cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14457/cu.the.2012.242
title: Buddhadasa's poetry and the contemplation on emptiness

description: ‘Emptiness’ as a Buddhist term is derived from the teaching of the Buddha which appears in the Tipiṭaka. In Theravāda, the word ‘suññatā’ is used in the meaning of emptiness and is explained by the Buddhism concept of paṭiccasamuppāda. In Mahāyāna, the word ‘śūññatā’ is used in the meaning of emptiness and its meaning is extended, to the greatest extent, to cover the Bodhi – the enlightenment of the Buddha. Buddhadāsa proposed the concept of emptiness as something beyond the division of schools, that is, he explained that emptiness is the essence of the religion which appears in the teaching of the Buddha, or what he called Buddhayāna. Emptiness in Buddhadāsa’s teaching can be divided into four categories; the empty mind, the original condition of the mind, Nibbāna here and now for everyone, and the integration of empty mind with daily life. These four aspects of emptiness cover all areas of Buddhadāsa’s teaching, that is, everything that Buddhadāsa taught is all related or connected to the concept of emptiness. Emptiness is also the main focus in Buddhadāsa’s poetry. His poetry portrayed the concept of emptiness in various aspects, that is, the poetry defines emptiness as the dependent origination of things with no core to cling to. Everything exists under the law of cause and effect. In his poetry, Buddhadāsa suggests that the ultimate condition of emptiness is elaborated in 4 dimensions namely, the notion of empty mind, the original condition of the mind, and the path to attain such ultimate state –covering the concept of nibbāna here and now for everyone, and the integration of empty mind with daily life. Moreover, Buddhadāsa’s poetry also illustrates that the emptiness is the concept used to explain the tri-sikkha (threefold training) that is sīla, samādhi, and paññā – which are the foundation of attaining nibbāna. Reading of poetry can also be considered the path to nibbāna because the poetry itself is an upāya which teach dhamma in a deep and refined way. Artistic techniques used in Buddhadāsa’s poetry, such as, imagery, poetry with picture, provocation, metaphor, conversation technique, and parable; all contribute in creating ‘skillful means’ in which the reader can ‘contemplate’ until they finally attain ‘emptiness’ or nibbāna. Buddhadāsa’s poetry is, thus, a crucial object of contemplation on emptiness.
DOI: 10.14457/cu.the.2012.243
title: Systematic design of biodiesel and fatty alcohol production process

description: Biodiesel is regarded as a promising alternative to a conventional petroleum-based diesel fuel. To reduce any risk for biodiesel producers, who rely only on the biodiesel product, the use of chemicals obtained from the biodiesel production to synthesize other high value-added products, such as fatty alcohol, has gained growing significance. The integration of fatty alcohol and biodiesel production results in a complicated process involving multi-components and various unit operations. The aim of this study is focused on the design and analysis of the production process of biodiesel integrated with fatty alcohol. The study is divided into four parts. In the first part, a systematic step by step methodology is developed for producing biodiesel and fatty alcohol products. A superstructure that includes all possible reaction and separation operations is generated through thermodynamic insights and available data. The number of alternative processes is systematically reduced through a screening procedure and economic analysis is performed to find the best economically and operationally feasible process. According to the methodology, a heterogeneous acid catalyzed process for biodiesel production integrated with fatty alcohol production is better than other process alternatives. In the second part, process intensification is applied to improve process performance in terms of productivity and energy consumption. A reactive distillation, which combines the reaction and separation tasks in the biodiesel production, is designed based on based on the element-based method. To further improve the performance of the reactive distillation in term of the energy consumption, a heat integration concept of the reactive distillation column is studied in the third part of the research. Various types of the heat-integrated reactive distillation are considered. Based on the minimization of a total annual cost, the multi-effect indirect split arrangement reactive distillation is the most attractive choice. In the final part of this study, the separation process of the fatty alcohol products is designed taking into account the total annual cost. The results indicate that the energy consumption of the fatty alcohol separation process can be minimized when the thermal coupling distillations are applied. In addition, the capital cost of the separation process is decreased because the number of unit operations, such as a condenser and a distillation column can be reduced.
DOI: 10.14457/cu.the.2012.244
title: Supporting construction personnel in the safety and planning of construction activities performed at high elevations via augmented reality technology

