Response Time Threshold Research Articles

Anomaly Detection Using Machine Learning in Hydrochemical Data From Hot Springs: Implications for Earthquake Prediction

AbstractThis study explores the potential of machine learning algorithms for earthquake prediction, utilizing fluid chemical anomaly data from hot springs. Six hot springs, located within an active fault zone along the southeastern coast of China, were carefully chosen as hydrochemical monitoring sites for an extended period of two and a half years. Using this data, a prediction model integrating six algorithms was developed to forecast M ≥ 5 earthquakes in Taiwan. The model's performance was validated against recorded earthquake events, and the factors influencing its predictive capability were analyzed. Our comprehensive analysis conclusively demonstrates the superiority of machine learning algorithms over traditional statistical methods for earthquake prediction. Additionally, including sampling time in the data sets significantly improves the model's predictive performance. However, it is important to note that the model's predictive performance varies across different hot spring and indicators type, highlighting the importance of identifying optimal indicators for specific scenarios. The model parameters, including the anomaly detection rate (P) and earthquake response time threshold (M), significantly impact the model's predictive capabilities. Therefore, adjustments are needed to optimize the model's performance for practical use. Despite limitations such as the inability to differentiate pre‐earthquake anomalies from post‐earthquake anomalies and pinpoint the precise location of earthquakes, this study successfully showcases the potential of machine learning algorithms in earthquake prediction, paving the way for further research and improved prediction methods.

Identification of the Ideal Reference Site and Pain Threshold Values for the Placement of Electric Pulp Testers in Permanent Upper and Lower Anterior Teeth: A Cross-Sectional Study.

Electric pulp testers (EPTs) are widely used diagnostic tools for diagnosing traumatized teeth. Several factors can affect the result of an electric pulp test. One such factor that will affect the diagnosis is the electrode tip placement. Hence, the current study aims to identify the most painful site and response time threshold in healthy anterior teeth. A total of 90 individuals, 48 male and 42 female, aged 19 to 25 years,were recruited. An EPT was placed on three different sites: the cervical, middle, and incisal third of the labial surface of both upper and lower anterior teeth (central incisor, lateral incisor, and canine) with an appropriate electrolyte as a conducting medium. Later, the threshold values were recorded, and pain assessment was done using the Memojis pain scale (MPS). Finally, the data was analyzed statistically using the Mann-Whitney U test. Mean and standard deviation values of reaction time were collected from 540 EPT readings (three sites from 180 teeth).Among the three sites tested, the difference between the upper and lower central incisors was statistically insignificant (p > 0.05). Similarly, when upper and lower lateral incisors and canines were compared, a statistically significant difference was observed among the three sites (p<0.05). There was a significant difference (p<0.05) in the pain scores only on the incisal and cervical thirds of the upper and lower central incisors. Only the incisal third showed a statistically significant difference (p<0.05) between the pain scores in the upper and lateral incisors. At the same time, a statistically significant difference in the pain scores was observed among the three tested sites between the upper and lower canines (p<0.05). Conclusion: Lower threshold values were appreciated at the incisal third of all the upper and lower anterior teeth for placing the EPT. Most individuals have experienced a score of 2 (hurts little bit) for the perceived pain using EPTs for both the upper and lower anterior teeth.

Locating helicopter ambulance bases in Iceland: efficient and fair solutions.

Fixed-wing air ambulances play an important role in healthcare in rural Iceland. More frequent use of helicopter ambulances has been suggested to shorten response times and increase equity in access to advanced emergency care. In finding optimal base locations, the objective is often efficiency-maximizing the number of individuals who can be reached within a given time. This approach benefits people in densely populated areas more than people living in remote areas and the solution is not necessarily fair. This study aimed to find efficient and fair helicopter ambulance base locations in Iceland. We used high-resolution population and incident location data to estimate the service demand for helicopter ambulances, with possible base locations limited to twenty-one airports and landing strips around the country. Base locations were estimated using both the maximal covering location problem (MCLP) optimization model, which aimed for maximal coverage of demand, and the fringe sensitive location problem (FSLP) model, which also considered uncovered demand (i.e., beyond the response time threshold). We explored the percentage of the population and incidents covered by one to three helicopter bases within 45-, 60-, and 75-min response time thresholds, conditioned or not, on the single existing base located at Reykjavík Airport. This resulted in a total of eighteen combinations of conditions for each model. The models were implemented in R and solved using Gurobi. Model solutions for base locations differed between the demand datasets for two out of eighteen combinations, both with the lowest service standard. Base locations differed between the MCLP and FSLP models for one combination involving a single base, and for two combinations involving two bases. Three bases covered all or almost all demand with longer response time thresholds, and the models differed in four of six combinations. The two helicopter ambulance bases can possibly obtain 97% coverage within 60 min, with bases in Húsafell and Grímsstaðir. Bases at Reykjavík Airport and Akureyri would cover 94.2%, whereas bases at Reykjavík Airport and Egilsstaðir would cover 88.5% of demand. An efficient and fair solution would be to locate bases at Reykjavík Airport and in Akureyri or Egilsstaðir.

