Qualitative Inference Research Articles

Beyond mill: Why cross-case qualitative causal inference is weak, and why we should still compare

Beyond mill: Why cross-case qualitative causal inference is weak, and why we should still compare

Influence of phylogenetic relatedness on paleoclimate estimation using fossil wood: Vessel and fiber-related traits

Wood anatomical traits have been historically used as a climate inference tool. During the last 20years, the use of more formal statistical approaches has allowed the field to start moving from general qualitative paleoclimate inference to quantitative estimates. These estimates are derived from the correlation between wood anatomical traits and climate, however the role of shared evolutionary history in this relationship has not been assessed. Greater influence of phylogenetic relatedness on trait variation (phylogenetic conservatism) would entail a reduction of wood trait variation due to environmental convergence, the central premise of the paleoclimate inference approach using fossil wood. Here, we analyzed the role of phylogenetic relatedness in the relationship between wood anatomical traits and climate. We also assessed the strength of phylogenetic signal in wood traits and climate preferences, as well as their most likely mode of evolution. Although we found similar trends in the phylogenetically uninformed and informed regressions, the fit of the latter models was better for every trait. We also found moderate but significant non-random phylogenetic signal in all traits but potential hydraulic conductivity and vulnerability index. Our results suggest that despite adaptive evolution is driving the relationship between wood anatomy and climate, a significant role of phylogenetic signal indicates that paleoclimate estimates using fiber and vessel traits are subject to broader errors than initially anticipated.

The "FIFA 11+" injury prevention program improves body stability in child (10 year old) soccer players.

The suitability of the FIFA 11+ prevention programme to improve selected performance outcomes in children aged < 14 years has not been established yet. This study aimed to investigate the effects of the FIFA 11+ programme on jump ability and stability in 10-year-old child soccer players. Sixteen young soccer players (aged 10 years) were randomly assigned to a conventional or a FIFA 11+ warm-up group. During a 5-week training period with 2 sessions per week the FIFA 11+ group warmed up with the 11+ programme, whereas the control group subjects performed their usual warm-up programme (e.g. running exercises with dribbling and/or passing techniques included). After the warm-up, both groups performed the same training exercises during each session. Before and after the training period, standing long jump performance and body stability (S3 Check, unstable uniaxial platform) were assessed. Significant improvements in the stability index were found in both groups (5.6±1.1 to 3.5±1.0 and 5.5±0.8 to 4.0±1.5 for the FIFA 11+ and the control group, respectively, p<0.001, partial η²=0.886 for the training effect of the analysis of variance) with likely (qualitative inference analysis) greater improvements in the FIFA 11+ group compared to the control group (p=0.078, partial η²=0.205 for the training x group interaction effect of the analysis of variance). Training had no effect on standing long jump performance (p>0.05). Data indicate that in 10-year-old soccer players the FIFA 11+ programme may have the potential to improve stability. Thus, the FIFA 11+ programme might contribute to injury prevention and possibly to better soccer performance as well. This might especially apply if the programme is performed over a longer period and/or with more weekly training sessions. Based on the present results the inclusion of such a programme within the training practice of the child soccer player can be recommended.

Dose-response effect of photobiomodulation therapy on neuromuscular economy during submaximal running.

The purpose of this study was to verify the photobiomodulation therapy (PBMT) effects with different doses on neuromuscular economy during submaximal running tests. Eighteen male recreational runners participate in a randomized, double-blind, and placebo-controlled trial, which each participant was submitted to the same testing protocol in five conditions: control, placebo, and PBMT with doses of 15, 30, and 60J per site (14 sites in each lower limb). The submaximal running was performed at 8 and 9kmh-1 during 5min for each velocity. Muscle activation of the vastus lateralis (VL), vastus medialis (VM), rectus femoris (RF), biceps femoris (BF), and gastrocnemius lateralis (GL) was collected during the last minute of each running test. The root mean square (RMS) was normalized by maximal isometric voluntary contraction (MIVC) performed a priori in an isokinetic dynamometer. The RMS sum of all muscles (RMSLEG) was considered as main neuromuscular economy parameter. PBMT with doses of 15, 30, and 60J per site [33 diodes = 5 lasers (850nm), 12 LEDs (670nm), 8 LEDs (880nm), and 8 LEDs (950nm)] or placebo applications occurred before running tests. For the statistical analysis, the effect size was calculated. Moreover, a qualitative inference was used to determine the magnitude of differences between groups. Peak torque and RMS during MIVCs showed small effect sizes. According to magnitude-based inference, PBMT with dose of 15J per site showed possibly and likely beneficial effects on neuromuscular economy during running at 8 and 9kmh-1, respectively. On other hand, PBMT with doses of 30 and 60J per site showed possible beneficial effects only during running at 9kmh-1. We concluded that PBMT improve neuromuscular economy and the best PBMT dose was 15J per site (total dose of 420J).