description: Due to the nature of construction, many of the tasks and activities tend to lead to the occurrence of accidents. The major causations of the accidents in construction industry are fall from height and being struck by falling object. The tasks to execute the safety and prevent the hazards of these causations consist of design and planning, monitoring, and training. The process of each task are carried out based on the project information, which represented by two dimensional and paper format documents accompanied with the construction personnel’s knowledge and experiences. However, the actual work conditions at the construction site are dynamic environment and contained the inhered hazards. Thus, the execution of the tasks to prevent the mentioned hazards sometimes requires the information of actual workplace for supporting in the safety considerations. Normally, the in-charge personnel convert, generate and integrate mental three dimensional pictures regarding safety with the actual environment by themselves. However, it is difficult, burdensome, and error prone. Additionally, it depends on the level of experience, knowledge, and individual perspective of undertaker. Therefore, the innovative and proactive approach for supporting the construction personnel regarding safety management in real time and actual environment via Augmented Reality (AR) technology is developed. The approach provides the virtual safety information and superimposes it on the real world scene. The prototype system, which named Visualized Safety Management using Augmented Reality Technology System (VSMART System), was developed to assist the in-charge personnel in the following tasks: 1) design and planning for preventing the hazards of falling object, 2) design and planning for arrangement of safe work areas, 3) monitoring, and 4) training. The projectile calculation and collision detection algorithms based on the computer vision techniques are developed to analyze the potential hazards of falling objects, the capability of designed falling protection system, and the virtual unsafe zone when operated crane and performed construction activities. Three functions in the prototype system, which consisted of providing the visualization of possible hazards from falling object, illustrating the unsafe working areas, and presenting the virtual objects regarding safety were tested in both laboratory and real environment. This proposed system was implemented at the real high rise construction project. The experiment results showed that this system is feasibly applied for design and planning task to provide the unseen and unforeseen information in the actual work environment and to envision the construction personnel in safety aspect prior the construction activities begin. For the monitoring and training, this system can support the project participants in communication.
DOI: 10.17632/5kwrwvmz4h.2
title: Fusion Pten-NOLC1 Promotes C-Met and EGFR Signals in Human Cancers (Chip-Seq part 12)

description: Deletion and mutation of PTEN are frequent in human cancers. These alterations disturb PI3K signaling and increase survival of cancer cells. Here, we report a pro-cancer growth Pten-NOLC1 gene fusion originated from a chr10 rearrangement. Expressed as a nuclear chimera protein, Pten-NOLC1 interacts with the promoter regions of genes like EGFR, c-MET and GAB1 and promotes cancer cell growth, invasion, and increases survivals; and increases metastasis and mortality in vivo. Pten-NOLC1 fusion is detected in primary human cancer samples and cancer cell lines from different organs. Genomic interruption of Pten-NOLC1 induces large number of cancer cell death. Genome integration of this fusion gene coupled with somatic Pten deletion produces liver cancer in mice. Our studies show that genome rearrangement of Pten-NOLC1 is functional. The nuclear interaction of Pten-NOLC1 drives cancer growth, and disruption of this fusion gene may be a potential target in the treatment of human cancers.
DOI: 10.17632/dt7rsx2558.1
title: Dataset of Chemical attributes of yellow latosols in areas of occurrence of Crazy Soybean II in Western Pará