Practical investigation and evaluation of the Start/Stop system's impact on the engine's fuel use, noise output, and pollutant emissions

Prior to the emergence of alternative energy sources, research on the start-stop system, which shuts down the engine at idle, was rapidly conducted by car manufacturers, in parallel with the growing need for energy-efficient technologies and the tightening of environmental regulations for vehicles. In addition, in order to increase sales as well as convenience and fuel efficiency, car manufacturers are attempting to commercialize start-stop technology by merging it with the generic smart key system. This paper shows a new practical study to evaluate a start/stop system designed specifically for the job. We have built and implemented a complete electronic start-stop mechanism for an aftermarket smart key system that uses an ECU starter and OBD-II interface. In addition to meeting all specified response time thresholds for vehicle status requests, the implemented Start Stop system standardizes the interface with vehicles to reduce the time required to install the Start Stop system on various vehicles. The results of this study highlight the importance of the resting system in terms of reducing fuel consumption, limiting greenhouse gas emissions, and keeping the vehicle engine quiet.

A Probabilistic Filtering Approach to Non‐Effortful Responding

AbstractCommon response‐time‐based approaches for non‐effortful response behavior (NRB) in educational achievement tests filter responses that are associated with response times below some threshold. These approaches are, however, limited in that they require a binary decision on whether a response is classified as stemming from NRB; thus ignoring potential classification uncertainty in resulting parameter estimates. We developed a response‐time‐based probabilistic filtering procedure that overcomes this limitation. The procedure is rooted in the principles of multiple imputation. Instead of creating multiple plausible replacements of missing data, however, multiple data sets are created that represent plausible filtered response data. We propose two different approaches to filtering models, originating in different research traditions and conceptualizations of response‐time‐based identification of NRB. The first approach uses Gaussian mixture modeling to identify a response time subcomponent stemming from NRB. Plausible filtered data sets are created based on examinees' posterior probabilities of belonging to the NRB subcomponent. The second approach defines a plausible range of response time thresholds and creates plausible filtered data sets by drawing multiple response time thresholds from the defined range. We illustrate the workings of the proposed procedure as well as differences between the proposed filtering models based on both simulated data and empirical data from PISA 2018.

A Comparison of Response Time Threshold Scoring Procedures in Mitigating Bias From Rapid Guessing Behavior.

Rapid guessing (RG) is a form of non-effortful responding that is characterized by short response latencies. This construct-irrelevant behavior has been shown in previous research to bias inferences concerning measurement properties and scores. To mitigate these deleterious effects, a number of response time threshold scoring procedures have been proposed, which recode RG responses (e.g., treat them as incorrect or missing, or impute probable values) and then estimate parameters for the recoded dataset using a unidimensional or multidimensional IRT model. To date, there have been limited attempts to compare these methods under the possibility that RG may be misclassified in practice. To address this shortcoming, the present simulation study compared item and ability parameter recovery for four scoring procedures by manipulating sample size, the linear relationship between RG propensity and ability, the percentage of RG responses, and the type and rate of RG misclassifications. Results demonstrated two general trends. First, across all conditions, treating RG responses as incorrect produced the largest degree of combined systematic and random error (larger than ignoring RG). Second, the remaining scoring approaches generally provided equal accuracy in parameter recovery when RG was perfectly identified; however, the multidimensional IRT approach was susceptible to increased error as misclassification rates grew. Overall, the findings suggest that recoding RG as missing and employing a unidimensional IRT model is a promising approach.

