cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19358783.v1
title: Dataset for The Relationship of Coach-Created Motivational Climate to Teamwork Behaviors in Female Collegiate Athletes.sav

description: Although the development of, and engagement in, teamwork behaviors, such as understanding their purpose, developing and executing plans, and nurturing teammate relationships, would be expected to emerge from coach-created task-involving climates, no study has examined this connection. Thus, we examined how athletes’ perceptions of the coach-created motivational climate relate to beliefs about their team’s teamwork behaviors (e.g., Preparation, Execution). Participants were female NCAA Division I collegiate athletes (<i>N </i>= 536; <i>M</i><sub>age </sub>= 20.13 years, <i>SD </i>= 1.36; 79.3% White) who completed the Perceived Motivational Climate in Sport Questionnaire and the Multidimensional Assessment of Teamwork in Sport – Short Form. Hierarchical and nonhierarchical cluster analyses revealed that the athletes were experiencing one of three coach-created motivational climates: low task/high ego, moderate task/moderate ego, and high task/low ego. There was a significant main effect for the motivational climate clusters in relation to the five teamwork areas, Pillai’s Trace = .154, <i>F</i>(10, 1048) = 8.76, <i>p</i> &lt; .001, partial η<sup>2</sup> = .08. Post-hoc descriptive discriminant analysis (DDA) revealed a single significant function, Wilk’s Λ = .848, χ<sup>2</sup>(10) = 87.66, <i>p</i> &lt; .001, on which all five areas contributed. The motivational clusters’ group centroids were significantly different, <i>F</i>(2, 533) = 47.64, <i>p</i> &lt; .001, partial η<sup>2</sup> = .15; athletes in high task/low ego motivational climates endorsed a higher level of teamwork behaviors compared to those in moderate task/moderate ego (<i>d</i> = .54) and low task/high ego (<i>d</i> = 1.14) climates. These findings suggest the importance of coach-created motivational climates on the teamwork behaviors athletes endorse.
DOI: 10.14457/tu.the.2021.80
title: An integrated network design and inventory optimization model considering the product freshness

description: Because of the increasing globalization and dynamic customer requirements, the company nowadays starts thinking about how to design the distribution networks in conjunction with when and how many products are placed to store in the distribution center to gain effective performance over the supply chain. In this regard, this thesis introduces an integrated network design and inventory optimization model considering a perishable supply chain under the sustainable perspective. The model determines the optimal inventory decisions, ordering quantity and frequency, for opened distributors to fulfill the customer demand over a planning period. The proposed model is multi-objective which simultaneously optimizes the profit, freshness loss of products at the point of demand fulfillment, and the solid waste stress of the supply chain. It is noted that the model takes the environmental and social aspects into account. The freshness loss value is regarded as the social sustainability performance metric. It is expected that the minimization of freshness loss contributes to the improved well-being of customers. Besides, the proposed model is capable of tracking the product’s remaining shelf life and accounting for the amount of waste generated when it expires. On the other hand, the accumulated solid waste of locations is taken into account as the way to measure the company’s environmental responsibility. In the resulting analysis, a numerical case is used to demonstrate the model utilization and the decision-making process. Max-Min Operator is then used to solve a multi-objective model. The model resulting shows tradeoffs among objectives. Additionally, the decision-maker is able to observe the influences of the environment and society along with the economic aspects of supply chain-related decisions, and vice versa.
DOI: 10.14457/tu.the.2021.81
title: Product strategy to avoid overstocking and regain customer retention

description: This study relied heavily on online customer evaluations to uncover a problem with perfume bottle gripping comfort, which was restricting customer readiness to purchase. The lack of ergonomic design in high capacity perfume bottles due to improper dimension was the primary cause of problems with comfortable gripping. A rectangular-shaped bottle was chosen as the study's basis by local users in a preference poll. Taguchi designed his experiment based on the extraction of dimensions from a rectangular bottle. Bottle samples were created utilizing the rapid prototyping (RP) technology – 3D Printer based on the experimental design. On bottle samples for grip comfort, Kansei words were used to elicit client feelings. Grey relational analysis was utilized in this study to evaluate the replies and determine the right dimension elements that resulted in the most pleasant grip and ergonomically built perfume bottle. The perfume bottle's optimized design will improve customer readiness to purchase and decrease overstock inventory.
DOI: 10.14457/tu.the.2021.82
title: Resilience factors for ICT industry during COVID 19 pandemic in Thailand

