Quantitative Rigor Research Articles

Mapping the landscape of social behavior.

Social interaction is integral to animal behavior. However, we lack tools to describe it with quantitative rigor, limiting our understanding of its principles and neuropsychiatric disorders, like autism, that perturb it. Here, we present a technique for high-resolution 3D tracking of postural dynamics and social touch in freely interacting animals, solving the challenging subject occlusion and part assignment problems using 3D geometric reasoning, graph neural networks, and semi-supervised learning. We collected over 140 million 3D postures in interacting rodents, featuring new monogenic autism rat lines lacking reports of social behavioral phenotypes. Using a novel multi-scale embedding approach, we identified a rich landscape of stereotyped actions, interactions, synchrony, and body contact. This enhanced phenotyping revealed a spectrum of changes in autism models and in response to amphetamine that were inaccessible to conventional measurements. Our framework and large library of interactions will greatly facilitate studies of social behaviors and their neurobiological underpinnings.

Improved drug target deconvolution with PISA-DIA using an extended, overlapping temperature gradient.

Thermal proteome profiling (TPP) is a powerful tool for drug target deconvolution. Recently, data-independent acquisition mass spectrometry (DIA-MS) approaches have demonstrated significant improvements to depth and missingness in proteome data, but traditional TPP (a.k.a. CEllular Thermal Shift Assay "CETSA") workflows typically employ multiplexing reagents reliant on data-dependent acquisition (DDA). Herein, we introduce a new experimental design for the Proteome Integral Solubility Alteration via label-free DIA approach (PISA-DIA). We highlight the proteome coverage and sensitivity achieved by using multiple overlapping thermal gradients alongside DIA-MS, which maximizes efficiencies in PISA sample concatenation and safeguards against missing protein targets that exist at high melting temperatures. We demonstrate our extended PISA-DIA design has superior proteome coverage as compared to using tandem-mass tags (TMT) necessitating DDA-MS analysis. Importantly, we demonstrate our PISA-DIA approach has the quantitative and statistical rigor using A-1331852, a specific inhibitor of BCL-xL. Due to the high melt temperature of this protein target, we utilized our extended multiple gradient PISA-DIA workflow to identify BCL-xL. We assert our novel overlapping gradient PISA-DIA-MS approach is ideal for unbiased drug target deconvolution, spanning a large temperature range whilst minimizing target dropout between gradients, increasing the likelihood of resolving the protein targets of novel compounds.

Motivation and self-efficacy are pivotal in driving science learning outcomes

This study explores how self-efficacy and learning motivation impact science cognitive learning outcomes among eighth-grade students. Using a correlational quantitative approach, the research identifies self-efficacy (X1) and learning motivation (X2) as independent variables and cognitive learning outcomes (Y) as the dependent variable. Sampling involves simple random sampling, with data collected through questionnaires and documentation. Analysis stages include normality and linearity tests, followed by correlation tests using SPSS Version 26. Results show a positive and significant influence of self-efficacy and learning motivation on cognitive learning outcomes, highlighting the importance of these factors in shaping science education outcomes for eighth-grade students. Highlight: Performance Dynamics: Self-efficacy and motivation influence science learning outcomes. Quantitative Rigor: Correlational research with SPSS ensures data validity. Educational Enhancement: Insights guide curriculum adjustments for improved science education outcomes. Keyword: Self-Efficacy, Learning Motivation, Science Education, Eighth Grade Students, Correlational Research

The Impact of Physical Education on Mental Health

By combining quantitative rigor with the qualitative depth, this study’s holistic review of how structured physical education affects mental health issues offers unique and valuable insights appreciated both by researchers, practitioners as well policymakers. The research covers a wide range of participants, including students from different levels in education structures, adults as well as individuals with various social backgrounds. With a view to having equal representation across age groups, genders and social statuses the stratified method of sampling was used to generate this report. The inclusion criteria refer to those individuals who participate in regular physical education activities. The MHI, using batteries of age-appropriate standardized tests to measure physical fitness. The meta-analysis of quantitative and qualitative data reveals the major positive effects that both mental health and physical fitness areas have shown in participants after a structured PE course. The holistic approach, which takes into account both objective measures and subjective experiences in this study reveals the positive effect of physical education on mental health. These results imply that high-quality physical education program has the possibility to contribute an increase in general wellbeing, which might be helpful for better mental health indicators.