A qualitative inference method for prediction of geographic process using spatial and temporal relations

A qualitative inference method for prediction of geographic process using spatial and temporal relations

A qualitative inference method for prediction of geographic process using spatial and temporal relations

Knowledge engineering is the systematic self-disciplined set of activities involved in design and development of knowledge-based systems. Abstraction of the real world into codified information is the objective of knowledge representation (KR). The survey of various works of researchers in the domain of spatio-temporal knowledge representation for reasoning real world actions in geographic applications is presented. Geographic event attributed spatial entity (GEASE) knowledge-base that will aid in reasoning events causing the spatial change in geographic features over the period of time is proposed. GEASE knowledge-base describing a spatial entity by considering the temporal event as an attribute is constructed to infer events that cause geographical changes. As a result, the significance of the proposed knowledgebase is illustrated by evaluating event based queries on synthetic dataset. Finally, we conclude the work with direction to enhance the logical formulation for its implementation on real datasets in future.

Effects of Four Weeks of β-Alanine Supplementation on Repeated Sprint Ability in Water Polo Players.

The purpose of this study was to investigate the effect of four weeks of β-alanine supplementation on repeated sprint ability in water polo players. Twenty-two male water polo players participated in the study, divided randomly into two homogeneous groups (placebo and β-alanine groups). The study design was double-blind, parallel and placebo controlled. Before and after the supplementation period (28 days), the athletes performed two specific repeated sprint ability tests interspaced by a 30-minute swimming test. Participants received 4.8g∙day-1 of the supplement (dextrose or β-alanine) on the first 10 days and 6.4g∙day-1 on the final 18 days. There was no significant group-time interaction for any variable. The qualitative inference for substantial changes demonstrated a likely beneficial effect in the β-alanine group (β-alanine vs placebo) for mean time (6.6±0.4s vs 6.7±0.4s; 81% likely beneficial), worst time (6.9±0.5s vs 7.1±0.5s; 78% likely beneficial) and total time (39.3±2.5s vs 40.4±2.5s; 81% likely beneficial) in the first repeated sprint ability set and for worst time (7.2±0.6s vs 7.5±0.6s; 57% possible beneficial) in the second repeated sprint ability set. Further, was found substantial change for total time for both repeated sprint ability tests (80.8±5.7s vs 83.4±5.6s; 52% possible beneficial). To conclude, four weeks of β-alanine supplementation had a likely beneficial effect in the first set of repeated sprint ability tests and a possible beneficial effect for worst time in the second set performed in a specific protocol in water polo players.

The shellfish enigma across the Mesolithic-Neolithic transition in southern Scandinavia

The well-known and widespread replacement of oysters (abundant during the Mesolithic period) by cockles and mussels in many Danish Stone Age shell middens ca. 5900 cal yrs BP coincides with the transition to agriculture in southern Scandinavia. This human resource shift is commonly believed to reflect changing resource availability, driven by environmental and/or climatic change at the Mesolithic-Neolithic transition rather than cultural choice. While several hypotheses have been proposed to explain the “Mesolithic-Neolithic oyster decline”, an explanation based on a sudden freshening of the inner Danish waters has received most attention. Here, for the first time, we test and refute this long-standing hypothesis that declining salinity explains the marked reduction in oysters identified within numerous shell middens across coastal Denmark at the Mesolithic-Neolithic transition using quantitative and qualitative salinity inference from several, independent proxies (diatoms, molluscs and foraminifera) from multiple Danish fjord sites. Alternatively, we attribute the oyster decline to other environmental causes (particularly changing sedimentation), ultimately driven by external climatic forcing. Critical application of such high-quality environmental archives can reinvigorate archaeological debates and can aid in understanding and managing environmental change in increasingly impacted coastal regions.

CHO Mouth Rinse Ameliorates Neuromuscular Response with Lower Endogenous CHO Stores.