Rapid Guessing in Low-Stakes Assessments: Finding the Optimal Response Time Threshold with Random Search and Genetic Algorithm

Rapid guessing is an aberrant response behavior that commonly occurs in low-stakes assessments with little to no formal consequences for students. Recently, the availability of response time (RT) information in computer-based assessments has motivated researchers to develop various methods to detect rapidly guessed responses systematically. These methods often require researchers to identify an RT threshold subjectively for each item that could distinguish rapid guessing behavior from solution behavior. In this study, we propose a data-driven approach based on random search and genetic algorithm to search for the optimal RT threshold within a predefined search space. We used response data from a low-stakes math assessment administered to over 5000 students in 658 schools across the United States. As we demonstrated how to use our data-driven approach, we also compared its performance with those of the existing threshold-setting methods. The results show that the proposed method could produce viable RT thresholds for detecting rapid guessing in low-stakes assessments. Moreover, compared with the other threshold-setting methods, the proposed method yielded more liberal RT thresholds, flagging a larger number of responses. Implications for practice and directions for future research were discussed.

Disengaged response behavior when the response button is blocked: Evaluation of a micro-intervention.

In large-scale assessments, disengaged participants might rapidly guess on items or skip items, which can affect the score interpretation's validity. This study analyzes data from a linear computer-based assessment to evaluate a micro-intervention that blocked the possibility to respond for 2 s. The blocked response was implemented to prevent participants from accidental navigation and as a naive attempt to prevent rapid guesses and rapid omissions. The response process was analyzed by interpreting log event sequences within a finite-state machine approach. Responses were assigned to different response classes based on the event sequence. Additionally, post hoc methods for detecting rapid responses based on response time thresholds were applied to validate the classification. Rapid guesses and rapid omissions could be distinguished from accidental clicks by the log events following the micro-intervention. Results showed that the blocked response interfered with rapid responses but hardly led to behavioral changes. However, the blocked response could improve the post hoc detection of rapid responding by identifying responses that narrowly exceed time-bound thresholds. In an assessment context, it is desirable to prevent participants from accidentally skipping items, which in itself may lead to an increasing popularity of initially blocking responses. If, however, data from those assessments is analyzed for rapid responses, additional log data information should be considered.

Resource Management for Intelligent Vehicular Edge Computing Networks

To overcome the inherent defect of centralized data processing in cloud computing, the mobile edge computing (MEC) brings data storage and computing capacities, to the edge closer to end users. However, the uneven distribution of access vehicles, as well the volume of computing data, cause the workload diversity among various mobile edge computing servers (MECSs). In this paper, we propose a hierarchical model with quality of service (QoS)-aware and power-aware resource management for the cooperative edge-computing-based intelligent vehicular network (CEC-IoV), and the system latency and energy efficiency at MECSs are respectively optimized. Specifically, considering the changing response times versus MECSs’ workloads, the Minimum Latency with Migration Loads (MLML) scheme is developed for workload balance among multiple MECSs. By selecting the appropriate response time threshold and migration loads from overloading MECSs to idle MECSs simultaneously, the load-balancing problem can be efficiently solved for multiple MECSs with unbalanced workloads. On the other hand, through performing workload redistribution and dynamic reconfiguration of virtual machines (VMs) instantiated onto the parallel computing platform at one MECS, the energy-efficiency can be also optimized while guaranteeing the QoS requirement on the processing delay. With the latency constraint, the power minimization problem is formulated to be a convex one, and the semi-closed forms for optimal solutions of VMs’ workloads and processing rates are provided using KKT conditions. Compared with the performance obtained by benchmark schemes, numerical results exhibit that our resource management schemes gain lower system latency and higher energy efficiency.

Fast valley landscape response to climate change in the Lower Jinsha River, Southeastern Tibetan Plateau: Field investigations and numerical modeling