INVESTIGATING THE IMPACT OF EMPLOYEE-MANAGER RELATIONSHIPS ON JOB SATISFACTION WITHIN THE HOSPITALITY INDUSTRY OF GOA

The hotel industry is booming amidst the scenic surroundings of Goa. This write-up probes deep into the way relationships with the teams of a manager affect work and job satisfaction of employees. Insights from 300 business executives have folded into an in-depth qualitative interviews with the quantitative rigor of surveys. The over-all scaling of Thurstone in a number of factors ranked autonomy, management support, effective communication, conflict resolution, incentives and recognition, and leadership style, among others by observing what actually influence work satisfaction. As compared to that underlying statistic analyses linked job happiness to quality of interpersonal relations at work, and its relationships to specific work schedules were significantly supported by certain job categories and hotel classifications as well. The findings indicated that employees should realize their own self-worth and should be in a position to develop conflict-resolution mechanisms, and open communication taking into consideration the larger economic impact with a satisfied hotel workforce.

Therapeutic targeting of tumor spheroids in a 3D microphysiological renal cell carcinoma-on-a-chip system

Metastatic renal cell carcinoma (RCC) remains an incurable disease for most patients highlighting an urgent need for new treatments. However, the preclinical investigation of new therapies is limited by traditional two-dimensional (2D) cultures which do not recapitulate the properties of tumor cells within a collagen extracellular matrix (ECM), while human tumor xenografts are time-consuming, expensive and lack adaptive immune cells. We report a rapid and economical human microphysiological system (“RCC-on-a-chip”) to investigate therapies targeting RCC spheroids in a 3D collagen ECM. We first demonstrate that culture of RCC cell lines A498 and RCC4 in a 3D collagen ECM more faithfully reproduces the gene expression program of primary RCC tumors compared to 2D culture. We next used bortezomib as a cytotoxin to develop automated quantification of dose-dependent tumor spheroid killing. We observed that viable RCC spheroids exhibited collective migration within the ECM and demonstrated that our 3D system can be used to identify compounds that inhibit spheroid collective migration without inducing cell death. Finally, we demonstrate the RCC-on-a-chip as a platform to model the trafficking of tumor-reactive T cells into the ECM and observed antigen-specific A498 spheroid killing by engineered human CD8+ T cells expressing an ROR1-specific chimeric antigen receptor. In summary, the phenotypic differences between the 3D versus 2D environments, rapid imaging-based readout, and the ability to carefully study the impact of individual variables with quantitative rigor will encourage adoption of the RCC-on-a-chip system for testing a wide range of emerging therapies for RCC.

Unraveling the Threads: A Comprehensive Exploration of the Interplay be-tween Social Isolation and Academic Stress Among Students

In the labyrinthine landscape of student experiences, this research endeavors to unravel the intricate relationship between social isolation and academic stress. Utilizing a mixed-methods approach, our study amalgamates quantitative rigor with qualitative depth to paint a comprehensive portrait of the challenges faced by students navigating the confluence of social dynamics and educational pressures. The primary objective is to understand how social isolation influences the prevalence and intensity of academic stress among students. Through a dual lens of theory and practice, the research aims to contribute to both the theoretical frameworks shaping stress models and the practical interventions implemented within educational institutions. A diverse sample of students across various educational institutions participated in this study. Quantitative data were gathered through structured surveys, probing the prevalence of social isolation and its correlation with academic stress. Qualitative insights were obtained through in-depth interviews and focus group discussions, unraveling the nuanced experiences and coping mechanisms employed by students. The research affirms a significant positive correlation between social isolation and academic stress, establishing a quantifiable connection. Qualitative narratives unveil the emotional dimensions of social isolation, emphasizing loneliness, fear of failure, and a sense of disconnection as prevalent themes. Stressors such as performance expectations and a competitive academic environment emerge as catalysts that intensify stress levels among socially isolated students. Theoretical implications extend to the refinement of stress models by integrating emotional well-being and recognizing intersectionality. Practical implications advocate for tailored institutional support systems, mental health literacy initiatives, and the integration of social support into academic programs. Collaborative efforts between researchers and practitioners are essential to bridge the gap between theory and practice. As this research concludes, it beckons educators, institutions, and policymakers to heed the call for transformative change. By prioritizing the emotional and social well-being of students alongside academic success, we pave the way for educational environments that foster resilience, support, and holistic growth. This research stands as a catalyst for ongoing conversations and actions, recognizing that the journey to understanding and enhancing student experiences is an ever-evolving endeavor