This study aimed to investigate carbohydrate (CHO) mouth rinse response on neuromuscular activity, fuel oxidation rates, and cycling performance with different initial levels of endogenous CHO availability. In a double-blind, randomized placebo-controlled design, eight males completed six experimental mouth rinse trials: CHO (6.4% maltodextrin) or placebo solution in a fed state (FED), 12-h fasted state (FAST), or a combined exercise-depleted muscle glycogen and 12-h fasted state (DEP). Trials consisted of 30-min cycling at 90% of gas exchange threshold, followed by a 20-km cycling time trial. Plasma lactate, plasma glucose, oxygen uptake, and EMG activity were measured, and CHO and fat oxidation rates were calculated. CHO mouth rinse maintained higher plasma glucose levels as the constant load exercise progressed (P = 0.023). The reduced EMG activity in the DEP condition with the placebo during constant load exercise was ameliorated with CHO mouth rinse (P < 0.01). Furthermore, the power output and the EMG activity throughout the 20-km time trial were reduced in the DEP condition with placebo but were both restored with CHO mouth rinse (P < 0.05). Time trial performance was only improved with CHO in the DEP compared with the corresponding placebo (P < 0.05), and no differences between supplements were observed in the FED or FAST states. Analyses of the qualitative inference showed "benefit very likely" of CHO mouth rinse on exercise performance in DEP, "possibly benefit" in FAST, and "negligible or trivial" in FED. CHO mouth rinse had no effect on CHO and fat oxidation rates in either exercise mode. The CHO mouth rinse influences exercise performance when endogenous CHO availability is low, and an enhanced central motor drive is potentially the main influencing mechanism.

Caffeine Improved Time to Exhaustion But Did Not Change Alternative Maximal Accumulated Oxygen Deficit Estimated During a Single Supramaximal Running Bout.

The aim of the current study was to investigate the effects of acute caffeine supplementation on anaerobic capacity determined by the alternative maximal accumulated oxygen deficit (MAODALT) in running effort. Eighteen recreational male runners [29 ± 7years; total body mass 72.1 ± 5.8 kg; height 176.0 ± 5.4cm; maximal oxygen uptake (VO2max) 55.8 ± 4.2 ml·kg-1 ·min-1] underwent a graded exercise test. Caffeine (6 mg·kg-1) or a placebo were administered 1 hr before the supramaximal effort at 115% of the intensity associated with VO2max in a double-blind, randomized cross-over study, for MAODALT assessment. The time to exhaustion under caffeine condition (130.2 ± 24.5s) was 11.3% higher (p = .01) than placebo condition (118.8 ± 24.9 s) and the qualitative inference for substantial changes showed a very likely positive effect (93%). The net participation of the oxidative phosphorylation pathway was significantly higher in the caffeine condition (p = .02) and showed a likely positive effect (90%) of 15.3% with caffeine supplementation. The time constant of abrupt decay of excess postexercise oxygen consumption (τ1) was significantly different between caffeine and placebo conditions (p = .03) and showed a likely negative effect (90%), decreasing -8.0% with caffeine supplementation. The oxygen equivalents estimated from the glycolytic and phosphagen metabolic pathways showed a possibly positive effect (68%) and possibly negative effect (78%) in the qualitative inference with caffeine ingestion, respectively. However, the MAODALT did not differ under the caffeine or placebo conditions (p = .68). Therefore, we can conclude that acute caffeine ingestion does not modify the MAODALT, reinforcing the robustness of this method. However, caffeine ingestion can alter the glycolytic and phosphagen metabolic pathway contributions to MAODALT.

Cervicovaginal and Rectal Fluid as a Surrogate Marker of Antiretroviral Tissue Concentration: Implications for Clinical Trial Design.

Quantifying tissue drug concentrations can yield important information during drug development, but complicates pharmacokinetic study design. Mucosal fluids collected by direct aspiration (cervicovaginal fluid; CVF) or swab (rectal fluid; RF) might be used as tissue concentration surrogates, but these relationships are not well characterized. Forty-nine healthy women, given a single oral dose of tenofovir, maraviroc, emtricitabine, or raltegravir at 50%-200% of the treatment dose, provided 13 plasma, 12 CVF, 12 RF and one cervical, vaginal and rectal tissue biopsy over 48 hours. Relationships between these paired samples were characterized by linear and multiple linear regression. Adjusted r values were used to select the final predictive models. CVF exposure increased linearly with dose for all antiretrovirals (r(2) ≥ 0.23, P ≤ 0.02) except raltegravir (r(2) = 0.08, P = 0.19). In RF, only emtricitabine increased linearly with dose (r(2) = 0.27, P = 0.01). For all antiretrovirals, CVF and RF concentrations significantly correlated with mucosal tissue concentrations (female genital tract r(2) ≥ 0.37, rectal tissue (2)r ≥ 0.50, P ≤ 0.001). In the final multivariate models, plasma and fluid concentrations were both associated with FGT concentrations for all antiretrovirals (r(2) ≥ 0.81, P < 0.001). The same was noted for rectal tissue (r(2) ≥ 0.58, P < 0.001) except for tenofovir, for which RF alone was predictive of tissue concentration (r(2) = 0.91, P < 0.001). Mucosal fluids were positively correlated with tissue concentrations and including plasma concentrations improved the regression models in most cases. Dose linearity in CVF, but not RF, suggests a saturation process in lower gastrointestinal tract tissue. These findings suggest that mucosal fluid and plasma concentrations may be used for qualitative inference of tissue concentrations for these antiretrovirals.

