Rt Curve Research Articles

Model-based analysis of the incidence trends and transmission dynamics of COVID-19 associated with the Omicron variant in representative cities in China

BackgroundIn 2022, Omicron outbreaks occurred at multiple sites in China. It is of great importance to track the incidence trends and transmission dynamics of coronavirus disease 2019 (COVID-19) to guide further interventions.MethodsGiven the population size, economic level and transport level similarities, two groups of outbreaks (Shanghai vs. Chengdu and Sanya vs. Beihai) were selected for analysis. We developed the SEAIQRD, ARIMA, and LSTM models to seek optimal modeling techniques for waves associated with the Omicron variant regarding data predictive performance and mechanism transmission dynamics, respectively. In addition, we quantitatively modeled the impacts of different combinations of more stringent interventions on the course of the epidemic through scenario analyses.ResultsThe best-performing LSTM model showed better prediction accuracy than the best-performing SEAIQRD and ARIMA models in most cases studied. The SEAIQRD model had an absolute advantage in exploring the transmission dynamics of the outbreaks. Regardless of the time to inflection point or the time to Rt curve below 1.0, Shanghai was later than Chengdu (day 46 vs. day 12/day 54 vs. day 14), and Sanya was later than Beihai (day 16 vs. day 12/day 20 vs. day 16). Regardless of the number of peak cases or the cumulative number of infections, Shanghai was higher than Chengdu (34,350 vs. 188/623,870 vs. 2,181), and Sanya was higher than Beihai (1,105 vs. 203/16,289 vs. 3,184). Scenario analyses suggested that upgrading control level in advance, while increasing the index decline rate and quarantine rate, were of great significance for shortening the time to peak and Rt below 1.0, as well as reducing the number of peak cases and final affected population.ConclusionsThe LSTM model has great potential for predicting the prevalence of Omicron outbreaks, whereas the SEAIQRD model is highly effective in revealing their internal transmission mechanisms. We recommended the use of joint interventions to contain the spread of the virus.

Cross-sectional Ct distributions from qPCR tests can provide an early warning signal for the spread of COVID-19 in communities.

SARS-CoV-2 PCR testing data has been widely used for COVID-19 surveillance. Existing COVID-19 forecasting models mainly rely on case counts obtained from qPCR results, even though the binary PCR results provide a limited picture of the pandemic trajectory. Most forecasting models have failed to accurately predict the COVID-19 waves before they occur. Recently a model utilizing cross-sectional population cycle threshold (Ct-the number of cycles required for the fluorescent signal to cross the background threshold) values obtained from PCR tests (Ct-based model) was developed to overcome the limitations of using only binary PCR results. In this study, we aimed to improve on COVID-19 forecasting models using features derived from the Ct-based model, to detect epidemic waves earlier than case-based trajectories. PCR data was collected weekly at Northeastern University (NU) between August 2020 and January 2022. Campus and county epidemic trajectories were generated from case counts. A novel forecasting approach was developed by enhancing a recent deep learning model with Ct-based features and applied in Suffolk County and NU campus. For this, cross-sectional Ct values from PCR data were used to generate Ct-based epidemic trajectories, including effective reproductive rate (Rt) and incidence. The improvement in forecasting performance was compared using absolute errors and residual squared errors with respect to actual observed cases at the 7-day and 14-day forecasting horizons. The model was also tested prospectively over the period January 2022 to April 2022. Rt curves estimated from the Ct-based model indicated epidemic waves 12 to 14 days earlier than Rt curves from NU campus and Suffolk County cases, with a correlation of 0.57. Enhancing the forecasting models with Ct-based information significantly decreased absolute error (decrease of 49.4 and 221.5 for the 7 and 14-day forecasting horizons) and residual squared error (40.6 and 217.1 for the 7 and 14-day forecasting horizons) compared to the original model without Ct features. Ct-based epidemic trajectories can herald an earlier signal for impending epidemic waves in the community and forecast transmission peaks. Moreover, COVID-19 forecasting models can be enhanced using these Ct features to improve their forecasting accuracy. In this study, we make the case that public health agencies should publish Ct values along with the binary positive/negative PCR results. Early and accurate forecasting of epidemic waves can inform public health policies and countermeasures which can mitigate spread.