Dynamic Data-Independent Acquisition Mass Spectrometry with Real-Time Retrospective Alignment.

Data-independent acquisition (DIA) mass spectrometry has grown in popularity in recent years, because of the reproducibility and quantitative rigor of a systematic tandem mass spectrometry (MS/MS) sampling method. However, traditional DIA methods may spend valuable instrument time acquiring MS/MS spectra with no usable information in them, affecting sensitivity and quantitative performance. We developed a DIA strategy that dynamically adjusts the MS/MS windows during the chromatographic separation. The method focuses MS/MS acquisition on the most relevant mass range at each point in time─increasing the quantitative sensitivity by increasing the time spent on each DIA window. We demonstrate an improved lower limit of quantification, on average, without sacrificing the number of peptides detected.

The crucial role of elasticity in regulating liquid-liquid phase separation in cells.

Liquid-liquid phase separation has emerged as a fundamental mechanism underlying intracellular organization, with evidence for it being reported in numerous different systems. However, there is a growing concern regarding the lack of quantitative rigor in the techniques employed to study phase separation, and their ability to account for the complex nature of the cellular milieu, which affects key experimentally observable measures, such as the shape, size and transport dynamics of liquid droplets. Here, we bridge this gap by combining recent experimental data with theoretical predictions that capture the subtleties of nonlinear elasticity and fluid transport. We show that within a biologically accessible range of material parameters, phase separation is highly sensitive to elastic properties and can thus be used as a mechanical switch to rapidly transition between different states in cellular systems. Furthermore, we show that this active mechanically mediated mechanism can drive transport across cells at biologically relevant timescales and could play a crucial role in promoting spatial localization of condensates; whether cells exploit such mechanisms for transport of their constituents remains an open question.

On the Utility of Ce3+ Spin−Orbit Transitions in the Interpretation of Rate Data in Ceria Catalysis: Theory, Validation, and Application

Cerium oxide is a ubiquitous component in catalytic systems of industrial and academic interest, and the precise mechanistic function of oxygen vacancies/Ce3+ ions a persistent open question in this regard. Existing methods for quantifying vacancy densities are for the most part indirect in nature, and they either have to necessarily be applied ex situ or, if applicable in situ, are oftentimes limited in applicability or quantitative rigor. We present herein a theoretical and experimental analysis of the utility of 2F5/2–2F7/2 electronic transitions in the quantitative estimation of oxygen vacancy or Ce3+ densities. Application of crystal field theory reveals the nonforbidden nature of 2F5/2–2F7/2 transitions for Ce3+ ions present in a C3v site symmetry environment, unlike free Ce3+ ions in the gas phase that exhibit La Porte forbidden transitions between states of equivalent parity. The molar extinction coefficient for the infrared feature of interest is estimated using three reductants─H2, CO, and ethanol─and applied toward interpretation of ceria-catalyzed H2–D2 exchange and tert-butanol dehydration catalysis rate data. Linear correlations between H2–D2 exchange rates and infrared spectroscopy-derived vacancy densities point to the sole involvement of reduced domains in H2 activation steps prevalent in hydrogenation and hydrodeoxygenation catalysis. Contrastingly, areal tert-butanol dehydration rates that trend inversely with vacancy densities both in the presence and absence of α-hydrogen-containing oxygenates carrying a propensity toward stoichiometric oxidative routes suggest the participation of oxidized, not reduced domains in dehydrative turnovers producing isobutene. The nonforbidden nature of the Ce3+2F5/2–2F7/2 transition─evidenced here using symmetry considerations─likely extends beyond the C3v symmetry environment under consideration here, implying that its fortuitous appearance within the infrared region of the electromagnetic spectrum may render it amenable to quantitative application in relating local structure to catalytic function in ceria catalysis more broadly.

