Development Of Database Research Articles

Molecular composition of dissolved organic matter across diverse ecosystems: Preliminary implications for biogeochemical cycling

Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) has been widely applied to characterize the molecular composition of dissolved organic matter (DOM) in different ecosystems. Most previous studies have explored the molecular composition of DOM focused on one or a few ecosystems, which prevents us from tracing the molecular composition of DOM from different sources and further exploring its biogeochemical cycling across ecosystems. In this study, a total of 67 DOM samples, including soil, lake, river, ocean, and groundwater, were analyzed by negative-ion electrospray ionization FT-ICR MS. Results show that molecular composition of DOM varies dramatically among diverse ecosystems. Specifically, the forest soil DOM exhibited the strongest terrestrial signature of molecules, while the seawater DOM showed the most abundant of biologically recalcitrant components, for example, the carboxyl-rich alicyclic molecules were abundant in the deep-sea waters. Terrigenous organic matter is gradually degraded during its transport along the river-estuary-ocean continuum. The saline lake DOM showed similar DOM characteristics with marine DOM, and sequestrated abundant recalcitrant DOM. By comparing these DOM extracts, we found that human activities likely lead to an increase in the content of S and N-containing heteroatoms in DOM, this phenomenon was commonly found in the paddy soil, polluted river, eutrophic lake, and acid mine drainage DOM samples. Overall, this study compared molecular composition of DOM extracted from various ecosystems, providing a preliminary comparison on the DOM fingerprint and an angle of view into biogeochemical cycling across different ecosystems. We thus advocate for the development of a comprehensive molecular fingerprint database of DOM using FT-ICR MS across a wider range of ecosystems. This will enable us to better understand the generalizability of the distinct features among ecosystems.

The utility of transcriptomics in the conservation of sensitive and economically important species

The utility of transcriptomics in the conservation of sensitive and economically important species

P14-089-23 Development of Food Patterns Equivalents Database for Use With WWEIA, NHANES 2017–March 2020 Pre-Pandemic

P14-089-23 Development of Food Patterns Equivalents Database for Use With WWEIA, NHANES 2017–March 2020 Pre-Pandemic

Characterization and classification of urban weed species in northeast China using terrestrial hyperspectral images

AbstractWeeds contribute to biodiversity and a wide range of ecosystem functions. It is crucial to map different weed species and analyze their physiological activities. Remote sensing techniques for plant identification, especially hyperspectral imaging, are being developed using spectral response patterns to vegetation for detection and species identification. A library of hyperspectral images of 40 urban weed species in northeast China was established in this study. A terrestrial hyperspectral camera was used to acquire 435 hyperspectral images. The hyperspectral information for each weed species was extracted and analyzed. The spectral characteristics and vegetation indices of different weeds revealed the differences between weed species in the cities of northeast China and indirectly characterized the growth and physiological activity levels of different species, but could not effectively distinguish different species. Five methods—first derivative spectrum (FDS), second derivative spectrum (SDS), standard normal variate (SNV), moving averages (MA), and Savitzky-Golay (SG) smoothing—were used to pretreat the spectral curves to maximize the retention of spectral characteristics while removing the influence of noise. We investigated the application of a convolutional neural network (CNN) with terrestrial hyperspectral remote sensing to identify urban weeds in northeast China. A CNN classification model was established to distinguish weeds from the hyperspectral images and demonstrated a test accuracy of 95.32% to 98.15%. The accuracy of the original spectrum was 97.45%; SNV had the best accuracy (98.15%) and SG was the least accurate (95.32%). This provides a baseline for understanding the hyperspectral characteristics of urban weed species and monitoring their growth. It also contributes to the development of a hyperspectral imaging database with global applicability.

Development of a food composition database of different food contaminants CONT11 and estimation of dietary exposure in children of southern Spain.

