Response Variance Research Articles

A Clarified Examination of the Item Wording Effect: Item Valence (Good vs. Bad) Versus Semantic Framing (I Am vs. I Am Not).

The Item Wording Effect (IWE) in psychological testing describes how individuals respond differently to positively and negatively worded items. Previous IWE research faced challenges due to measures varying beyond item valence. This study aimed to address this problem by developing an inventory, the Positive and Negative Descriptor Inventory (PANDI), with items varying solely on valence. Semantic framing was manipulated to examine which factor (valence vs. framing) was more causal of the IWE. Using an online survey on Mechanical Turk, 336 Canadian participants responded to PANDI items in different experimental conditions. Results indicated that item valence had a bigger impact on IWE than semantic framing. PANDI-Good items in the Affirming Condition exhibited lower reliability but higher means and response variance than other groups, emphasizing the significant difference in how individuals interpret positive and negating inventory items. This study recommends using negatively worded items sparingly, and not using negating items at all.

Parameter instabilities and monetary policy in a small open economy: Evidence from an estimated model for the UK

This paper reconsiders whether monetary policy in small open economies responds to exchange rates by studying possible parameter instabilities in a Dynamic Stochastic General Equilibrium model. The main focus of the paper is to revisit preceding evidence on the response to exchange rate movements by the Bank of England and determine if its reaction function has remained constant throughout the sample. To this end, I estimate a small open economy general equilibrium model using Bayesian econometric techniques over rolling windows. I find overwhelming evidence of shifts in several parameters, including those related to the policy rule. Furthermore, posterior odds tests reveal a time-varying response to exchange-rate fluctuations by the monetary authorities. The results favor the model with the nominal exchange rate embedded in the policy rule for the initial subsamples. However, the evidence steadily evolves across windows and ultimately changes to prefer the model specification with no exchange rate. The paper also documents evident variations in the model dynamics derived from the instability of parameters via rolling-window impulse response functions and variance decomposition analysis.

Genomic predictors of fat mass response to the standardized exercise training.

To explore the genetic architecture underlying exercise-induced fat mass change, we performed a genome-wide association study with a Chinese cohort consisting of 442 physically inactive healthy adults in response to a 12-week exercise training (High-intensity Interval Training or Resistance Training). The inter-individual response showed an exercise-induced fat mass change and ten novel lead SNPs were associated with the response on the level of P<1×10-5. Four of them (rs7187742, rs1467243, rs28629770 and rs10848501) showed a consistent effect direction in the European ancestry. The Polygenic Predictor Score (PPS) derived from ten lead SNPs, sex, baseline body mass and exercise protocols explained 40.3% of the variance in fat mass response, meanwhile importantly the PPS had the greatest contribution. Of note, the subjects whose PPS was lower than -9.301 had the highest response in exercise-induced fat loss. Finally, we highlight a series of pathways and biological processes regarding the fat mass response to exercise, e.g. apelin signaling pathway, insulin secretion pathway and fat cell differentiation biological process.

The Interplay of Foreign Direct Investment in Unravelling the Nexus of Technological Innovation and Economic Dynamics: An Integrated Study Using Vector Error Correction Model

Most lower-middle income countries prioritise innovation, with foreign direct investment (FDI) as a key funding source for sustainable development. This article studies the interplay between FDI, technological innovation (measured by patent-granted residents), gross domestic product (GDP), research and development (R&amp;D) expenditure (RDE) and inflation of the Indian economy from 2002–2003 to 2022–2023. It uses a vector error correction model, Johansen cointegration tests, Granger causality tests, the impulse response function and variance decomposition. The study finds two cointegration relationships between the variables. GDP and RDE have a significant positive effect on technological innovation in the long term. Neither FDI nor inflation shows such an impact. FDI policies should therefore consider factors such as a conducive regulatory framework, tax breaks and grants for R&amp;D to enhance their impact on innovation. JEL Codes: O31, O32, F21, F23, E01, O47