Technology Development Framework: Moving from Qualitative toward Quantitative Decision-Making

Summary Technology development in the energy sector typically suffers from an ad hoc approach to making decisions about the key questions of “What is the next derisking step?” and “At what scale?” This lack of structure in decision-making occurs despite the technology development process usually being within a stage-gated protocol. This often leads to significant waste of time and resources and plenty of “surprises” about the extent of additional testing required. The approach proposed in this paper is relatively simple to use, scalable, and transferable across industry sectors. Consistent application of the methodology has the potential to bring a quantitative rigor that can lead to more effective and efficient technology development and improve both intellectual and monetary capital allocation. Additionally, the framework provided facilitates a more structured and faster learning curve for people moving into technology development roles. Starting with a high-level understanding of the technology and business case, the methodology identifies possible commercial deployments and associates key technical and commercial risks that can be barriers to commercialization. Then, using a “risk burndown” approach based around an initial assessment of probability of success (POS), different paths to deployment (PTDs) are developed. A value of information (VOI) approach is used to evaluate key metrics. This leads to a diverse set of derisking options with associated trade-offs for informed decision-making. The methodology has been developed and deployed since 2017 across a portfolio of both incremental improvement and game-changing subsurface technologies at Suncor Energy, a large integrated Canadian energy company. More than 25 technologies have been progressed using elements of this workflow with 7 of the more complex and expensive projects using the full quantitative VOI approach. These analyses have been used to inform decision-making on more than $400 million1 of proposed derisking activity spend.

Is economics STEM? Process of (re)classification, requirements, and quantitative rigor

From 2012 to 2019, the proportion of undergraduate economics degrees denoted as “Econometrics and Quantitative Economics” (STEM-eligible) conferred annually increased from 1 percent to 22 percent. The authors present results from a survey of the 73 institutions conferring at least one STEM-eligible economics degree in 2017 or 2018. They find that most institutions (59%) offer both traditional and STEM-eligible degrees and report needing departmental, college/university committee, and provost/dean approval to (re-)classify. The main motivation for this change is maintaining consistency with an increasingly quantitative discipline (73%). The significant differences in requirements between STEM-eligible and traditional economics degrees are the proportion requiring single variable calculus (91% vs. 69%), multivariable calculus (70% vs. 31%), linear algebra (48% vs. 21%), basic econometrics (96% vs. 77%), and advanced econometrics (48% vs. 8%).

Q-Methodology and Psychological Phenotyping to Design Patient-Centered Diabetes Education for Persons With Type 2 Diabetes on Insulin Therapy.

The purpose of this study was to identify the psychological phenotypes of persons with type 2 diabetes (T2D) on insulin therapy to better inform personalized diabetes education strategies to improve self-management behaviors. Q-methodology, a research approach combining the quantitative rigor of statistical analysis with qualitative data on perception of diabetes self-management by persons with T2D on insulin therapy, was used. The Summary of Diabetes Self-Care Activity measure and A1C in the past 6 months were used to further describe self-management behaviors of each P-sample, Q-sorter. Of 160 statements, 33 Q-sample statements were selected as Q-set. Then, 37 P-samples (24 men; 13 women) were recruited from a university-affiliated diabetes clinic in South Korea. Data obtained from each P-sample with a Q-set and a Q-sorting table, a forced-choice normal distribution table, were analyzed using varimax rotation. Forty-one percent of the variance was explained with 5 factors represented by 27 Q-sorters, explaining variance ranging from 5% to 17% for each factor: Factor A (n = 6): those showing self-management education need but possessing inadequate health literacy; Factor B (n = 4): those valuing lifestyle modification to control diabetes; Factor C (n = 5): those valuing antidiabetic medication to control diabetes; Factor D (n = 6): carpe diem, accepting diabetes as destiny; and Factor E (n = 6): those overestimating their competencies to control diabetes. Ten Q-sorters fell into either confounded or nonsignificant. Tailoring messages and educational approaches based on patients' psychological phenotypes are necessary to promote optimal self-management behaviors.

