. The overexpression of inflammation response, cytokine dysregulation, and induction of apoptosis could be an well-organized factors to reduce the pathogenicity of COVID-19.
DOI: 10.6084/m9.figshare.21740401
title: Equilibrium queueing analysis in a ride-hailing service with sharing option

description: This paper examines different car-sharing models offered by ride-hailing firms. In the traditional model, customers are served individually. In the sharing-only model, all customers are willing to share the ride with other customers. In the hybrid model, customers may choose either individual or shared service provided by the same fleet. Sharing customers incur a hassle cost. We develop a queueing game-theoretic model to (i) determine the arrival rates that maximizes social welfare and (ii) choose admission fees that maximizes firm profits. First, we discover a tipping point in the hybrid model. When hassle cost decreases to this point, (i) the optimal customer behavior immediately switches from less than 80% sharing customers to 100%, (ii) the optimal arrival rate increases dramatically, and (iii) the rate at which a decreasing hassle cost improves the maximum social welfare significantly increases. Second, when hassle cost is higher than the tipping point, the hybrid model may generate higher social welfare than the other two models. Hence, the firm can improve social welfare by assigning customers to differentiated services even when they are not heterogeneous. Finally, we propose a profit-maximizing admission fee structure in the hybrid model to maximize firm profits and demonstrate its effectiveness.
DOI: 10.6084/m9.figshare.21740401.v1
title: Equilibrium queueing analysis in a ride-hailing service with sharing option

description: This paper examines different car-sharing models offered by ride-hailing firms. In the traditional model, customers are served individually. In the sharing-only model, all customers are willing to share the ride with other customers. In the hybrid model, customers may choose either individual or shared service provided by the same fleet. Sharing customers incur a hassle cost. We develop a queueing game-theoretic model to (i) determine the arrival rates that maximizes social welfare and (ii) choose admission fees that maximizes firm profits. First, we discover a tipping point in the hybrid model. When hassle cost decreases to this point, (i) the optimal customer behavior immediately switches from less than 80% sharing customers to 100%, (ii) the optimal arrival rate increases dramatically, and (iii) the rate at which a decreasing hassle cost improves the maximum social welfare significantly increases. Second, when hassle cost is higher than the tipping point, the hybrid model may generate higher social welfare than the other two models. Hence, the firm can improve social welfare by assigning customers to differentiated services even when they are not heterogeneous. Finally, we propose a profit-maximizing admission fee structure in the hybrid model to maximize firm profits and demonstrate its effectiveness.
DOI: 10.5517/ccdc.csd.cc23cqv2
title: CCDC 1947694: Experimental Crystal Structure Determination

description: Related Article: Ping Wu, Liandi Wang, Kaikai Wu, Zhengkun Yu|2023|Org.Lett.|25|8434|doi:10.1021/acs.orglett.3c03302
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.cc27vgyj
title: CCDC 2081028: Experimental Crystal Structure Determination

description: Related Article: Yu-Peng Li, Kang Yang, Hui Meng, Tao Shen, Hua Zhang|2022|Chin.J.Nat. Med.|20|301|doi:10.1016/S1875-5364(21)60120-6
description: Related Article: Yu-Peng Li|2023|CSD Communication|||
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: 10.6084/m9.figshare.24671343
title: Supplementary Material for: Diabetic Retinopathy and Chronic Kidney Disease: Associations and Comorbidities in a Large Diabetic Population: The Tongren Health Care Study

description: Introduction: To investigate associations between diabetic retinopathy (DR) and chronic kidney disease (CKD) in patients with type 2 diabetes (DT2). 
Methods: The participants of the cross-sectional, community-based Tongren Health Care Study underwent a detailed medical and ophthalmological examination. We defined DT2 by a fasting plasma glucose concentration of ≥7.0 mmol/L or a medical history. CKD was classified as either reduced estimated glomerular filtration rate (eGFR) of &lt;60ml/min/1.73mm2, or presence of albuminuria. DR was assessed using color fundus photographs.
Results: Out of 62,217 participants of the Tongren Health Care Study, 5103 (8.2%) patients had DT2. The prevalence of DR was 12.8% (95%CI, 11.8%, 13.7%), CKD was 13.3% (95%CI,12.4%, 14.3%), and the subtypes of CKD, including reduced eGFR and albuminuria was 4.6% (95%CI, 4.2%, 5.1%), and 10.1% (95%CI, 9.3%, 10.9%), respectively. DR was detectable in 21.0% of the patients with CKD, while CKD present in 20.9% of the DR patients. Higher DR prevalence was associated with higher prevalence of albuminuria and reduced eGFR (both P&lt;0.05). Factors independently associated with the presence of CKD instead of DR were older age (P&lt;0.001, OR=1.05), a higher body mass index (P&lt;0.001, OR=1.14), a higher serum concentration of triglycerides (P&lt;0.001, OR=1.26), and a lower blood glucose (P&lt;0.001, OR=0.93). Having hypertension was additionally associated with the presence of reduced eGFR as compared with DR (P=0.005, OR=4.47).
Conclusions: TD2 patients of older age and with higher body mass index, hypertension and dyslipidemia had a higher probability of being affected by CKD rather than DR, while those with a higher blood glucose level were more prone to DR than CKD.
DOI: 10.5281/zenodo.7640252
title: Data from: Long-term forecast of thermal mortality with climate warming in riverine amphipods

description: Dataset and code to reproduce the figures in the associated publication
DOI: 10.5281/zenodo.7640253
title: Data from: Long-term forecast of thermal mortality with climate warming in riverine amphipods

description: Dataset and code to reproduce the figures in the associated publication
DOI: 10.6084/m9.figshare.24097941
title: Transcriptome data of samples from two <i>Gossypium barbadense</i> varieties before and after <i>Verticillium dahliae</i> inoculation

description: This is the original transcriptome data of 24 <i>Gossypium barbadense</i> samples under different time points of <i>Verticillium dahliae</i> treatment.File1 is the breakdown of each sample file on GSA.File2 contains the read counts and the expression level of each gene.File3 contains all DEGs between the BR and BS varieties before <i>Verticillium dahliae</i> infection.File4 and File5 contain the GO enrichment analysis results for DEGs from File2.File6 contains the DEGs of BR and BS varieties under different time points of <i>Verticillium dahliae</i> treatment.File7 contains the DEGs induced by Verticillium dahliae which are used for GO analysis.File8 and File9 contain the GO enrichment analysis results for DEGs from File7.<br>