Determinants of Household and Professional Forecasters’ Inflation Expectations in India

ABSTRACTThis study analyses and compares the determinants of inflation expectations among households and professional forecasters in India. To this end, we utilize quarterly survey data from the Reserve Bank of India (RBI), specifically the Inflation Expectations Survey of Households (IESH) and the Professional Forecasters’ Survey (SPF). The analysis employs a non‐recursive structural vector autoregressive (SVAR) model to explore the relationships between variables. The impulse response function and variance decomposition analysis shed light on the response of inflation expectations to macroeconomic shocks. Our findings indicate that apart from conventional macroeconomic factors like realized inflation and monetary policy, exogenous factors such as oil prices significantly shape inflation expectations. Comparing IESH and SPF, we found out that household expectations are more sensitive to shocks related to food prices, reflecting the influence of food expenses on household decision‐making. Conversely, professional forecasters’ expectations are more influenced by core inflation. Finally, we observed that inflation expectations adjust more quickly than realized inflation in response to macroeconomic shocks, suggesting a leading role. This study is novel with the contribution to the existing literature as it provides a comparative analysis of determinants of inflation expectations between households and professional forecasters in India, while also considering inflation targeting as a significant factor.

Bayesian inference in arm posture perception.

To configure our limbs in space, the brain must compute their position based on sensory information provided by mechanoreceptors in the skin, muscles, and joints. Because this information is corrupted by noise, the brain is thought to process it probabilistically and integrate it with prior belief about arm posture, following Bayes' rule. Here, we combined computational modeling with behavioral experimentation to test this hypothesis. The model conceives the perception of arm posture as the combination of a probabilistic kinematic chain composed by the shoulder, elbow, and wrist angles, compromised with additive Gaussian noise, with a Gaussian prior about these joint angles. We tested whether the model explains errors in a virtual reality (VR)-based posture matching task better than a model that assumes a uniform prior. Human participants (N = 20) were required to align their unseen right arm to a target posture, presented as a visual configuration of the arm in the horizontal plane. Results show idiosyncratic biases in how participants matched their unseen arm to the target posture. We used maximum likelihood estimation to fit the Bayesian model to these observations and estimate key parameters including the prior means and its variance-covariance structure. The Bayesian model including a Gaussian prior explained the response biases and variance much better than a model with a uniform prior. The prior varied across participants, consistent with the idiosyncrasies in arm posture perception and in alignment with previous behavioral research. Our work clarifies the biases in arm posture perception within a new perspective on the nature of proprioceptive computations.NEW & NOTEWORTHY We modeled the perception of arm posture as a Bayesian computation. A VR posture-matching task was used to empirically test this Bayesian model. The Bayesian model including a nonuniform postural prior well explained individual participants' biases in arm posture matching.

Patient-Specific Nanoparticle Targeting in Human Leukemia Blood.

Antibody-directed targeting of chemotherapeutic nanoparticles to primary human cancers holds promise for improving efficacy and reducing off-target toxicity. However, clinical responses to targeted nanomedicines are highly variable. Herein, we prepared and examined a matrix of 9 particles (organic and inorganic particles of three surface chemistries with and without antibody functionalization) and developed an ex vivo model to study the person-specific targeting of nanoparticles in whole blood of 15 patients with chronic lymphocytic leukemia (CLL). Generally, anti-CD20-functionalized poly(ethylene glycol) (PEG) nanoparticles efficiently targeted CLL cells, leading to low off-target phagocytosis by granulocytes and monocytes in the blood. However, there was up to 164-fold patient-to-patient variability in the CLL targeting. This was further exemplified through using clinically relevant PEGylated doxorubicin-encapsulated liposomes, which showed high interpersonal differences in CLL targeting (up to 234-fold differences) and off-target phagocytosis (up to 65- and 112-fold differences in granulocytes and monocytes, respectively). Off-target phagocytosis led to almost all monocytes being killed within 24 h of treatment. Variance of the off-target association of PEGylated liposomes with granulocytes and monocytes significantly correlated to anti-PEG immunoglobulin G levels in the blood of CLL patients. A negative correlation between CLL targeting of PEG particles and anti-PEG immunoglobulin M levels was found in the blood. Taken together, our study identifies anti-PEG antibodies as key proteins in modulating patient-specific targeting of PEGylated nanoparticles in human leukemia blood. Other factors, such as the antigen expression of targeted cells and fouling properties of nanoparticles, also play an important role in patient-specific targeting. The human leukemia blood assay we developed provides an ex vivo model to evaluate interpersonal variances in response to targeted nanomedicines.