description: COVID-19 pandemic was impacting in ICT industry. This article aims to investigate the resilience factors for ICT industry during COVID-19 in Thailand through the qualitative and quantitative analysis. The qualitative research was conducted by interviewing with top executives of 3 ICT firms and analyzed by thematic analysis to identify their resilience factors. There are five resilience factors identified from thematic analysis and literature review. The quantitative research was conducted by using Analytic Hierarchy Process (AHP) to identify the ranking for each factor. AHP survey was distributed to fifteen experts who have at least the manager position. The most importance factors to be resilience companies are experience management, profitability, and education background in the order.
DOI: 10.14457/tu.the.2021.83
title: Self-assembly patterning of MXene onto silicon substrate

description: Nowadays, two-dimensional nanomaterials were acquired significant interest from scientists due to their excellent properties applied in vast application fields, especially Titanium-based MXene -Ti3C2Tx. Diverse morphologies of MXene were synthesized for certain applications, from multilayer films to monolayer sheets. Therefore, It has required various techniques, such as printing, patterning, and deposition to create MXene film with different thicknesses. Here, a micropatterning strategy is demonstrated to achieve stable and selective MXene adsorption through the molecular-driven assembly. MXene flakes were assembled by strong interaction with a silicon substrate, which was functionalized by micro-contact printing (μCP) to create an active surface. A clear micropattern was observed by SEM showing the uniform coverage of MXene flakes. AFM revealed pattern thickness around 50 nm, much thinner than the patterns obtained by direct μCP. The obtained micropattern presents good stability against rinsing and sonication. XPS shows that this stability can be attributed to strong covalent bonding between MXene and active molecules on a silicon substrate. Moreover, the sheet resistance of the as-formed MXene layer was measured at around 154.69 (Ω/□), which is lower than that of other published techniques with similar thickness around 50 nm. This method can achieve a well-defined MXene pattern around the sub-100 µm scale without requiring prior MXene surface modification. Therefore, MXene can retain its intrinsic surface property, allowing further molecule adsorption as a sensing platform. Moreover, this patterning technique does not require complicated control of ink preparation and offers possible application on any geometry substrate with few layers of thickness.For practical application, MXene was used to assembly layer-by-layer with Polyaniline (PANI) onto sensing device available graphene electrode to detect ammonia (NH3) gas. As a result, the sensitivity (∆R/Ra %) was calculated up 129.31% for 80 ppm NH3 by a sensor with 5 layers of PANI/MXene, which indicated the effectivity of combination between MXene and PANI. In addition, the layer-by-layer method was also valuable to optimize and adjust the sensing layer thickness to improve the sensing performance.
DOI: 10.14457/tu.the.2021.85
title: Determining (s, S) inventory policy for health care system: a case study of hospital in Thailand

description: The inventory optimization problems are required an appropriate optimization model. In this paper, an (s, S) policy is determined by using a simulation-optimizationapproach for a periodic review inventory system at a pharmacy department of a major hospital in Thailand. The simulation, which imitates the inventory system behavior, is constructed on a spreadsheet simulation, while the cyclic coordinate method with golden section search is adopted as the optimization algorithm. Solutions from the search algorithm are evaluated using the simulation, which features randomly generated demand and lead time data from empirical distributions of actual data. The objective is to minimize total inventory costs, including ordering, holding, and shortage costs. Thismodel is applied for ten medicine items, selected as representatives of the entire item range in the pharmacy department. According to the simulation results, a minimal cost inventory policy for each item is obtained within a short amount of run time. This indicates the efficiency and effectiveness of the proposed approach for this type of problem.
DOI: 10.14457/tu.the.2021.86
title: Forecasting hotel room cancellations by using machine learning