The Jinsha River, the upper reaches of the Yangtze River, winds and incises through the eastern margin of the Tibetan Plateau, where Asian monsoon climate prevails. Along the Jinsha River, extensive and thick Quaternary valley fillings and multiple river terraces have been developed. However, their specific relations to climate change and tectonics remain elusive. In this study, we conducted field investigation, chronological studies and numerical modeling in its lower reaches. Our study indicates that the extensive valley fillings in the Wudongde-Menggu segment were formed in cold-arid climate with Optically Stimulated Luminescence (OSL) ages of ~23–19 ka B.P., coinciding with the timing of the Last Glacial Maximum (LGM). We suggest that the post-LGM warming and humidifying, by restrained sediment supply while enhanced discharge, switched the valley from prevailing aggradation into incision. Multiple subsequent fill-cut terraces, postdating the LGM, were formed and nested in the valley fillings. OSL data indicate that sediments of three terraces (T1–T3) were formed at ~10 ka B.P., ~11.5–12.5 ka B.P. and ~13.5 ka B.P., respectively. Our study suggests that these terraces are sensitive records of millennial and sub-millennial cold-arid climate perturbations superimposed over the post-LGM deglaciation. Our modeling highlights a high sensitivity of valley aggradation and incision to cold-arid and warm-wet climate change, as well as a fast valley landscape response in the Jinsha River characterized by high sediment transport influx. We propose that valley landscape and terraces serve as a timely record for climate change in certain rivers with short response time threshold characterized by high sediment transport influx.

Mixture Model Method: A new method to handle aberrant responses in psychological and educational testing

<p id="p00005">Aberrant responses have been repeatedly reported in psychological and educational measurement. If traditional measurement models or methods (e.g., item response theory, IRT) are applied to data sets contaminated by aberrant responses, parameter estimates may be biased. Therefore, it is necessary to identify aberrant responses and to reduce their detrimental effects. <p id="p00005">In the literature, there are two traditional response time (RT)-based methods to detect aberrant responses: RT threshold method and RT residual method. The focus of these methods is to find a threshold of RT or RT residual. If a RT or RT residual is remarkably less than the threshold, this response should be regarded as an aberrant response with extremely short RT (e.g., speededness, rapid-guessing), and consequently does not provide information about the test taker’s latent trait. Afterwards, down-weighting strategy, which tries to limit the influence of aberrant responses on parameter estimation by reducing their weight in the sample, can be applied. <p id="p00005">The mixture model method (MMM), is a new method proposed to handle data contaminated by aberrant responses. This method applies the accommodating strategy, which is to extend a model in order to account for the contaminations directly. MMM shows more advantages in terms of: (1) detecting aberrant responses and obtaining parameter estimates simultaneously, instead of two steps (detecting and down-weighting); (2) precisely recovering the severity of aberrant responding. There are two categories of MMM. The first category of methods assumes that the classification (i.e., whether the item is answered normally or aberrantly) can be predicted by RT. While the second category is a natural extension of van der Linden’s (<xref xml:base="bibr" rid="b53">2007</xref>) hierarchical model, which models responses and RTs jointly. In this method, the observed RT, as well as the correct response probability of each item-by-person encounter can be decomposed to RT (or probability) caused by normal response and that caused by aberrant response according to the most important difference between the two distinct behaviors. This method leads to more precisely estimated item and person parameters, as well as excellent classification of aberrant/normal behavior. <p id="p00005">First, this article compares the basic logic of the two traditional RT-based methods and MMM. Aberrant responses are regarded as outliers in both RT threshold method and RT residual method. Therefore, they rely heavily on the severity of aberrance. If data set is contaminated by aberrant responses seriously, the observed RT (or RT residual) distribution will be different from the expected distribution, which in turn leads to low power and sometimes high false detection rate. On the other hand, MMM, which assumes that both observed RT and correct response probability follow a mixture distribution, treats aberrant and normal responses equally. In that way, it has little reliance on the severity of aberrance. In addition to that, MMM can apply to the situation when all the respondents actually respond regularly in theoretic. In that situation, all the responses are assumed to be classified into one category. Second, this article summarizes the disadvantages of the three methods. MMM has three primary limitations: (1) it usually relies heavily on strong assumptions, which means that it may not perform well if these assumptions are violated; (2) low proportion of aberrant response may lead to convergence problem and model identification problem; (3) it is quite complex and time-consuming. In all, practitioners should choose a proper method according to the characteristics of tests and categories of aberrant responses (e.g., rapid-guessing, item with preknowledge, cheating). In the end, this article suggests future researches may investigate the performance of MMM when its assumptions are violated or data consists of more types of aberrant response patterns. Fixing item parameter estimates, proposing some index to help choosing suitable methods, are encouraged to improve the efficiency of MMM.