Epidemiological characteristics and dynamic transmissions of COVID-19 pandemics in Chinese mainland: A trajectory clustering perspective analysis

BackgroundThe corona virus disease 2019 (COVID-19) pandemic has spread to more than 210 countries and regions around the world, with different characteristics recorded depending on the location. A systematic summarization of COVID-19 outbreaks that occurred during the “dynamic zero-COVID” policy period in Chinese mainland had not been previously conducted. In-depth mining of the big data from the past two years of the COVID-19 pandemics must be performed to clarify their epidemiological characteristics and dynamic transmissions. MethodsTrajectory clustering was used to group epidemic and time-varying reproduction number (Rt) curves of mass outbreaks into different models and reveal the epidemiological characteristics and dynamic transmissions of COVID-19. For the selected single-peak epidemic curves, we constructed a peak-point judgment model based on the dynamic slope and adopted a single-peak fitting model to identify the key time points and peak parameters. Finally, we developed an extreme gradient boosting-based prediction model for peak infection cases based on the total number of infections on the first 3, 5, and 7 days of the initial average incubation period. Results(1) A total of 7 52298 cases, including 587 outbreaks in 251 cities in Chinese mainland between June 11, 2020, and June 29, 2022, were collected, and the first wave of COVID-19 outbreaks was excluded. Excluding the Shanghai outbreak in 2022, the 586 remaining outbreaks resulted in 1 25425 infections, with an infection rate of 4.21 per 1 00000 individuals. The number of outbreaks varied based on location, season, and temperature.(2) Trajectory clustering analysis showed that 77 epidemic curves were divided into four patterns, which were dominated by two single-peak clustering patterns (63.3%). A total of 77 Rt curves were grouped into seven patterns, with the leading patterns including four downward dynamic transmission patterns (74.03%). These curves revealed that the interval from peak to the point where the Rt value dropped below 1 was approximately 5 days.(3) The peak-point judgment model achieved a better result in the area under the curve (0.96, 95% confidence interval = 0.90–1.00). The single-peak fitting results on the epidemic curves indicated that the interval from the slow-growth point to the sharp-decline point was approximately 4–6 days in more than 50% of mass outbreaks.(4) The peak-infection-case prediction model exhibited the superior clustering results of epidemic and Rt curves compared with the findings without grouping. ConclusionOverall, our findings suggest the variation in the infection rates during the “dynamic zero-COVID” policy period based on the geographic division, level of economic development, seasonal division, and temperature. Trajectory clustering can be a useful tool for discovering epidemiological characteristics and dynamic transmissions, judging peak points, and predicting peak infection cases using different patterns.

Identification of Diagenetic Facies Logging of Tight Oil Reservoirs Based on Deep Learning—A Case Study in the Permian Lucaogou Formation of the Jimsar Sag, Junggar Basin

As a typical tight oil reservoir in a lake basin, the Permian Lucaogou Formation of the Jimsar Sag in the Junggar Basin has great potential for exploration and development. However, at present, there are few studies on the identification of the diagenetic facies of tight oil reservoir logging in the study area, and the control effect of diagenesis on tight oil reservoirs is not clear. The present work investigates the diagenesis and diagenetic facies logging of the study area, making full use of core data, thin sections, and logs, among other data, in order to understand the reservoir characteristics of the Permian Lucaogou Formation in the Jimsar Sag. The results show that the Lucaogou Formation has undergone diagenetic activity such as compaction, carbonate cementation, quartz cementation, and clay mineral infilling and dissolution. The diagenetic facies are classified according to mineral and diagenetic type, namely, tightly compacted facies, carbonate-cemented facies, clay mineral-filling facies, quartz-cemented facies, and dissolution facies. The GR, RT, AC, DEN, and CNL logging curves were selected, among others, and the convolutional neural network was introduced to construct a diagenetic facies logging recognition model. The diagenetic facies of a single well was divided and identified, and the predicted diagenetic facies types were compared with thin sections and SEM images of the corresponding depths. Prediction results had a high coincidence rate, which indicates that the model is of a certain significance to accurately identify the diagenetic facies of tight oil reservoirs. Assessing the physical properties of the studied reservoirs, dissolution facies are the dominant diagenetic facies in the study area and are also the preferred sequence for exploration—to find dominant reservoirs in the following stage.

Assessing the effect of non-pharmaceutical interventions on COVID-19 transmission in Spain, 30 August 2020 to 31 January 2021.