Role of blockchain in HR's response to new-normal

PurposeThis study aims to broaden the understanding of the blockchain for human resource (HR) managers through use cases. The study presents a plausible solution for HR professionals to effectively manage some of the core processes to focus on more strategic work and be a true HR business partner for the organization.Design/methodology/approachThe study adopted a case research strategy. The case research strategy is well-suited to capture the practitioner’s knowledge, mainly when focusing on contemporary events (such as COVID-19). Data collected from 12 tech organizations through telephonic conversations and the interviews were recorded and transcribed using NoNotes call recording.FindingsThis study identifies five use cases to streamline the critical processes, helping HR professionals such as certificates verification, skill mapping, payroll processing, data protection and performance management. These early use cases offer a plausibly superior alternative in managing critical HR functions and associated business processes with blockchain technology.Research limitations/implicationsDespite the growing number of blockchain applications, its usage in HR activities is limited. By extensive qualitative case study and data triangulation, the study integrates a resource-based view and unified theory of acceptance by explaining how blockchain adoption helps organizations use their internal resources and capabilities to gain a competitive advantage. The study presents five use cases and propositions that can act as building blocks for the HR department in adopting blockchain applications. Lack of empirical validation (quantitative rigor) of the propositions is the limitation and can be a future research scope.Practical implicationsAdopting new technologies is not new for HR managers. However, most of the technologies are disjointed applications, and therefore, the need for an all-pervasive solution assumes significance. Several of the blockchain concepts are still in the nascent stage. Thus, the study highlights the need for HR leaders to work alongside technical architects to create blockchain applications. Unlike other HR applications, blockchain can integrate all the employees, clients, vendors and businesses seamlessly. This study proposes research propositions that provide research directions for future research.Originality/valueAcademic literature on connecting blockchain technology with HR functions and applications is notably absent. This research can be considered one of the first academic articles connecting blockchain and HR processes.

Ten Years of the 2010 HMG: A Perspective from the Department of Justice

Ten years after their release, the 2010 Horizontal Merger Guidelines continue to reflect accurately current legal and economic principles of antitrust. Despite fears to the contrary, the Antitrust Division still relies on market shares and concentration—along with a wide range of other evidence—to determine whether a merger is likely to harm competition substantially. Similarly, market definition remains an essential ingredient to merger analysis, combining the quantitative rigor of the hypothetical monopolist test with the kinds of qualitative evidence that date back to Brown Shoe. The 2010 Horizontal Merger Guidelines have also contributed to courts’ increasing acceptance of the standard economic tools that are used to quantify the potential impact of horizontal mergers, including merger simulation and upward pricing pressure.

Surrogacy in invasion research and management: inferring “impact” from “invasiveness”

Biological invasions are known drivers of biodiversity decline, yet the ecological impacts of invaders remain largely unmeasured in many contexts. Consequently, other measures of a species invasion (eg local abundance) are often used as surrogates (or “proxies”) to infer impact on recipient ecosystems. However, the use of surrogates for impact in invasion science and management is often implicit, and frequently lacks the evaluation and validation that characterize surrogate use in other fields. Although there are practical reasons for this, the risks associated with not testing the accuracy, stability, and certainty of surrogates for invasive species impact must be acknowledged. Recognizing the role of surrogacy in invasion science offers previously unappreciated solutions for increasing the quantitative rigor of invasive species impact assessments that inform management decisions.

Advancing quantitative rigor in the circular economy literature: New methodology for product lifetime extension business models

Research on product lifetime extension (PLE) is of emerging interest in the circular economy (CE), but the extant literature is deficient in various aspects. First, it lacks a systematic analysis of the structure which underlies organizational efforts to PLE. Second, the literature has overlooked the role of two key agents in circular economy, namely, businesses and consumers. Third, the literature lacks a systematic study of the product lifetime extension strategies. Fourth, although several studies have proposed taxonomies of organizations in the circular economy, they lack quantitative rigor, ecological validity, and generalizability. The purpose of this study is to address these deficiencies in the circular economy literature. Specifically, this article develops and empirically validates a methodology to classify a specific type of circular business model, namely product lifetime extension business models, involving organizations and consumers, to bring quantitative rigor to conduct and presentation of taxonomy research in the field of the circular economy.