Does the choice of response time threshold procedure substantially affect inferences concerning the identification and exclusion of rapid guessing responses?\xa0A meta-analysis

BackgroundIn testing contexts that are predominately concerned with power, rapid guessing (RG) has the potential to undermine the validity of inferences made from educational assessments, as such responses are unreflective of the knowledge, skills, and abilities assessed. Given this concern, practitioners/researchers have utilized a multitude of response time threshold procedures that classify RG responses in these contexts based on either the use of no empirical data (e.g., an arbitrary time limit), response time distributions, and the combination of response time and accuracy information. As there is little understanding of how these procedures compare to each other, this meta-analysis sought to investigate whether threshold typology is related to differences in descriptive, measurement property, and performance outcomes in these contexts.MethodsStudies were sampled that: (a) employed two or more response time (RT) threshold procedures to identify and exclude RG responses on the same computer-administered low-stakes power test; and (b) evaluated differences between procedures on the proportion of RG responses and responders, measurement properties, and test performance.ResultsBased on as many as 86 effect sizes, our findings indicated non-negligible differences between RT threshold procedures in the proportion of RG responses and responders. The largest differences for these outcomes were observed between procedures using no empirical data and those relying on response time and accuracy information. However, these differences were not related to variability in aggregate-level measurement properties and test performance.ConclusionsWhen filtering RG responses to improve inferences concerning item properties and group score outcomes, the actual threshold procedure chosen may be of less importance than the act of identifying such deleterious responses. However, given the conservative nature of RT thresholds that use no empirical data, practitioners may look to avoid the use of these procedures when making inferences at the individual-level, given their potential for underclassifying RG.

Comparing different response time threshold setting methods to detect low effort on a large-scale assessment

Low examinee effort is a major threat to valid uses of many test scores. Fortunately, several methods have been developed to detect noneffortful item responses, most of which use response times. To accurately identify noneffortful responses, one must set response time thresholds separating those responses from effortful ones. While other studies have compared the efficacy of different threshold-setting methods, they typically do so using simulated or small-scale data. When large-scale data are used in such studies, they often are not from a computer-adaptive test (CAT), use only a handful of items, or do not comprehensively examine different threshold-setting methods. In this study, we use reading test scores from over 728,923 3rd–8th-grade students in 2056 schools across the United States taking a CAT consisting of nearly 12,000 items to compare threshold-setting methods. In so doing, we help provide guidance to developers and administrators of large-scale assessments on the tradeoffs involved in using a given method to identify noneffortful responses.

Assessing the Accuracy of Parameter Estimates in the Presence of Rapid Guessing Misclassifications.

The presence of rapid guessing (RG) presents a challenge to practitioners in obtaining accurate estimates of measurement properties and examinee ability. In response to this concern, researchers have utilized response times as a proxy of RG and have attempted to improve parameter estimation accuracy by filtering RG responses using popular scoring approaches, such as the effort-moderated item response theory (EM-IRT) model. However, such an approach assumes that RG can be correctly identified based on an indirect proxy of examinee behavior. A failure to meet this assumption leads to the inclusion of distortive and psychometrically uninformative information in parameter estimates. To address this issue, a simulation study was conducted to examine how violations to the assumption of correct RG classification influences EM-IRT item and ability parameter estimation accuracy and compares these results with parameter estimates from the three-parameter logistic (3PL) model, which includes RG responses in scoring. Two RG misclassification factors were manipulated: type (underclassification vs. overclassification) and rate (10%, 30%, and 50%). Results indicated that the EM-IRT model provided improved item parameter estimation over the 3PL model regardless of misclassification type and rate. Furthermore, under most conditions, increased rates of RG underclassification were associated with the greatest bias in ability parameter estimates from the EM-IRT model. In spite of this, the EM-IRT model with RG misclassifications demonstrated more accurate ability parameter estimation than the 3PL model when the mean ability of RG subgroups did not differ. This suggests that in certain situations it may be better for practitioners to (a) imperfectly identify RG than to ignore the presence of such invalid responses and (b) select liberal over conservative response time thresholds to mitigate bias from underclassified RG.