description: Soil assessment is the first step in defining soil fertility management measures, with soil analysis as an important tool in assessing soil fertility by diagnosing soil physicochemical patterns and, in addition, knowledge soil fertility and plant nutritional needs enables the identification and quantification of essential nutrients. Soil-related plant anomalies are directly linked to critical and toxic levels of soil physical, chemical or biological attributes, so soil fertility is one of the predisposing factors of plants to pathogens. Mad-II soybean is an anomaly that causes a 40% reduction in crops and no defined cause, such a disturbance as the soybean crop does not produce pods, which prevents it from completing its cycle, characterized by reduced yield in function of the high abortion rate of flowers and pods and the high percentage discount on soybean value, due to the presence of impurities, ie pieces of green tissue and rotten grains, which favor the rotting of the grain mass. From an agronomic point of view, this anomaly is quite worrying, since there is a reduction in grain yield and quality, difficulty in harvesting due to green stalks and, in addition, lengthening of the period when there are green soybean leaves, increasing the survival of biotrophic fungi such as Asian rust Therefore, since plant mineral nutrition, governed by soil nutrient availability, has been one of the most studied factors regarding plant susceptibility and resistance to disease. Thus, any modification in the soil can directly change its structure and biological activity and, consequently, its fertility, with effects on environmental quality and crop productivity. It becomes necessary to evaluate the chemical attributes of soil where anomalies such as Crazy Soy II occur, so the objective of these data is to evaluate the levels and variance of chemical attributes of soils in areas with occurrence of Crazy Soy II.
DOI: 10.17632/k2yhbng5dw.1
title: Micro-X-ray diffraction data and codes for Best Fit for Complex Peaks (BFCP)

description: Micro-X-ray diffraction data and Matlab codes that were used in the BFCP program. Detail is in the manuscript: Quantitative analysis of in situ 2D X-ray diffraction data from complex crystal deformation using the Best Fit for Complex Peaks (BFCP) code in Matlab®
DOI: 10.17632/sjdxg5cc5h.1
title: Angiotensin II type I receptor autoantibodies and prostate cancer: cross-sectional and longitudinal studies.

description: Autoantibodies against the angiotensin II type I receptor (AT1R) have been associated with multiple diseases (pre-eclampsia, malignant hypertension, transplant rejection, Huntington’s and Alzheimer’s disease, ovarian cancer) suggesting that while the autoantibodies are not necessarily causative they may promote disease progression. These autoantibodies (AT1RaAbs) bind and chronically activate the receptor increasing inflammatory burden. The prostate has a local renin angiotensin system that has been implicated in prostate cancer growth. Two distinct datasets were used to examine the associations between AT1RaAbs and prostate cancer. A cross-sectional set (n = 151) consisting of 101 serum specimens that were collected from patients with scheduled appointments for either elevated prostate specific antigen levels, a scheduled prostate biopsy or being seen as a newly diagnosed PCA patient in a Urology Outpatient Clinic. 80 of these patients were positive for PCA at biopsy, whereas 21 were biopsy benign (either atrophy, benign prostatic hyperplasia, high-grade prostatic intraepithelial neoplasia or inflammation). The remaining 50 specimens were collected from men visiting an offsite prostate cancer screening who were free of prostate disease. Comparisons of covariate values between groups were by Kruskal-Wallis ANOVA with Dunn’s multiple comparisons test. Pairwise correlations between AT1RaAb and clinical correlates or pathological measurements were assessed using Spearman rank correlations. The longitudinal set of pre-diagnosis serum samples from 109 men was obtained from the Baltimore Longitudinal Study of Aging. This prospective cohort study is run by the National Institute on Aging, National Institutes of Health. Clinical measures associated with each BLSA serum sample include age, BMI, blood pressure, PSA levels and, for subjects who later developed PCA, the diagnosis date. All serum is from subjects now deceased with known date of death and post-mortem pathological status of the prostate (disease-free or PCA present). Time to events (diagnosis or death) were modeled nonparametrically by Kaplan-Meier survival curves, dichotomizing samples into either low or high AT1RaAb levels and analyzing serum samples grouped as most proximal or distal to timed event. Accelerated failure estimates were used to assess the effects of other predictors on AT1RaAb association with disease-free and overall survival at most proximal or most distal time points. The datasets correspond to the a study described in the Journal of Translational Autoimmunity published online 13 August 2019, 10000. "Angiotensin receptor autoantibodies as exposures that modify disease progression: cross sectional, longitudinal and in vitro studies of prostate cancer." https://doi.org/10.1016/j.jtauto.2019.100008
DOI: 10.17632/xsbz9dmv7v.1
title: A Comparison of Chinese and US Memories for Public Events
DOI: 10.7910/dvn/59nphx/7uptyx
title: ricegalileogluegaia.pdf