Increasing food security is one of the Sustainable Development Goals. One of the main risks in food is the increase in food contaminants. Processing methods, such as the addition of additives or heat treatment, influence contaminant generation and increase their levels in food. The aim of the present study was to create a database using a methodology similar to that of food composition databases but with a focus on potential food contaminants. CONT11 collects information on 11 contaminants: hydroxymethyl-2-furfural, pyrraline, Amadori compounds, furosine, acrylamide, furan, polycyclic aromatic hydrocarbons, benzopyrene, nitrates, nitrites and nitrosamines. This is collected for more than 220 foods obtained from 35 different data sources. A food frequency questionnaire validated for use with children was used to validate the database. Contaminant intake and exposure in 114 children aged 10-11 years were estimated. Outcomes were within the range of values described by other studies, confirming the usefulness of CONT11. This database will allow nutrition researchers to go a step further in assessing dietary exposure to some food components and the association of this with disease, whilst also informing strategies to reduce exposure.

FDI, international trade and global value chains (GVCs): India's GVC participation, position and value capture

Using OECD Trade in Value Added (TiVA) database (2021, 2022) and Asian Development Bank (2022) dataset, this paper indicates that though India's GVC participation rate has risen over time, it was lower than that of several economies in Asia-Pacific and its relative share in participation gains was marginal. Nevertheless, India's relative share in forward and backward GVC content to (and from) the region was not as peripheral. Raising net participation gains will require key enablers, and stimulating the mutually reinforcing FDI-GVC relationship by attracting quality FDI inflows. Findings based on the panel, fixed-effects model support the hypotheses that production-based GVC participation, revealed comparative advantage based on value-added exports, the country's relative economic size, and economic complexity (in medium-to-high technology manufacturing sectors) positively affect economic upgrading through capturing a greater share in world's domestic value-added in an industry while relative GVC position has a negative effect.

Integrating multiple regulations on enzyme activity: the case of phosphoenolpyruvate carboxykinases.

Data on protein post-translational modifications (PTMs) increased exponentially in the last years due to the refinement of mass spectrometry techniques and the development of databases to store and share datasets. Nevertheless, these data per se do not create comprehensive biochemical knowledge. Complementary studies on protein biochemistry are necessary to fully understand the function of these PTMs at the molecular level and beyond, for example, designing rational metabolic engineering strategies to improve crops. Phosphoenolpyruvate carboxykinases (PEPCKs) are critical enzymes for plant metabolism with diverse roles in plant development and growth. Multiple lines of evidence showed the complex regulation of PEPCKs, including PTMs. Herein, we present PEPCKs as an example of the integration of combined mechanisms modulating enzyme activity and metabolic pathways. PEPCK studies strongly advanced after the production of the recombinant enzyme and the establishment of standardized biochemical assays. Finally, we discuss emerging open questions for future research and the challenges in integrating all available data into functional biochemical models.

IMPLEMENTATION OF RELIABILITY CENTERED MAINTENANCE (RCM) IN PERTAMINA HULU ENERGY SUBHOLDING UPSTREAM (PHE SHU) THROUGH PERTAMINA RELIABILITY DATA (PAREDA) DATABASE & APPLICATION DEVELOPMENT

As part of the integrated efforts that need to be made to achieve the target of becoming a world-class energy company, PHE SHU needs to carry out a series of strategic initiative programs related to the implementation of RCM which need to be carried out in several field including all Regions, Zones, Work Areas and Assets. In the context of implementing RCM at PHE SHU, management has carried out a series of massive and simultaneous activities during 2022-2023 period, both debriefing several workshops & socialization of RCM understanding, issuing task forces and director's orders, conducting site visits & field implementation pilot projects in the onshore area (GTC SKG Subang Field) as well as offshore area (GTG X-Ray Jatibarang Field), performing sharing sessions/focus group discussion, review maturity level assessment, initiate various continuous improvement and its replication to other fields, as well as database development and created Pertamina Reliability Data (PAREDA) applications.

ORAL PROSODIC CORPUS: PHONETIC-PHONOLOGICAL AND INTONATIONAL TRANSCRIPTION OF THE TEXT

The paper discusses the role of phonetic-phonological transcription in modern linguistics and its scope of application. The aim of the study is also to identify and present the transcription and prosodic specificity of the text as a sample. After all, in modern linguistics, the prosodic side is not taken into account when transcribing texts. In general, the ratio of prosody and intonation was different in modern Kazakh linguistics. The research is guided by the research works of academician Z.M. Bazarbayeva, who for the first time comprehensively studied the problem of intonation in Kazakh linguistics. Also, in the process of analyzing the text, 8 main intonemic models are given. I.e., along with phonetic transcription, intonation(al) transcription of the text will also be transmitted in order to identify prosodic features. Also, in the process of transcription of the text, each sentence is divided into a syntagma, a rhythmic group in which such components as intensity, melody, pause, tempo are distinguished and described.In the study, models of intonemes of each sentence were created. The results of the research will be useful for conducting research on the prosodic development of the oral sub-corpus database and for the research of master's and doctoral students.