Introducing fairness in Norwegian air ambulance base location planning

BackgroundA primary task of the Norwegian helicopter emergency medical services (HEMS) is to provide advanced medical care to the critical ill and injured outside of hospitals. Where HEMS bases are located, directly influences who in the population can be reached within a given response time threshold and who cannot. When studying the locations of bases, the focus is often on efficiency, that is, maximizing the total number of people that can be reached within a given set time. This approach is known to benefit people living in densely populated areas, such as cities, over people living in remote areas. The most efficient solution is thus typically not necessarily a fair one. This study aims to incorporate fairness in finding optimal air ambulance base locations.MethodsWe solve multiple advanced mathematical optimization models to determine optimal helicopter base locations, with different optimization criteria related to the level of aversion to inequality, including the utilitarian, Bernoulli-Nash and iso-elastic social welfare functions. This is the first study to use the latter social welfare function for HEMS.ResultsFocusing on efficiency, a utilitarian objective function focuses on covering the larger cities in Norway, leaving parts of Norway largely uncovered. Including fairness by rather using an iso-elastic social welfare function in the optimization avoids leaving whole areas uncovered and in particular increases service levels in the north of Norway.ConclusionsIncluding fairness in determining optimal HEMS base locations has great impact on population coverage, in particular when the number of base locations is not enough to give full coverage of the country. As results differ depending on the mathematical objective, the work shows the importance of not only looking for optimal solutions, but also raising the essential question of ‘optimal with respect to what’.

Response Time Threshold for Predicting Outcomes of Patients with Out-of-Hospital Cardiac Arrest.

Ambulance response time is a prognostic factor for out-of-hospital cardiac arrest (OHCA), but the impact of ambulance response time under different situations remains unclear. We evaluated the threshold of ambulance response time for predicting survival to hospital discharge for patients with OHCA. A retrospective observational analysis was conducted using the emergency medical service (EMS) database (January 2015 to December 2019). Prehospital factors, underlying diseases, and OHCA outcomes were assessed. Receiver operating characteristic (ROC) curve analysis with Youden Index was performed to calculate optimal cut-off values for ambulance response time that predicted survival to hospital discharge. In all, 6742 cases of adult OHCA were analyzed. After adjustment for confounding factors, age (odds ratio [OR] = 0.983, 95% confidence interval [CI]: 0.975–0.992, p < 0.001), witness (OR = 3.022, 95% CI: 2.014–4.534, p < 0.001), public location (OR = 2.797, 95% CI: 2.062–3.793, p < 0.001), bystander cardiopulmonary resuscitation (CPR, OR = 1.363, 95% CI: 1.009–1.841, p=0.044), EMT-paramedic response (EMT-P, OR = 1.713, 95% CI: 1.282–2.290, p < 0.001), and prehospital defibrillation using an automated external defibrillator ([AED] OR = 3.984, 95% CI: 2.920–5.435, p < 0.001) were statistically and significantly associated with survival to hospital discharge. The cut-off value was 6.2 min. If the location of OHCA was a public place or bystander CPR was provided, the threshold was prolonged to 7.2 min and 6.3 min, respectively. In the absence of a witness, EMT-P, or AED, the threshold was reduced to 4.2, 5, and 5 min, respectively. The adjusted OR of EMS response time for survival to hospital discharge was 1.217 (per minute shorter, CI: 1.140–1299, p < 0.001) and 1.992 (<6.2 min, 95% CI: 1.496–2.653, p < 0.001). The optimal response time threshold for survival to hospital discharge was 6.2 min. In the case of OHCA in public areas or with bystander CPR, the threshold was prolonged, and without witness, the optimal response time threshold was shortened.

High Sensitivity and Fast Valley Landscape Response to Climate Change in the Lower Reaches of the Jinsha River, Southeastern Qinghai-Tibetan Plateau, Field Characteristics and Numerical Modeling

The Jinsha River, the upper reaches of the Yangtze River, winds and incises through the eastern margin of the Qinghai-Tibetan Plateau, where Asian monsoon climate prevails. Along the Jinsha River, extensive and thick Quaternary valley fillings and multiple river terraces are developed. However, their specific relations to climate change and tectonics remain elusive. In this study, we conducted field investigation, chronological studies and numerical modeling in its lower reaches. Our study indicates that the extensive valley fillings in the Wudongde-Menggu segment were formed in cold-arid climate with Optically Stimulated Luminescence (OSL) ages of ~23-19 ka B.P., coinciding with the timing of the Last Glacial Maximum (LGM). We suggest that the post-LGM warming and humidifying, by restrained sediment supply while enhanced discharge, switched the valley from prevailing aggradation into incision. Multiple subsequent fill-cut terraces, postdating the LGM, were formed and nested in the valley fillings. OSL data indicate that the first to third terrace sediments were formed at ~10 ka B.P., ~11.5-12.5 ka B.P. and ~13.5 ka B.P., respectively. Our study suggests that these terraces are a sensitive record of millennial and sub-millennial cold-arid climate perturbations superimposed over the post-LGM deglaciation. Our modelling highlights a high sensitivity of valley aggradation and incision to cold-arid and warm-wet climate change, as well as a fast valley landscape response in the Jinsha River characterized by high sediment transport influx. We propose that valley landscape and terraces serve as a timely record for climate change in certain rivers with low response time threshold characterized by high sediment transport influx.