7814 Non-fasting and Fasting Mixed Meal Tolerance Tests Equally Capture the Triglyceride Response in Participants With and Without MASLD

Abstract Disclosure: L.A. Gonzalez Ramirez: None. Z. He: None. J.N. Binongo: None. H.E. Huneault: None. A. Ramirez Tovar: None. J.A. Welsh: None. M.B. Vos: Consulting Fee; Self; Boehringer Ingelheim, Prosciento, Target Real World Solutions, Intercept Pharmaceuticals, INC, Novo Nordisk. Grant Recipient; Self; Target Real World Solutions. Mixed meal tolerance tests (MMTTs) are functional assessments that may identify metabolic dysregulation earlier than fasting tests during the progression to metabolic dysfunction-associated steatotic liver disease (MASLD). Although standards to conduct MMTTs in adults are readily available, the knowledge gap for children is quite large. Furthermore, conducting this type of study in children is challenging because they are less tolerant of long fasting intervals, long periods of testing, and early morning visits that interrupt school attendance. The objective of this study was to assess if conducting an MMTT in a non-fasting state will equally identify variance in the metabolic response of triglycerides (TG) between healthy children and those living with MASLD when compared to a 12-hour fasting MMTT. We collected blood samples every two hours in our 2-day randomized crossover feeding study. During each visit, 9 children with MASLD and 10 healthy controls aged 10 to 18 y underwent 1 standardized MMTT after a 12-hour overnight fasting (breakfast), followed by 2 standardized MMTTs in a non-fasting state (lunch and dinner). Participants were randomized to receive a glucose or fructose beverage at visit 1 and the other at visit 2. For uniformity, we only used data from the glucose beverage visit. We found that TG levels were statistically higher in the MASLD participants when compared to the non-MASLD group at each time point (p= 0.01). The maximum TG metabolic response peak for each MMTT was higher and more delayed in the MASLD group compared to the non-MASLD group. Within groups, postprandial TG level patterns were not significantly different when comparing breakfast, lunch, and dinner. Although TG levels varied throughout the day, the pattern after every meal was similar. These findings suggest that it is possible to identify differences in the TG metabolic response between children living with MASLD and healthy participants in the postprandial state. The results from our study also support the use of non-fasting MMTTs when examining TG metabolism in children, though further research to validate these findings is needed. Presentation: 6/1/2024

How does the pelvic floor respond to modulations in trunk pressure induced by a variety of voicing tasks? A cross-sectional, observational study.

The pelvic floor responds to changes in trunk pressure, elevating during low-pressure exhale and descending during high-pressure exhale. Voicing occurs during exhalation, spanning low-to-high trunk-pressure, yet it is unknown how voicing affects the pelvic floor. The aim of this study was to quantify pelvic floor response to voicing and identify if there are differences for women with stress urinary incontinence. We hypothesized that shouting would cause pelvic floor descent, with greater magnitude for incontinent women. Sixty women (38 incontinent, 22 continent) performed four voicing tasks (counting to "4" in speaking/shouting/low-pitch/high-pitch voice) while transperineal ultrasound measured changes in pelvic floor morphology. ANOVA compared variance of responses to voicing and t-tests compared groups. Bladder neck height shortened, levator plate length increased and levator plate angle decreased more during shouting compared to speaking; consistent with pelvic floor straining. There were no differences for high versus low pitch-voicing and small group differences based on continence status. Voicing causes pelvic floor muscles to strain, with greater strain during shouting. Changing vocal pitch does not affect pelvic floor morphology and incontinent women had slight differences from continent women. Voicing may be a safe way to lengthen the pelvic floor without provoking incontinence.