description: Cancellation can make a bad effect on hotel revenue management. When cancellation is made, it means that they have a lost income from an unoccupied room.Cancellation has many causes. For example, business schedule, holiday, disease bad environment, and other factors. This Independent study aims to develop machine learning to reduce hotel room booking cancellations.An accurate forecast is a crucial technique for the hotel industry. And a critical tool for predicting booking cancellation. Much Research is supposed that within the present technology and machine learning. Booking cancellation can be forecast by building a model. Hotel is truly little known about the reason that makes customer cancel the booking, so cancellation is a crucial thing that hotel needs to focus on. This research aims to develop a hotel room management system by using machine learning in order to predict hotel room cancellation to satisfy customers’ demands and improve revenue management. This independent study will use RapidMiner as a tool and will use Artificial Neural Network, K nearest neighbor, and Decision Tree analysis as a model in order to predict the cancellation of customer’s demand to improve the efficiency of an unoccupied room. This independent study focuses on the use of unusual variables that another research did not use. If a cancellation can be forecasted it will be able to improve in many areas of the hospitality industry. For example, in-room management, predicting cancellations can be able to produce accurate pricing models for hotel rooms.
DOI: 10.14457/tu.the.2021.87
title: Optimization of vehicle routing problem in cold chain network: a case study in a convenience store business, Thailand

description: This study is referred to the real case of cold chain distribution in Thailand. The effectiveness of cold chain management in perishable food is important when transporting with requirements which are travel time, control temperature, and cost. However, mismanagement in cold chain distribution caused huge losses in logistics distribution. Since the study presents a mathematical model and applies it to the vehicle routing to minimization of related costs and satisfy constraints. The study displays routing from distribution centers to retailers to investigate the shortest distance to deliver products in cold chain management. The analysis encoded results from the CPLEX application and examine the cost analysis compare to cost from supplier. Study in trends of demands allows the truck planners to coordinate a number of trucks, quantity to balance with capacity, optimize the shortest route, monitor inventory, and realized in lower total cost. Furthermore, the impact of results operated three cases of sensitivity analysis. To conclude, the results from the algorithms were better than manual. The results appear appropriate total cost, the number of trucks, and truck efficiency.
DOI: 10.14457/tu.the.2021.88
title: Modified decision tree model for fraud detection application

description: Due to the expansion of e-commerce, the number of transactions made using debit and credit cards has grown which also comes with the increase in fraud. Detecting fraudulent transactions can help the company to make a decision and take action before the loss has occurred. This research aims to develop a machine learning model that can be applied to detect fraud from online transaction data.Regarding the logistics and supply chain application, this research focus on extracting usable information from the data by applying a machine learning model. Naturally, data related to this field consists of a high different proportion between normal and fraudulent transactions. To handle this problem, the under-sampling method is used to balance the data. The models are developed from the decision tree algorithm which is the white box operation that each learning step of the model can be observed. Performance measurement of the models is from observation of accuracy, precision, and recall. The mathematical model is developed under two assumptions, loss of the company equal to the value of order and penalty from suspecting normal order is occurred in percentage discount offered, to descript that which model suitable to which situation.The research outcomes can be concluded that, first, the modified decision tree model is developed and can process the real-world data set with high performance. Second, the proportion of the majority class has a negative correlation with the performance of detecting fraud. Finally, the mathematical model can select the best model according to the assumption, which is considered to be the company policies.
DOI: 10.14457/tu.the.2021.89
title: Factors affecting sales stimulation during the COVID-19 pandemic: perspectives of e-commerce platforms in Thailand

description: During the COVID-19 pandemic past few months (March-October,2020), our world has been led to dramatic losses and has been presented an unprecedented challenge to public health by the virus. The social and economic disruption have been ruined and it takes a lot of time to recover this situation. The virus has been affecting a whole supply chain system. Both local and international trade restrictions cause economic disruption. Thousands of businesses that did not adapt to right now globalization have fallen so as the online retail businesses or e-commerce.This research aims to study about how the managers of e-commerce platform think about what factors affect sales stimulation in Bangkok, Thailand. The software that is used to conduct this research is an Analytic Hierarchy Process (AHP) which all processes are based on comments between factors transforming to quantitative values. The weight between factors is judged by business owners or executive managers who have experiences and the platforms must be run for more than 1 years in Thailand, moreover, the respondents must have an ability to evaluate the criteria through pair-wise comparisons
DOI: 10.6084/m9.figshare.19358789.v1
title: Dataset for "Cumulative Advantage and Citation Performance of Repeat Authors in Scholarly Journals."