description: :unav
DOI: 10.7910/dvn/59nphx/ok62ii
title: handout_glue_10QViz_Rice.pdf

description: Handout from A. Goodman Rice VCS Symposium
DOI: 10.17632/7xkc6txwb8.1
title: Hydrogen Permeation and Hydrogen Microprint of pipeline steel

description: The data includes the typical Permeation curve from the Permeation experiment and the EDS analysis after the Microprint experiments
DOI: 10.17632/gg852jn9bg.1
title: PTPS facilitates compartmentalized LTBP1 S-nitrosylation and promotes tumor growth under hypoxia

description: Original Western blot data in association with MOLECULAR-CELL-D-19-01081 .
DOI: 10.5061/dryad.79ck1tm/1
title: Dryad Item 10.5061/DRYAD.79CK1TM/1

description: (:tba)
DOI: 10.5281/zenodo.3239498
title: Industry-scale Application and Evaluation of Deep Learning for Drug Target Prediction

description: Artificial intelligence (AI) is undergoing a revolution thanks to the breakthroughs of machine learning algorithms in computer vision, speech recognition, natural language processing and generative modelling. Recent works on publicly available pharmaceutical data showed that AI methods are highly promising for Drug Target prediction. However, the quality of public data might be different than that of industry data due to different labs reporting measurements, different measurement techniques, fewer samples and less diverse and specialized assays. As part of a European funded project (ExCAPE), that brought together expertise from pharmaceutical industry, machine learning, and high-performance computing, we investigated how well machine learning models obtained from public data can be transferred to internal pharmaceutical industry data. Our results show that machine learning models trained on public data can indeed maintain their predictive power to a large degree when applied to industry data. Moreover, we observed that deep learning derived machine learning models outperformed comparable models, which were trained by other machine learning algorithms, when applied to internal pharmaceutical company datasets. To our knowledge, this is the first large-scale study evaluating the potential of machine learning and especially deep learning directly at the level of industry-scale settings and moreover investigating the transferability of publicly learned target prediction models towards industrial bioactivity prediction pipelines.
description: Dataset Format to reproduce manuscript results
DOI: 10.5281/zenodo.3239499
title: Industry-scale Application and Evaluation of Deep Learning for Drug Target Prediction

description: Artificial intelligence (AI) is undergoing a revolution thanks to the breakthroughs of machine learning algorithms in computer vision, speech recognition, natural language processing and generative modelling. Recent works on publicly available pharmaceutical data showed that AI methods are highly promising for Drug Target prediction. However, the quality of public data might be different than that of industry data due to different labs reporting measurements, different measurement techniques, fewer samples and less diverse and specialized assays. As part of a European funded project (ExCAPE), that brought together expertise from pharmaceutical industry, machine learning, and high-performance computing, we investigated how well machine learning models obtained from public data can be transferred to internal pharmaceutical industry data. Our results show that machine learning models trained on public data can indeed maintain their predictive power to a large degree when applied to industry data. Moreover, we observed that deep learning derived machine learning models outperformed comparable models, which were trained by other machine learning algorithms, when applied to internal pharmaceutical company datasets. To our knowledge, this is the first large-scale study evaluating the potential of machine learning and especially deep learning directly at the level of industry-scale settings and moreover investigating the transferability of publicly learned target prediction models towards industrial bioactivity prediction pipelines.
DOI: 10.5281/zenodo.3377413
title: Effects of flavoring compounds used in electronic cigarette refill liquids on endothelial and vascular function