Impact of Digital Economy Development on Financialization of Firms: Empirical Evidence from PVAR Model

In this paper, we select several indicators to measure the level of the digital economy in cities, the index of digital inclusive finance in cities and the degree of financialization of enterprises, we apply variables mentioned above to analyze the complex relationship between multiple variables based on the PVAR model, we firstly suppose a unique order and use impulse response function(IRF) and variance decomposition measures to predict the impact of the relationship between variables, so as to provide a reference for policy making and risk prevention. and use impulse response and variance decomposition methods to predict the future direction of the relationship between variables, so as to provide certain reference significance for policy making and risk prevention.

Analysis of the Combined Impact of Socio-Economic Factors on House Price Volatility in the Housing Market

As an important variable in China’s economic system, real estate price is a key point closely linked to the country’s economy and people’s livelihood. It is of great practical significance to study the impact of socio-economic factors in the housing market on China’s house prices and its transmission mechanism, so as to put forward corresponding policy recommendations for stabilizing house prices and preventing real estate market and financial risks. Taking China’s time series data from 2014 to 2023 as a sample, this paper empirically investigates the law of the relationship between socio-economic factors in the housing market and house price fluctuations by constructing a structural vector autoregressive model, and employs impulse response function and variance decomposition to analyze the relationship between the two dynamically. The study shows that the 15-period variance decomposition effect of itself and residents’ disposable income are the main influencing factors of house price fluctuation, and the degree of explanation of its fluctuation is 55.5% and 23.2% respectively. In a market economy, real estate prices fluctuate up and down around their value due to the law of value. Therefore, real estate prices cannot rise indefinitely, and the final result should be stabilized within a reasonable level.

Virulence and Immune Evasion Strategies of FMDV: Implications for Vaccine Design.

Foot-and-mouth disease (FMD) is globally recognized as a highly economically devastating and prioritized viral disease affecting livestock. Vaccination remains a crucial preventive measure against FMD. The improvement of current vaccine platforms could help control outbreaks, leading to the potential eradication of the disease. In this review, we describe the variances in virulence and immune responses among FMD-susceptible host species, specifically bovines and pigs, highlighting the details of host-pathogen interactions and their impact on the severity of the disease. This knowledge serves as an important foundation for translating our insights into the rational design of vaccines and countermeasure strategies, including the use of interferon as a biotherapeutic agent. Ultimately, in this review, we aim to bridge the gap between our understanding of FMDV biology and the practical approaches to control and potentially eradicate FMD.

A novel sensitivity analysis method for multi-input-multi-output structures considering non-probabilistic correlations

In practical engineering, a multi-input-multi-output (MIMO) structure generally features a significant number of correlated input parameters and output responses. Sensitivity analysis is usually adopted to select key parameters for improving the computational efficiency of structural analysis and design processes. Traditional sensitivity analysis methods based on probabilistic models for MIMO structures may not reliably and efficiently derive the sensitivity indexes of correlated input parameters with limited samples. To solve the above problems, a novel sensitivity analysis method for MIMO structures considering non-probabilistic correlations is proposed to estimate the influence of uncertainties and correlations among the parameters on the responses in a unified framework. Firstly, a multidimensional parallelepiped (MP) model is employed to quantify the uncertainties and non-probabilistic correlations among the parameters. A new non-probabilistic variance propagation equation based on the MP model is then proposed to derive the non-probabilistic variances of output responses. The non-probabilistic independent, correlated, and total sensitivity indexes of each parameter for multi-input-single-output (MISO) structures are defined according to the non-probabilistic variance contribution rates. A dimensional normalization method and a vector projection method are then adopted to extend the non-probabilistic sensitivity indexes of each parameter for MIMO structures with correlations. Two numerical examples and an experimental example are exemplified to verify the proficiency and efficiency of the currently proposed method.