BackgroundAfter a national lockdown during the first wave of the COVID-19 pandemic in Spain, regional governments implemented different non-pharmaceutical interventions (NPIs) during the second wave.AimTo analyse which implemented NPIs significantly impacted effective reproduction number (Rt) in seven Spanish provinces during 30 August 2020–31 January 2021.MethodsWe coded each NPI and levels of stringency with a ‘severity index’ (SI) and computed a global SI (mean of SIs per six included interventions). We performed a Bayesian change point analysis on the Rt curve of each province to identify possible associations with global SI variations. We fitted and compared several generalised additive models using multimodel inference, to quantify the statistical effect on Rt of the global SI (stringency) and the individual SIs (separate effect of NPIs).ResultsThe global SI had a significant lowering effect on the Rt (mean: 0.16 ± 0.05 units for full stringency). Mandatory closing times for non-essential businesses, limited gatherings, and restricted outdoors seating capacities (negative) as well as curfews (positive) were the only NPIs with a significant effect. Regional mobility restrictions and limited indoors seating capacity showed no effect. Our results were consistent with a 1- to 3-week-delayed Rt as a response variable.ConclusionWhile response measures implemented during the second COVID-19 wave contributed substantially to a decreased reproduction number, the effectiveness of measures varied considerably. Our findings should be considered for future interventions, as social and economic consequences could be minimised by considering only measures proven effective.

Social isolation relaxation and the effective reproduction number (Rt) of COVID-19 in twelve Brazilian cities

Abstract We analyzed the social isolation relaxation strategies adopted by the twelve biggest Brazilian cities in 2020, in relation to the number of cases, number of deaths and the effective reproduction number (Rt), which are internationally considered the fundamental epidemiological criteria for allowing wider population mobility in public spaces. The Brazilian central government has not set unique guidelines neither for closure nor for opening, and states and cities have taken the lead in strategy definition. Until July 31 2020, in Belém do Pará, Fortaleza, Manaus, Recife and Rio de Janeiro, where the epidemic peak had already been surpassed, and in Salvador and São Paulo, in which the peak seemed to be already reached, the Rt curve followed a decreasing path after the openings. Porto Alegre, a city in which the epidemic curve was flattened, had an increase in Rt after the start of relaxation. In Belo Horizonte, Brasília, Curitiba and Goiânia, where the curve was also flattened, the Rt remained stable after the opening. The decision on how to operationalize the relaxation of social isolation and the speed with which it happened was heterogeneous among the cities studied. Also, broad population testing strategies were not done in any of the cities.

Reparations for Black American descendants of persons enslaved in the U.S. and their potential impact on SARS-CoV-2 transmission.

BackgroundIn the United States, Black Americans are suffering from a significantly disproportionate incidence of COVID-19. Going beyond mere epidemiological tallying, the potential for racial-justice interventions, including reparations payments, to ameliorate these disparities has not been adequately explored.MethodsWe compared the COVID-19 time-varying Rt curves of relatively disparate polities in terms of social equity (South Korea vs. Louisiana). Next, we considered a range of reproductive ratios to back-calculate the transmission rates for 4 cells of the simplified next-generation matrix (from which R0 is calculated for structured models) for the outbreak in Louisiana. Lastly, we considered the potential structural effects monetary payments as reparations for Black American descendants of persons enslaved in the U.S. would have had on pre-intervention and consequently R0.ResultsOnce their respective epidemics begin to propagate, Louisiana displays Rt values with an absolute difference of 1.3–2.5 compared to South Korea. It also takes Louisiana more than twice as long to bring Rt below 1. Reasoning through the consequences of increased equity via matrix transmission models, we demonstrate how the benefits of a successful reparations program (reflected in the ratio ) could reduce R0 by 31–68%.DiscussionWhile there are compelling moral and historical arguments for racial-injustice interventions such as reparations, our study considers potential health benefits in the form of reduced SARS-CoV-2 transmission risk. A restitutive program targeted towards Black individuals would not only decrease COVID-19 risk for recipients of the wealth redistribution; the mitigating effects would also be distributed across racial groups, benefiting the population at large.

The time-varying transmission dynamics of COVID-19 and synchronous public health interventions in China

ObjectivesWe aimed to estimate the time-varying transmission dynamics of COVID-19 in China, Wuhan City, and Guangdong province, and compare to that of severe acute respiratory syndrome (SARS). MethodsData on COVID-19 cases in China up to 20 March 2020 was collected from epidemiological investigations or official websites. Data on SARS cases in Guangdong Province, Beijing, and Hong Kong during 2002–3 was also obtained. We estimated the doubling time, basic reproduction number (R0), and time-varying reproduction number (Rt) of COVID-19 and SARS. ResultsAs of 20 March 2020, 80,739 locally acquired COVID-19 cases were identified in mainland China, with most cases reported between 20 January and 29 February 2020. The R0 value of COVID-19 in China and Wuhan was 5.0 and 4.8, respectively, which was greater than the R0 value of SARS in Guangdong (R0 = 2.3), Hong Kong (R0 = 2.3), and Beijing (R0 = 2.6). At the start of the COVID-19 epidemic, the Rt value in China peaked at 8.4 and then declined quickly to below 1.0 in one month. With SARS, the Rt curve saw fluctuations with more than one peak, the highest peak was lower than that for COVID-19. ConclusionsCOVID-19 has much higher transmissibility than SARS, however, a series of prevention and control interventions to suppress the outbreak were effective. Sustained efforts are needed to prevent the rebound of the epidemic in the context of the global pandemic.