Demand Estimation and Forecasting Using Neuroeconomic Models of Consumer Choice

Empirical studies of consumer choice increasingly make use of cognitive process models that incorporate behavioral insights while maintaining quantitative rigor. At the same time, important questions remain regarding their ability to deliver insights that are at once accurate, generalizable, and managerially relevant. We take a step toward addressing these issues by conducting a series of consumer choice experiments and comparing the accuracy and generalizability of the canonical multinomial logit model (MNL) against the drift diffusion model (DDM), a cognitive model that incorporates response times in addition to choice data. We find that the DDM robustly outperforms MNL in providing accurate forecasts on several managerially relevant measures, and that these improvements generalize to out-of-sample scenarios involving new consumers and new choice environments. Perhaps most impressively, relative performance improvements when generalizing across individuals are greater in magnitude than when using holdout choices within the same individuals. Additional analyses further show that these improvements derive from the ability of the cognitive model to capture heterogeneity in the tradeoff between time spent on deliberation and the probability of mistakenly choosing a lower-valued option. We conclude with a discussion of the implications of these findings for theoretical and applied work in consumer choice modeling.

Treatment fidelity in Model of Human Occupation research

Introduction Treatment fidelity is an important consideration in occupational therapy efficacy research. It involves methodological strategies that enhance quantitative rigor and improves confidence in research outcomes. This study examines treatment fidelity in Model of Human Occupation efficacy literature because it is a widely used, occupation-focused theory with a substantial evidence base. Method Relevant articles ( n = 17) were coded for treatment fidelity with the Treatment Fidelity Measure. Percentages of articles reporting treatment fidelity strategies and mean adherence to fidelity strategies were calculated. One-way analysis of variance was used to examine fidelity over time. Results Only one study reported provider training strategies and measured nonspecific treatment effects. Overall mean adherence to treatment fidelity strategies for Model of Human Occupation research was 0.57; one study demonstrated high fidelity with a score of ≥0.80. Model of Human Occupation efficacy literature trends toward higher levels of treatment fidelity over time. Conclusion Model of Human Occupation research demonstrates a moderate level of treatment fidelity overall; it has stronger treatment fidelity from 2001 to the present. As the model progresses toward more outcomes studies, Model of Human Occupation scholars should report provider training and strategies that monitor treatment delivery to improve the quality and applicability of research outcomes.

The forgotten prey of an iconic predator: a review of interactions between grey wolvesCanis lupusand beaversCastorspp.

AbstractPredator–prey relationships can have wide‐ranging ecological and landscape‐level effects. Knowledge of these relationships is therefore crucial to understanding how these systems function and how changes in predator–prey communities affect these systems. Grey wolvesCanis lupuscan be significant predators of beaversCastorspp., and conversely, beavers can be important prey for wolves, but wolf‐beaver dynamics in North America, Europe, and Asia are poorly understood.Our objectives were to synthesise current knowledge regarding wolf‐beaver interactions and to identify knowledge gaps that should be targeted for study to increase our understanding of wolf‐beaver dynamics.During the ice‐free season, beavers are vulnerable to predation and can be the primary or secondary prey of wolves, but the factors that affect beaver consumption by wolves are complex and are likely dependent on biological and environmental factors.High beaver abundance can increase wolf pup survival, and beavers may subsidise wolves during periods of reduced ungulate abundance. Thus, many researchers have suggested that beaver densities adversely affect ungulate populations through apparent competition, though this remains largely untested.The effects of wolf predation on beaver population dynamics are poorly understood, as most assessments are lacking in quantitative rigor and are instead based on indirect methods (e.g. scat analysis), anecdotal evidence, or speculation. To understand the effect of predation on beaver populations fully, better estimates (e.g. from documented predation events) of wolf predation on beavers are necessary.Given the complexities of wolf‐ungulate‐beaver systems, fully understanding wolf‐beaver dynamics will be challenging and is likely to require long‐term, intensive research of wolf, ungulate, and beaver population parameters. Understanding this dynamic has implications, not only for the conservation and management of wolves and beavers, but also for ungulate populations, which are affected by the numerical and functional responses of wolves in these same systems.