description: Aggregated dataset for PLOS One article.
DOI: 10.6084/m9.figshare.19358789
title: Dataset for "Cumulative Advantage and Citation Performance of Repeat Authors in Scholarly Journals."

description: Aggregated dataset for PLOS One article.
DOI: 10.5517/ccdc.csd.cc29yfvk
title: CCDC 2143459: Experimental Crystal Structure Determination

description: Related Article: Philip M. Keil, Terrance J. Hadlington|2022|Chem.Commun.|58|3011|doi:10.1039/D2CC00422D
DOI: 10.5517/ccdc.csd.cc29038q
title: CCDC 2115262: Experimental Crystal Structure Determination

description: Related Article: Mikiya Kato, Tomoya Fukui, Hiroyasu Sato, Yoshiaki Shoji, Takanori Fukushima|2022|Inorg.Chem.|61|3649|doi:10.1021/acs.inorgchem.1c03758
DOI: 10.5517/ccdc.csd.cc29yfrg
title: CCDC 2143456: Experimental Crystal Structure Determination

description: Related Article: Philip M. Keil, Terrance J. Hadlington|2022|Chem.Commun.|58|3011|doi:10.1039/D2CC00422D
DOI: 10.5517/ccdc.csd.cc29yfsh
title: CCDC 2143457: Experimental Crystal Structure Determination

description: Related Article: Philip M. Keil, Terrance J. Hadlington|2022|Chem.Commun.|58|3011|doi:10.1039/D2CC00422D
DOI: 10.5517/ccdc.csd.cc29yftj
title: CCDC 2143458: Experimental Crystal Structure Determination

description: Related Article: Philip M. Keil, Terrance J. Hadlington|2022|Chem.Commun.|58|3011|doi:10.1039/D2CC00422D
DOI: 10.5517/ccdc.csd.cc29yfwl
title: CCDC 2143460: Experimental Crystal Structure Determination

description: Related Article: Philip M. Keil, Terrance J. Hadlington|2022|Chem.Commun.|58|3011|doi:10.1039/D2CC00422D
DOI: 10.5517/ccdc.csd.cc2801fs
title: CCDC 2085414: Experimental Crystal Structure Determination

description: Related Article: Ş. Çakmak, B. Koşar Kırca, A. Veyisoğlu, H. Yakan, C.C. Ersanlı, H. Kütük|2022|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|78|201|doi:10.1107/S2053229622002066
DOI: 10.5281/zenodo.5848047
title: Dataset: A New Infrared Criterion for Selecting Active Galactic Nuclei to Lower Luminosities

description: The dataset accompanying the paper "A New Infrared Criterion for Selecting Active Galactic Nuclei to Lower Luminosities" (Hviding et al. in prep)
DOI: 10.13023/bkf8-z725
title: Single Nucleus RNA Sequencing of Human Sural Nerve Injury

description: Single nucleus RNA sequencing of human sural nerve injury collected from two participants at A proteomic analysis, using mass spectrometry and immunoassays, of the human peripheral nervous system's response to a transection injury. We obtained, from the same participants, the protein levels in freshly cut and degenerating human sural nerve tissue.
DOI: 10.6084/m9.figshare.14936052.v2
title: Maps of cropping patterns in China during 2015-2020

description: Here we present the first annual 500-m maps of multiple cropping systems in china at national scale during 2015 to 2020,which provide information on cropping intensity with descriptions of three staple crops (Maize,paddy rice and wheat). We produced the cropping patterns maps by developing phenological metrics, which can be applied to national scale.
DOI: 10.7910/dvn/bzyrde
title: Replication Data for: Board of Directors' Interlocks: A Social Network Analysis Tutorial