description: raw data of all figures and tables
DOI: 10.5281/zenodo.3377414
title: Effects of flavoring compounds used in electronic cigarette refill liquids on endothelial and vascular function

description: raw data of all figures and tables
DOI: 10.7910/dvn/59nphx/muyqac
title: ricegalileogluegaia.key

description: :unav
DOI: 10.14457/cu.the.2012.245
title: An automation approach for data and information manipulation to reduce knowledge and skill requirements in construction

description: The lack of personnel, especially knowledgeable and skilled personnel, always arises in the construction industry. This issue highly concerns the stakeholders and related personnel in the industry because it leads to prolonged construction, cost overrun, and lower quality of structure construction. Therefore, the reduction of knowledge and skill requirements is important in order to increase productivity, increase the number of qualified personnel, and supply personnel to the construction industry. Thus, this research aims to explore the automation approach for data and information manipulation to reduce knowledge and skill requirements in construction. The installation process of prefabricated members in residential projects was selected as a case study. The knowledge and skill requirements depend on the construction processes and the roles and responsibilities of related personnel. In addition, the changes and mistakes increase the level of knowledge and skill requirements in the construction processes to perceive and select countermeasures. Thus, an automation approach for data and information manipulation, which is the integration of computer and information technology with Radio Frequency Identification (RFID), is proposed in this research. The approach was developed from the roles and responsibilities of related personnel and the three main steps of the installation process, specifically, checking the available prefabricated members, making a decision for an installation process, and installing the prefabricated members. Moreover, the approach covers four supplementary steps, which are checking the availability of other resources, comparing the required resources and the available resources, deciding the work location of the mobile crane, and inspection of installed prefabricated members. The approach offers support to personnel in collecting data, accessing information, and manipulating the data and information. In addition, the approach processes the data and information based on the current conditions. With this scheme, personnel perceive the actual conditions and perform the operation based on the provided information, which is displayed in graphical format. Some of the actions in an installation process were replaced using the processes of an automation approach. Thus, the knowledge and skill requirements of personnel can be reduced. This reduction affects the duration and quality of construction processes directly.
DOI: 10.14457/cu.the.2012.246
title: Synthesis and properties of mucoadhesive thiolated chitosan for simvastatin delivery system

description: The objective of this research was to prepare a mucoadhesive thiolated chitosan suitable for delivery of hydrophobic drugs. This can be achieved by modification of chitosan with 5-amino-2-mercaptobenzimidazole (MBI) using methyl acrylate (MA) as a linker agent. The substitution of MA was about 14.38% calculated by 1H NMR. The amounts of thiol groups (MBI) and disulfide bonds coupled on MA-CS determined by Ellman’s method were 11.86 and 6.54 μmol per gram of polymer, respectively. Periodic acid: schiff (PAS) colorimetric method was used to study mucin-conjugated polymer bioadhesive strength in the simulated gastrointestinal fluid (pH 1.2, 4.0 and 6.4). The MA-CS and MBI-MA-CS showed stronger mucoadhesive property 10.28 and 11-fold, respectively than that of unmodified chitosan at pH 1.2. Additionally, the applications of CS and modified CS as hydrophobic drug delivery carriers were investigated using simvastatin (SV) as a model drug. The microspheres of CS and modified CS were fabricated using electrospray ionization technique. The swollen particle sizes of microspheres were in the range of 1-5 µm measured by particle sizer. The SV loaded microspheres exhibited over 80% drug entrapment efficiency. The mucoadhesiveness of SV-MA-CS and SV-MBI-MA-CS microspheres displayed 7- and 7.33-fold at pH 1.2, respectively compared to SV-CS. The obtained microspheres not only reduced the burst effect but also prolonged release of SV as long as 12 h.