This workshop is presented by members of a University of North Texas research team. First, the team will overview their experience as members of the research team and share experience in areas such as trust formation, team roles, productivity, work-life balance, faculty-students interaction, peer and faculty mentorship, dissertation preparation, and job seeking. Second, the workshop will discuss and brainstorm how this format can be implemented for organizations both with faculty-student teams and with peer-directed teams. Finally, successes and challenges are openly discussed with audience.

The 17th International Conference on Knowledge Management was held in the historic city of Potsdam, Germany. Since the conference was among the first post-pandemic face to face conferences, the overall theme of the 17th edition of the ICKM conference rightly focused on “Knowledge, Uncertainty and Risks: From individual to global scale” at different levels of analysis and agency. This document highlighted one of the panels that provide an overview of the different methodologies and theories of sense-making from several of the seminal originators of sensemaking.

Global warming is the term used to describe critical environmental issues and concerns. Social media such as Twitter provides a platform for people to share information, exchange ideas, and express their opinions about current and timely issues. This study utilized contextual analysis to analyze data collected from Twitter for the hashtag "global warming" during the period 2010 & 2011. Using sentiment analysis and topic modeling, the study aimed first at assessing people's perception towards global warming issues, and second study the impact of misinformation from the standpoint of social noise on people's perception of global warming during critical environmental events. The outcome of this study helps create a better understanding of the environmental issues discussed on social media. The sentiment analysis from the data analyzed so far shows that most of the tweets were based on Twitter users' personal opinions and not science. The topic modeling results suggest that Twitter users typically tweeted when a major environmental event occurred due to global warming. Topic modeling also aids in the identification of terms that is associated with social noise. The presence of social noise suggests that misinformation does exist and spreads faster.

Building predictive models for companies often relies on inference using historical data of companies in the same industry sector. However, companies are similar across a variety of dimensions that should be leveraged in relevant prediction problems. This is particularly true for large, complex organizations which may not be well defined by a single industry and have no clear peers. To enable prediction using company information across a variety of dimensions, we create an embedding of company stocks, Stock2Vec, which can be easily added to any prediction model that applies to companies with associated stock prices. We describe the process of creating this rich vector representation from stock price fluctuations and characterize what the dimensions represent. We then conduct comprehensive experiments to evaluate this embedding in applied machine learning problems in various business contexts. Our experiment results demonstrate that the four features in the Stock2Vec embedding can readily augment existing cross-company models and enhance cross-company predictions.

Considerable research has been conducted on the topic of information overload using different approaches, from marketing and customer demand to information technologies and sciences, and even among mental health professionals. In business the critical question is how does information overload impact processes, operations, and profitability, and how can data visualization help to solve issues with data management and consumption in organizations. The ability to quickly and effectively process information and make decisions equates to organizational survival in a dynamic, knowledge-based economy where all segments of society are heavily affected by information technologies and systems and data management industries. The growing number of systems apparatuses challenges both individuals and organizations, resulting in reports of fatigue and experiences that compromise successful performance. The objective of this literature review is to discuss how data visualization tools help address information overload and optimize decision making and the business intelligence process in organizations. It concludes that data visualization, indeed, is critical in helping individuals capture, manage, organize, visualize, and present understandable data, but that decision making is affected by cognitive factors that interfere with data processing and interpretation in decision makers.

This article investigates low-level laser therapy for brain tumor treatment. The results provide evidence that the paired optical-driven agents provide a tunable platform that can generate significant U251 cell death increase.

Article on the composition of the four cell wall fractions in diverse maize genotypes and to understand how this composition influences the resistance to pests, ethanol capacity and digestibility. Results evidence that there is no maize cell wall ideotype among the tested for optimal performance for various uses, and maize plants should be specifically bred for each particular application.

Article presents research where friction stir additive manufacturing technique was employed to fabricate AZ31B magnesium-hydroxyapatite composite. The study aims to evaluate effect of hydroxyapatite (HA, Ca₁₀(PO₄)₆OH₂), a ceramic similar to natural bone, into AZ31B Mg alloy matrix on biomineralization and biocompatibility.

Article conducting an intensive study on the problems of low recognition efficiency and noise in the overlapping structure of protein functional modules, based on topological characteristics of PPI network. Developing a protein function module recognition method ECTG based on Topological Features and Gene expression data for Protein Complex Identification. The experimental results show that the ECTG algorithm can detect protein functional modules better.

This article formulates a within-subject Bayesian rate ratio effect size (BRR) for autocorrelated count data that would obviate the need for small sample corrections. The authors illustrate this within-subject effect size using real data for an ABAB design and provide codes for practitioners who may want to compute BRR.

Article showing that a recently identified protein termed LD-associated protein [LDAP]-interacting protein (LDIP) works together with both endoplasmic reticulum-localized SEIPIN and the LD-coat protein LDAP to facilitate LD formation in Arabidopsis thaliana. The data is discussed in the context of a new model for LD biogenesis in plant cells with evolutionary connections to LD biogenesis in other eukaryotes.

This article examines the UV/X-ray properties of 1378 quasars in order to link empirical correlations to theoretical models of the physical mechanisms dominating quasars as a function of mass and accretion rate.

This article proposes an urban nutrition (UN) extension to the previously published urban ecological economic system. The proposed extension can be used by decision makers worldwide to evaluate how landscape configurations and agricultural production systems affect the nutritional needs of the local population while fostering sustainable practices.

Article presents research that explores proanthocyanidin (PA) biosynthesis routes in plants. The data suggests that different species have evolved different routes for PA biosynthesis.

This article investigates global metabolic responses to lignin pathway perturbations in the model grass Brachypodium distachyon using a systems biology approach.

Presentation on SciFinder-n and the updates made from SciFinder. It was presented at the STEM Librarians South Conference which was held virtually on July 16, 2020.

This presentation provides an overview of the landscape and factors to consider in choosing among the options for printing and selling an open textbook.

This article develops a molecular cell tracker with a strong fluorescence signal in the second near-infrared (NIR-II) window (1,000-1,700 nm) for real-time monitoring of in vivo cell behaviors in both healthy and diseased animal models to address the issue of precisely and quantitatively evaluating the in vivo cell distribution, migration, and engraftment in stem cell therapy.

This article uses three common open-access satellite image datasets (Sentinel-2B, Landsat-8, and Gaofen-6) for extracting information on rocky desertification in a typical karst region (Guangnan County, Yunnan) of southwest China, using three machine-learning algorithms implemented in the Python programming language: random forest (RF), bagged decision tree (BDT), and extremely randomized trees (ERT).

This article presents the governing equations and analytical solutions of the classical and shear deformation theories of functionally graded axisymmetric circular plates.

This article presents findings from a series of related studies exploring aspects of Digital Humanities teaching, education, and research in iSchools, often in collaboration with other units and disciplines. Results provide a snapshot of the current state of digital humanities in iSchools which may usefully inform the design and evolution of new DH programs, degrees, and related initiatives.

Article indicating directions in which the field of Developmental Physiology might move. It suggests three categories of challenges: demonstrating broad relevance, promoting conceptual advances, and improving experimental approaches.

This document is intended to be a resource for library employees who wish to create a land acknowledgment for various aspects of their work. Creating land acknowledgments is not required, and they represent the perspective of the individual not the libraries or university.

Article highlighting the potential of utilizing additive manufacturing of HEAs for use in extreme environments that require a combination of tribo-corrosion resistance, mechanical durability, extended service life, and net shaping with low dimensional tolerance.