description: Our tutorial describes and provides examples of data collection, directors'’ data treatment, and the use of these data to map and measure network structural properties using an open-source tool -– R statistical software.
DOI: 10.5519/qd.z0porg3d
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5281/zenodo.6354922
title: Scattering and absorption coefficients calculated from size distributions and absorption photometer data at Dome C, Antarctica

description: The file contains the scattering and absorption coefficients presented in Virkkula et al.: Aerosol optical properties calculated from size distributions, filter samples and absorption photometer data at Dome C, Antarctica and their relationships between seasonal cycles of sources, ACP-2021-562.
description: {"references": ["Virkkula et al.: Aerosol optical properties calculated from size distributions, filter samples and absorption photometer data at Dome C, Antarctica and their relationships between seasonal cycles of sources, ACP-2021-562."]}
DOI: 10.5281/zenodo.6354921
title: Scattering and absorption coefficients calculated from size distributions and absorption photometer data at Dome C, Antarctica

description: The file contains the scattering and absorption coefficients presented in Virkkula et al.: Aerosol optical properties calculated from size distributions, filter samples and absorption photometer data at Dome C, Antarctica and their relationships between seasonal cycles of sources, ACP-2021-562.
description: {"references": ["Virkkula et al.: Aerosol optical properties calculated from size distributions, filter samples and absorption photometer data at Dome C, Antarctica and their relationships between seasonal cycles of sources, ACP-2021-562."]}
DOI: 10.5281/zenodo.6354932
title: A Comparative Analysis of Agile Teamwork Quality Models.

description: Supplementary material for article A Comparative Analysis of Agile Teamwork Quality Models.
DOI: 10.5281/zenodo.4763134
title: A Comparative Analysis of Agile Teamwork Quality Models.

description: Supplementary material for article A Comparative Analysis of Agile Teamwork Quality Models.
DOI: 10.34740/kaggle/dsv/3301786
title: Our World in Data - COVID-19
DOI: 10.25345/c5jd4ps4n
title: MassIVE MSV000089058 - Phaeodactylum tricornutum first extraction
title: 15 uL injected onto a C-18 PS column. Extracted with Methanol chloroform water
DOI: 10.34944/dspace/7467
title: 3D Data Creation to Curation: Community Standards for 3D Data Preservation, Chapter 4: Metadata Requirements for 3D Data, Appendix: Survey 1 Results and Survey 2 Results

description: Data on metadata practices from different institutions managing 3D data. Consists of results from Surveys 1 and 2 distributed by the metadata working group of the Community Standards for 3D Preservation (CS3DP) project. Dataset consists of a spreadsheet of data shared from institutions and organizations and a PDF summary from Google form. CS3DP project received funding from the Institute of Museum and Library Services.
description: The “Metadata Requirements for 3D Data” chapter provides recommendations for metadata based on the five-stage digital asset lifecycle. The “Create” section covers some of the principal ways 3D models are created and discusses what metadata can be captured during the creation process. This section looks at not only what metadata could be captured during model creation, but also why capturing that information is important. The “Manage” section covers the metadata needs for organizing, verifying, and providing access to 3D data. Recommendations include grouping files together as much as possible (by 3D object, by collection of objects, and by project) in order to apply organizational metadata that can be used for access and reuse purposes. The Distribution and Publication section discusses the need for a variety of distribution platforms that support the broadly varying metadata needs of different disciplines. Examples include the need for more granular metadata to support reproducibility and privacy in certain fields, as well as concerns around metadata requirements for accessibility for disability more broadly. Though the circulation and access norms for 3D data are still evolving, the Access and Reuse section posits key metadata anticipated to be useful in the discovery and access of 3D data and models for research or reuse. The “Archive” section utilizes PREMIS as a basis for its recommendations. The rapid changes in the tools and platforms that support the creation and utilization of 3D data results in heavier emphasis on metadata that provides context to data that is often no longer supported by the latest technologies. Additional portions of PREMIS that may be of interest to readers are also specified. The chapter ends with an overall table of recommended metadata fields along with future work needed, naming annotation metadata and metadata for accessibility needs as top priorities for standardization and best practice recommendations.