PERANCANGAN SISTEM INFORMASI PENJUALAN PADA TOKO BUKU BINA MEDIA SARANA BERBASIS WEBSITE

Bina Media Sarana bookstore needs to adopt information technology to enhance the efficiency and quality of its book sales services. In this context, the author designs a website-based sales information system to optimize the store's operations and expand its market reach. This study aims to design an effective and practical sales information system for the bookstore. Through needs analysis, intuitive user interface design, structured database development, and website-based system implementation, these objectives can be achieved. The sales information system enables customers to make online book purchases through the store's website. Additionally, it assists the store owner in inventory management, order processing, sales analysis, and shipment tracking. By implementing this system, it is expected that Bina Media Sarana Bookstore can improve operational efficiency, enhance the quality of customer service, and expand market reach through online presence. Furthermore, this system provides a competitive advantage for the store in the increasingly competitive book sales industry in this digital era.

A chemistry-informed hybrid machine learning approach to predict metal adsorption onto mineral surfaces

Historically, surface complexation model (SCM) constants and distribution coefficients (Kd) have been employed to quantify mineral-based retardation effects controlling the fate of metals in subsurface geologic systems. Our recent SCM development workflow, based on the Lawrence Livermore National Laboratory Surface Complexation/Ion Exchange (L-SCIE) database, illustrated a community FAIR data approach to SCM development by predicting uranium(VI)-quartz adsorption for a large number of literature-mined data. Here, we present an alternative hybrid machine learning (ML) approach that shows promise in achieving equivalent high-quality predictions compared to traditional surface complexation models. At its core, the hybrid random forest (RF) ML approach is motivated by the proliferation of incongruent SCMs in the literature that limit their applicability in reactive transport models. Our hybrid ML approach implements PHREEQC-based aqueous speciation calculations; values from these simulations are automatically used as input features for a random forest (RF) algorithm to quantify adsorption and avoid SCM modeling constraints entirely. Named the LLNL Speciation Updated Random Forest (L-SURF) model, this hybrid approach is shown to have applicability to U(VI) sorption cases driven by both ion-exchange and surface complexation, as is shown for quartz and montmorillonite cases. The approach can be applied to reactive transport modeling and may provide an alternative to the costly development of self-consistent SCM reaction databases.

Validation of the Edited Tromsø Infant Faces Database (E-TIF): A study on differences in the processing of children's emotional expressions

Images of emotional facial expressions are often used in emotion research, which has promoted the development of different databases. However, most of these standardized sets of images do not include images from infants under 2 years of age, which is relevant for psychology research, especially for perinatal psychology. The present study aims to validate the edited version of the Tromsø Infant Faces Database (E-TIF) in a large sample of participants. The original set of 119 pictures was edited. The pictures were cropped to remove nonrelevant information, fitted in an oval window, and converted to grayscale. Four hundred and eighty participants (72.9% women) took part in the study, rating the images on five dimensions: depicted emotion, clarity, intensity, valence, and genuineness. Valence scores were useful for discriminating between positive, negative, and neutral facial expressions. Results revealed that women were more accurate at recognizing emotions in children. Regarding parental status, parents, in comparison with nonparents, rated neutral expressions as more intense and genuine. They also rated sad, angry, disgusted, and fearful faces as less negative, and happy expressions as less positive. The editing and validation of the E-TIF database offers a useful tool for basic and experimental research in psychology.