Qualitative probabilistic inference under varied entropy levels

In previous work, we studied four well known systems of qualitative probabilistic inference, and presented data from computer simulations in an attempt to illustrate the performance of the systems. These simulations evaluated the four systems in terms of their tendency to license inference to accurate and informative conclusions, given incomplete information about a randomly selected probability distribution. In our earlier work, the procedure used in generating the unknown probability distribution (representing the true stochastic state of the world) tended to yield probability distributions with moderately high entropy levels. In the present article, we present data charting the performance of the four systems when reasoning in environments of various entropy levels. The results illustrate variations in the performance of the respective reasoning systems that derive from the entropy of the environment, and allow for a more inclusive assessment of the reliability and robustness of the four systems.

Automatic HAZOP analysis method for unsteady operation in chemical based on qualitative simulation and inference

Comparing with continuous production process, unsteady operation process, such as startup and shutdown, tends to abnormal situations due to a large number of operations of operators and dynamic state changes involved. To guarantee a safe operation, process hazard analysis (PHA) is very important to proactively identify the potential safety problems. In the chemical process industry, hazard and operability (HAZOP) analysis is the most widely used method. In this paper, based on proposed qualitative simulation and inference method, an automatic HAZOP analysis method for unsteady operation processes is proposed. Mass transfer and relationships among process variables are expressed by Petri net–directed graph model based fuzzy logic. Operating procedure is expressed according to a formal expression. Possible operation deviations from normal operating procedure are identified by using a group of guidewords. Hazards are identified automatically by qualitative simulation and inference when wrong operation process is performed. The method is validated by a rectification column system.

Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks.

Microarray technologies have been the basis of numerous important findings regarding gene expression in the few last decades. Studies have generated large amounts of data describing various processes, which, due to the existence of public databases, are widely available for further analysis. Given their lower cost and higher maturity compared to newer sequencing technologies, these data continue to be produced, even though data quality has been the subject of some debate. However, given the large volume of data generated, integration can help overcome some issues related, e.g., to noise or reduced time resolution, while providing additional insight on features not directly addressed by sequencing methods. Here, we present an integration test case based on public Drosophila melanogaster datasets (gene expression, binding site affinities, known interactions). Using an evolutionary computation framework, we show how integration can enhance the ability to recover transcriptional gene regulatory networks from these data, as well as indicating which data types are more important for quantitative and qualitative network inference. Our results show a clear improvement in performance when multiple datasets are integrated, indicating that microarray data will remain a valuable and viable resource for some time to come.

Sodium bicarbonate supplementation improved MAOD but is not correlated with 200- and 400-m running performances: a double-blind, crossover, and placebo-controlled study.

The aim of the study was to investigate the effects of acute supplementation of sodium bicarbonate (NaHCO3) on maximal accumulated oxygen deficit (MAOD) determined by a single supramaximal effort (MAODALT) in running and the correlation with 200- and 400-m running performances. Fifteen healthy men (age, 23 ± 4 years; maximal oxygen uptake, 50.6 ± 6.1 mL·kg(-1)·min(-1)) underwent a maximal incremental exercise test and 2 supramaximal efforts at 110% of the intensity associated with maximal oxygen uptake, which was carried out after ingesting either 0.3 g·kg(-1) body weight NaHCO3 or a placebo (dextrose) and completing 200- and 400-m performance tests. The study design was double-blind, crossover, and placebo-controlled. Significant differences were found between the NaHCO3 and placebo conditions for MAODALT (p = 0.01) and the qualitative inference for substantial changes showed a very likely positive effect (98%). The lactic anaerobic contribution in the NaHCO3 ingestion condition was significantly higher (p < 0.01) and showed a very likely positive effect (99% chance), similar to that verified for peak blood lactate concentration (p < 0.01). No difference was found for time until exhaustion (p = 0.19) or alactic anaerobic contribution (p = 0.81). No significant correlations were observed between MAODALT and 200- and 400-m running performance tests. Therefore, we can conclude that both MAODALT and the anaerobic lactic metabolism are modified after acute NaHCO3 ingestion, but it is not correlated with running performance.