Machine learning reveals the transcriptional regulatory network and circadian dynamics of Synechococcus elongatus PCC 7942

Synechococcus elongatus is an important cyanobacterium that serves as a versatile and robust model for studying circadian biology and photosynthetic metabolism. Its transcriptional regulatory network (TRN) is of fundamental interest, as it orchestrates the cell's adaptation to the environment, including its response to sunlight. Despite the previous characterization of constituent parts of the S. elongatus TRN, a comprehensive layout of its topology remains to be established. Here, we decomposed a compendium of 300 high-quality RNA sequencing datasets of the model strain PCC 7942 using independent component analysis. We obtained 57 independently modulated gene sets, or iModulons, that explain 67% of the variance in the transcriptional response and 1) accurately reflect the activity of known transcriptional regulations, 2) capture functional components of photosynthesis, 3) provide hypotheses for regulon structures and functional annotations of poorly characterized genes, and 4) describe the transcriptional shifts under dynamic light conditions. This transcriptome-wide analysis of S. elongatus provides a quantitative reconstruction of the TRN and presents a knowledge base that can guide future investigations. Our systems-level analysis also provides a global TRN structure for S. elongatus PCC 7942.

Combining price and non-price interventions for water conservation

Abstract Marginal pricing has long been the instrument of choice to address water conservation challenges. More recently, non-price behavioral interventions have emerged as an alternative. However, there is limited data on the relative efficacies of price and non-price interventions. We report results from long-term field experiments studying unit-level water conservation responses to both price and non-price interventions in the same group of households (n = 64 186 household-days). Conservation habits, attitude-action gaps, principal-agent incongruities, and billing cycles help account for the heterogeneity in response between households, and across time. A non-price behavior modification intervention before the introduction of marginal pricing resulted in a large and significant effect on treated households (33%). The subsequent introduction of marginal volumetric pricing also reduced water use (8%, for previously untreated households). However, this average price effect masks how a large share (21%) of households increased water use, or how a mere 12% of the households accounted for all the aggregate reduction in water use. We investigated such heterogeneous responses as a systematic conservation maximization design question beyond statistical variance in individual responses. We used daily water consumption measurements across three years alongside a household survey to delineate structural and agentic barriers to conservation behavior. Our analysis reveals how combining price and non-price behavioral interventions could hold the key to achieving conservation effects that are both large and persistent.

311 Effect of feeding butyric acid on growth performance and metabolic indicators of dairy calves before weaning: A meta-analysis

Abstract This meta-analysis aimed to evaluate the effect of feeding butyric acid (BA) on growth performance and metabolic indicators in dairy calves. A literature search was conducted to identify in vivo research studies carried out on BA supplementation in dairy calves. Inclusion criteria were in vivo studies, dairy calves, weaning, BA, and inclusion doses of BA. Twenty-three papers with 80 data and 1,132 calves were selected. Data extracted included the number of calves in control and treatment groups and measures of variance of responses (standard error or standard deviation). The response variables were production performance including body weight (BW), average daily gain (ADG) feed efficiency (FE), and metabolic indicators including blood glucose and beta-hydroxybutyrate (BHB) concentrations. A random effect of model was used to examine the raw mean difference and standardized mean difference between BA supplementation and the control group. The analysis was conducted using the metafor package of Rstudio. Butyric acid moderately improved the growth performance and metabolic indicators responses of calves with substantial heterogeneity (59 &amp;lt; I2 &amp;lt; 73%, P &amp;lt; 0.01). Final BW and ADG were increased by 2.7 kg and 48.1 g/day, or &amp;gt; 0.6 and &amp;gt; 0.4 standard deviation units (P &amp;lt; 0.05), respectively. However, FE was increased by BA supplementation but not significantly different. For metabolic indicators, glucose concentration was greater with BA supplementation with &amp;gt; 0.4 standard deviation unit, (P &amp;lt; 0.05). However, BA supplementation did not affect the blood concentration of BHB (P &amp;gt; 0.05). In conclusion, the meta-analysis results demonstrated that BA constitutes an important energy source for dairy calves. Butyric acid is effective in promoting growth performance and intestinal health and, yet, increasing production profits.