User-Relevant Land Cover Products for Informed Decision-Making in the Complex Terrain of the Peruvian Andes

Land cover in mountainous regions is shaped by a complex web of stressors arising from natural and anthropogenic processes. The co-design process implemented with regional stakeholders in this study highlighted persistent data gaps and the need for locally relevant (thematic, spatial, and temporal) data products, which global alternatives still fail to deliver. This study describes the development of a land cover database designed for the Junín National Reserve (JNR) in Peru as a precursor of a broader effort designed to serve Andean wetland ecosystems. The products were created using Random Forest models leveraging Sentinel-1 and Sentinel-2 data and trained using a large database of in situ data enhanced by the use of high-resolution commercial imagery (Planet). The land cover basemap includes eight classes (two of vegetation) with an overall accuracy of 0.9 and Cohen’s Kappa of 0.93. A second product further subdivided vegetation into locally meaningful vegetation classes, for a total of four types (overall accuracy of 0.85). Finally, a surface water product (snapshot and frequency) delivered a representation of the highly variable water extent around Lake Junín. It was the result of a model incorporating 150 Sentinel-1 images from 2016 to 2021 (an overall accuracy of 0.91). The products were successfully employed in identifying 133 ecosystem services provided by the different land cover classes existing in the JNR. The study highlights the value of participatory monitoring and open-data sharing for enhanced stewardship of social-ecological systems.

INFRA-ART: An Open Access Spectral Library of Art-related Materials as a Digital Support Tool for Cultural Heritage Science

Easily accessible characterization techniques such as X-ray fluorescence (XRF), Fourier Transform Infrared Spectroscopy (FTIR), or Raman spectroscopy, are at this moment the most commonly used analytical tools in heritage and conservation science. Materials identification in works of art is a fundamental step for understanding an object's history or an artist's technique. Comprehensive characterization and diagnosis of the various constituent materials in artworks can provide valuable information on the artist's working methods, as well as significant evidence for dating, provenance attribution, or forgery detection. The development of databases with high-quality data on the pure substances used as artists’ materials is of utmost importance for the identification and characterization of unknown samples. However, there are relatively few open access spectra libraries dedicated exclusively to the cultural heritage field. To address this need, within the frame of the postdoctoral project INFRA-ART, an open access spectral library of art-related materials has been developed. The database is an ongoing compilation of spectra that contains at this moment over 1,000 high-quality attenuated total reflection–FTIR, Raman, and XRF spectra associated with over 500 known reference materials. In this article, a summary of the database structure and design, functionality, and use is presented, in view of the dissemination of this new open access spectral library to the scientific community.

Retrospective cohort observation on psychotropic drug-drug interaction and identification utility from 3 databases: Drugs.com®, Lexicomp®, and Epocrates®.

Pharmacotherapy is necessary for many people with psychiatric disorders and polypharmacy is common. The psychotropic drug-drug interaction (DDI) should be concerned and efficiently monitored by a proper instrument. This study aimed to investigate the prevalence and associated factors of psychotropic DDI and to compare the identification utility from three databases: Drugs.com®, Lexicomp®, and Epocrates®. This was a retrospective cohort design. We collected demographic and clinical data of all patients hospitalised in the psychiatric inpatient unit in 2020. Psychotropic DDI profiles were examined through three databases. Descriptive statistics were used to report comprehensiveness of each database and prevalence of psychotropic DDI. The Fleiss' kappa index would be analysed to indicate agreement strength of DDI severity classification among three databases. From 149 total admissions, the psychotropic DDIs were found in 148 admissions (99.3%). Thorough the study, there were 182 of both psychotropic and other agents prescribed under 1,357 prescriptions. In total, 2,825 psychotropic DDIs were identified by using Drugs.com® 2,500 times, Epocrates® 2,269 times, and Lexicomp® 2,265 times. Interactions with clonazepam was the three most frequent agents when co-administrated with quetiapine (n = 56), risperidone (n = 36), and valproic acid and derivatives (n = 36). Serious DDIs were comparatively lower in incidence and there was no evidence of its association with reported clinical adverse consequences. The study revealed slight and fair agreement regarding severity classification among the three databases was found. DDI events detected by Drugs.com® were greatest in number, but Lexicomp® provided the broadest list of medications prescribed in our study. Among three databases, interactions detected by Drugs.com® were greatest in number, whereas Lexicomp® provided the broadest list of medications. Development of such databases, based on both theoretical and clinical conceptions, should be focused to balance safety of patients and weariness of healthcare providers.