Process Tracing and Qualitative Causal Inference

This essay critically reviews this symposium's essays on process tracing and security studies by James Mahoney, Andrew Bennett, and Nina Tannenwald. It covers three major issues that have not been adequately addressed by previous writings on process tracing: the relationship of single case studies to more general causal claims, the conceptualization of causation, and the criteria of valid causal inference. It introduces the “completeness standard,” which combines causal graphs, event history maps, and invariant causal mechanisms. The completeness standard, it argues, bridges unit-level causal inferences and average treatment effects, invokes an epistemologically warranted conceptualization of causation, and better satisfies existing standards of causal inference by making unit homogeneity assumptions more credible.

Odds ratio vs risk ratio in randomized controlled trials

Objective. Use of odds ratio (OR) in randomized controlled trials (RCTs) has been criticized because it overestimates the effect size, if incorrectly interpreted as risk ratio (RR). To what extent does this make a difference in the context of clinical research is unclear. We, therefore, aimed to address this issue considering its importance in evidence-based practice of medicine. Methods. We reviewed 580 RCTs published in the New England Journal of Medicine between January 2004 and June 2014 and identified 107 RCTs that reported unadjusted RR (n = 76) or OR (n = 31) for the primary outcome. For studies reporting ORs, we calculated RRs, and vice versa, using Stata software. The percentage of divergence between the reported and calculated effect size estimates was analyzed. Results. None of the RCTs showed a statistically significant result becoming insignificant or vice versa depending on the effect size estimate. OR exaggerated the RR in 62% of the RCTs. The percentage of overestimation was > 50% in 28 RCTs and > 100% in 13 RCTs. The degree of overestimation was positively correlated with the prevalence of outcomes (spearman’s rho = 0.84 and 0.66, p < 0.001). Conclusion. Use of OR instead of RR in RCTs does not change the qualitative inference of results. However, the use of OR can markedly exaggerate the effect size in RCTs if misinterpreted as RR and, hence, has the potential to mislead clinicians.

Minimum distance estimation of the errors-in-variables model using linear cumulant equations

We consider a multiple mismeasured regressor errors-in-variables model. We develop closed-form minimum distance estimators from any number of estimating equations, which are linear in the third and higher cumulants of the observable variables. Using the cumulant estimators alters qualitative inference relative to ordinary least squares in two applications related to investment and leverage regressions. The estimators perform well in Monte Carlos calibrated to resemble the data from our applications. Although the cumulant estimators are asymptotically equivalent to the moment estimators from Erickson and Whited (2002), the finite-sample performance of the cumulant estimators exceeds that of the moment estimators.

Mixed Methods and the Logic of Qualitative Inference

Can quantitative evidence be valuable for qualitative research designs? Here, I first examine recent arguments by qualitative methodologists who challenge the conventional view that quantitative evidence is necessary for explanatory generalization, but note that many qualitative researchers frequently incorporate quantitative evidence in their studies, despite methodological arguments to the contrary. I then extend recent developments in mixed methods research to argue that quantitative evidence offers preliminary description of sociological patterns to be explained by qualitative investigation.

An Agent-mediated Ontology-based Approach for Composite Activity Recognition in Smart Homes

Activity recognition enables ambient assisted living applications to provide activity- aware services to users in smart homes. Despite significant progress being made in activity recognition research, the focus has been on simple activity recognition leaving composite activity recognition an open problem. For instance, knowledge-driven activity recognition has recently attracted increasing attention but mainly focused on simple activities. This paper extends previous work by introducing a knowledge-driven approach to recognition of composite activities such as interleaved and concurrent activities. The approach combines the recognition of single and composite activities into a unified framework. To support composite activity modelling, it combines ontological and temporal knowledge modelling formalisms. In addition, it exploits ontological reasoning for simple activity recognition and qualitative temporal inference to support composite activity recognition. The approach is organized as a multi-agent system to enable multiple activities to be simultaneously monitored and tracked. The presented approach has been implemented in a prototype system and evaluated in a number of experiments. The experimental results have shown that average recognition accuracy for composite activities is 88.26%.