Scale-down cultivation in mammalian cell bioreactors—The effect of bioreactor mixing time on the response of CHO cells to dissolved oxygen gradients

Scale-down simulators have been widely applied to investigate the impact of various concentration gradients on the efficiency of industrial-scale fed-batch bioprocesses involving microbial cell factories. However, due to the general fragility and shear sensitivity of mammalian cells, these simulators, especially those with multiple compartments, have not been widely adopted to investigate the effects of similar concentration gradients on cell culture processes. In this work, we developed a multi-compartment scale-down simulator comprising a stirred tank bioreactor and a plug-flow reactor (PFR). CHO cells expressing a recombinant protein were recycled through the PFR whilst being subjected to dissolved oxygen gradients at varying residence times from 70 s to 120 s. The results show a clear cut switch in the metabolism of CHO cells, such that until a residence time of 90s was exceeded, the cells did not respond to the presence of dissolved oxygen gradients in the PFR. Beyond this residence time threshold, there was a marked accumulation of lactate and up to 15 % decline in viable cell density in the stationary phase, compared to the reference fed-batch process. Interestingly, the recombinant protein productivity was not affected by the dissolved oxygen gradients, although the purity of the product, measured as the concentration of host cell proteins in the supernatant was adversely affected. The response time threshold in the metabolism of the cells was used to propose a scale-up technique based on similar physiological indices between bioreactor scales. The demonstrated method is a possible tool for assessing the suitability of a process in a given large scale bioreactor with known mixing times.

Enhancing response time thresholds with response behaviors for detecting disengaged examinees

The item responses of examinees who rapid-guess, who do not spend enough time reading and engaging with an item, will not reflect their true ability on that item. Rapid-disengagement refers to rapidly selecting a response to multiple-choice items (i.e., rapid-guess), omitting items, or providing short-unrelated answers to open-ended items in an unreasonably short time. Such rapid responses need to be identified to enhance the validity of the arguments from the test data. Detection of rapid-guessing behaviors is typically based on identifying a threshold to represent the minimum response time required for the student to have thoughtfully considered a given item. This study investigates whether using response behaviors can improve the detection of rapid-disengagement by investigating two approaches: (a) using response behaviors to decide on the size of the threshold, and (b) using response behaviors as a condition for detecting disengaged examinees in addition to response times, referred as enhanced methods. Process data and item responses from the PISA 2012 computer-based mathematics assessment were used to examine both approaches under threshold values varying from very small (5 s) to very large (60 s). Results suggested that response behaviors can provide meaningful input on establishing the size of the threshold and that while enhanced methods performed better than using only response times in recognizing rapid-disengagement in some cases, no clear pattern was observed as to when such improvement occurs. This study makes a unique contribution by inspecting the response behaviors of disengaged examinees and providing guidelines on using response behaviors to decide on the size of the threshold. This study suggests response behavior categories that can be applicable to many item and response types, which make them suitable for use in digitally-based large-scale assessments.

Modeling Responses and Response Times in Tests With the Hierarchical Model and the Three-Parameter Lognormal Distribution.

The hierarchical model of van der Linden is the most popular model for responses and response times in tests. It is composed of two separate submodels-one for the responses and one for the response times-that are joined at a higher level. The submodel for the response times is based on the lognormal distribution. The lognormal distribution is a skew distribution with a support from zero to infinity. Such a support is unrealistic as the solution process demands a minimal processing time that sets a response time threshold. Ignoring this response time threshold misspecifies the model and threatens the validity of model-based inferences. In this article, the response time model of van der Linden is replaced by a model that is based on the three-parameter lognormal distribution. The three-parameter lognormal distribution extends the lognormal distribution by an additional location parameter that bounds the support away from zero. Two different approaches to model fitting are proposed and evaluated with regard to parameter recovery in a simulation study. The extended model is applied to two data sets. In both data sets, the extension improves the fit of the hierarchical model.