Comparison of Data Modeling Tools in Database Development

Modeliranje podataka je najvažniji dio dizajniranja baze podataka ali i cijelog informacijskog sustava. U procesu izrade relacijske baze podataka kreiranje modela podataka je ključno jer naknadne promjene na bazi podataka nisu poželjne. U prvoj fazi izrade uzimaju se specifikacije od korisnika koje služe za modeliranje podataka. Iz definiranih specifikacija izrađuje se model podataka koji se kreira u tri osnovne faze: izrada konceptualnog, logičkog i na kraju relacijskog, odnosno fizičkog modela. Dok se konceptualni model radi „na papiru“, odnosno skiciraju se osnovni entiteti, atributi i veze, izrada logičkog modela u često uključuje korištenje nekog alata za modeliranje podataka. Ovisno o alatu, iz logičkog modela se može napraviti i relacijski model koji se već smatra dijelom fizičke izrade baze podataka. Pri podučavanju baza podataka i modeliranja kao prve faze iznimno je važno odabrati alat koji je dovoljno jednostavan za studente ali i dovoljno složen da se lako može preslikati na realne sustave u praksi. U ovom radu se kroz izradu modela podataka za bazu podataka o zaposlenicima prikazuje proces izrade modela pomoću različitih alata. Prikazana je usporedba u mogućnostima i opcijama različitih alata za modeliranje, kako besplatnih tako i onih koji su dostupni uz plaćanje pri izradi baze podataka.

Quantitative Study of Butterfly Diversity in Wando Quercus acuta Forest Over 5 Years (2017-2021)

This study presents the long-term quantitative data on butterflies in Wando Arboretum, which represents the only warm-temperate forest located in the southernmost part of South Korea. This arboretum has significant academic value as approximately 770 species of rare woody plants or herbs, such as the Japanese evergreen oak (<i>Quercus acuta</i>), found in warm temperate zones grow under natural conditions here. In this project, the butterflies in this region were studied due to their sensitivity to temperature changes. The study was conducted from March-April to October-November over 5 years (2017-2021) in the region dominated by Japanese evergreen oak. We found 1,743 individuals of 47 butterfly species belonging to five families. The acquired butterfly data could serve as a reference for the further development of a network-oriented database for assessing temporal climate changes.

Tale of Two Tools

Consistent delivery of full-text content has been a challenge for libraries since the development of online databases. Library systems have attempted to meet this challenge, but link resolvers and early direct linking tools often fell short of patron expectations. In the last several years, a new generation of direct linking tools has appeared, two of which will be discussed in this article: Third Iron’s LibKey Discovery and Quicklinks by Ex Libris, a Clarivate company. Figure 1 shows the “Download PDF” link added by LibKey. Figure 2 shows the “Get PDF” link provided by Quicklinks. The way we configured our discovery interface, a resource cannot receive both the LibKey and Quicklinks PDF links. These two direct linking tools were chosen because they were both relatively new to the market in April 2021 when this analysis took place and they can both be integrated into Primo VE, the library discovery system of choice at the authors’ home institutions of SUNY College of Optometry and Ferris State University. Through analysis of the frequency of direct links, link success rate, and number of clicks, this study may help determine which product is most likely to meet your patrons’ needs.

Prospective Study of Associations Between Testosterone, Mortality, and Health Outcomes Among Adults Undergoing Hemodialysis

Prospective Study of Associations Between Testosterone, Mortality, and Health Outcomes Among Adults Undergoing Hemodialysis

Domain Ontology Representation Model Based on Graph Databases

The article presents an approach to modeling domain ontologies based on graph databases. Ontology is traditionally considered as a means of studying and formalizing the subject area. Based on ontologies, knowledge bases of information systems are formed, which can later be replenished and used to study certain applied aspects of the subject area. At the same time, with the development of NoSQL technologies and graph databases aimed at optimizing work with related data, it becomes possible to design a data warehouse without a strict pre-established domain model. Due to the obvious graph nature of ontologies, graph databases are a promising solution for storing and working with ontologies. However, with all the similarities, the ontology and data models used in graph DBMSs are not so easy to combine. The paper proposes an approach to the integration of ontological and graph models of knowledge representation and considers its application in creating a database for a prototype of a web ontology editor. Visual tools for editing ontologies are described, an algorithm for layer-by-layer rendering of a directed graph is given, a mechanism for generating dynamic forms for editing classes and ontology instances is described, and basic support for ontological design patterns is implemented.