The Democracy I Like: Perceptions of Democracy and Opposition to Democratic Backsliding

Abstract When democracy is under attack, the hope is often that citizens will punish undemocratic incumbents. However, recent studies show that not all citizens punish governments for their undemocratic actions. In this article, we argue that citizens' understanding of and satisfaction with democracy are sources of heterogeneous reactions. In a survey experiment conducted in Germany and Poland, we show that the importance that citizens attach to specific institutions under threat, as well as their understanding of democracy, can explain much of the variance in citizens' responses to undemocratic actions. Citizens are willing to defend what they consider important for democracy – regardless of whether this reflects theoretical conceptions of democracy. Moreover, in times of democratic backsliding, Polish ‘critical citizens’, those who are dissatisfied with the way democracy works in Poland, are more likely to punish governments for undemocratic actions. Our findings help us understand how to increase citizens' resilience against democratic backsliding.

The impacts of microplastics on zebrafish behavior depend on initial personality state

Microplastic pollution is associated with inflammation, gut dysbiosis and behavioral changes in fish. Fish have distinct personality traits but the role of personality in behavioral toxicology is rarely considered. We classified zebrafish on four behavioral axes: boldness, anxiety, sociability and exploration tendency then exposed them to low- or high- concentrations of two types of polyethylene microplastics (low- and high-density) for 28 days. Behaviors, antioxidant enzymes (catalase and superoxide dismutase), and gut microbiome were then measured. There were direct effects of microplastics on boldness, anxiety and sociability. However, fish retained their initial behavioral tendencies. Exposure to all microplastic treatments reduced average swimming speed and decreased the time spent motionless. Microplastic exposure did not affect antioxidant enzymes but did cause significant changes in the composition of the gut microbiome. This study demonstrates that environmentally realistic concentrations of microplastics can alter fish behavior, but much of the variance in response can be explained by personality.

Optimum designs for clinical trials in personalized medicine when response variance depends on treatment

ABSTRACT We study optimal designs for clinical trials when the value of the response and its variance depend on treatment and covariates are included in the response model. Such designs are generalizations of Neyman allocation, commonly used in personalized medicine when external factors may have differing effects on the response depending on subgroups of patients. We develop theoretical results for D-, A-, E- and D A -optimal designs and construct semidefinite programming (SDP) formulations that support their numerical computation. D-, A-, and E-optimal designs are appropriate for efficient estimation of distinct properties of the parameters of the response models. Our formulation allows finding optimal allocation schemes for a general number of treatments and of covariates. Finally, we study frequentist sequential clinical trial allocation within contexts where response parameters and their respective variances remain unknown. We illustrate, with a simulated example and with a redesigned clinical trial on the treatment of neuro-degenerative disease, that both theoretical and SDP results, derived under the assumption of known variances, converge asymptotically to allocations obtained through the sequential scheme. Procedures to use static and sequential allocation are proposed.

Analysis of the Factors Influencing House Prices Based on the Var Model

Var model is established to study the relationship between house price, inflation rate and GDP in this article. By using Granger causality test, cointegration test, impulse response function and variance decomposition to analyze, we conclude that the value of inflation rate and GDP can be predicted by the past data of house price, and GDP has a significant impact on house price.