Forcing Seasonality of Influenza-like Epidemics with Daily Solar Resonance.

SummarySeasonality of acute viral respiratory diseases is a well-known and yet not fully understood phenomenon. Several models have been proposed to explain the regularity of yearly recurring outbreaks and the phase differences observed at different latitudes on the Earth. Such models consider known internal causes, primarily the periodic emergence of new virus variants that evade the host immune response. Yet, this alone is generally unable to explain the regularity of recurrences and the observed phase differences.Here we show that seasonality of viral respiratory diseases, as well as its distribution with latitude on the Earth, can be fully explained by the virucidal properties of UV-B and UV-A solar photons through a daily, minute-scale, resonant forcing mechanism. Such an induced periodicity can last, virtually unperturbed, from tens to hundreds of cycles, and even in the presence of internal dynamics (host's loss of immunity) much slower than seasonal will, on a long period, generate seasonal oscillations.

Time to Rt < 1 for COVID-19 public health lockdown measures.

The epidemiological target of lockdowns is to drive down the effective reproduction number (Rt) to less than 1. A key unknown is the duration that lockdowns need to be in place to achieve this and which lockdown measures are effective. Daily number of laboratory confirmed community coronavirus 2019 cases were extracted from regular reports from the Ministry of Health Singapore from 20 March 2020 to 4 May 2020. We generated daily Rt to estimate the time needed for these public health lockdown measures to control the spread of severe acute respiratory syndrome coronavirus 2 as demonstrated by Rt < 1. It took about 14 days of nationwide lockdown for the Rt trend to change and start falling. The upper limit of the 95% confidence interval for time to Rt < 1 was day 15 of lockdown. We have shown that it is possible to start 'bending the Rt curve' about 2 weeks after implementation of specific lockdown measures with strict compliance.

Structural and magnetotransport properties of topological trivial LuNiBi single crystals

In this work, we have grown the high-quality LuNiBi single crystals by a Bi flux method. The band gaps from calculation and fitting RT curve both show a small value that indicates LuNiBi is a gapless semiconductor. And we present the magnetic field dependency of transport properties for LuNiBi single crystal. Because of the strong spin-orbital coupling (SOC), some fascinating transport properties were observed. A cusp in the low magnetic field region that is similar to weak antilocalization (WAL) effect was observed in magnetoresistance (MR). And large MR reaching to 105% at a field of 2T and 81% at 1T field makes LuNiBi single crystal become a potential material candidate for applications in high-sensitivity magnetic sensors.

On the contribution of overt tactile expectations to visuo-tactile interactions within the peripersonal space

Since the discovery of neural regions in the monkey brain that respond preferentially to multisensory stimuli presented in proximal space, researchers have been studying this specialised spatial representation in humans. It has been demonstrated that approaching auditory or visual stimuli modulate tactile processing, while they are within the peripersonal space (PPS). The aim of the current study is to investigate the additional effects of tactile expectation on the PPS-related multisensory interactions. Based on the output of a computational simulation, we expected that as tactile expectation increases rapidly during the course of the motion of the visual stimulus, the outcome RT curves would mask the multisensory contribution of PPS. When the tactile expectation remains constant during the motion, the PPS-related spatially selective multisensory processes become apparent. The behavioural results on human experiments followed the pattern predicted by the simulation. That is, rapidly changing levels of tactile expectation, caused by dynamic visual stimuli, masks the outcome of the multisensory processes within peripersonal space. This indicates that both PPS-related multisensory interactions and tactile expectations play an important role in anticipating and responding to interactions with the body.

Emotion and Implicit Timing.

This study examined the effects of emotion on implicit timing. In the implicit timing task used, the participants did not receive any temporal instructions. Instead they were simply asked and trained to press a key as quickly as possible after a stimulus (response stimulus) that was separated from a preceding stimulus by a given temporal interval (reference interval duration). However, in the testing phase, the interval duration was the reference interval duration or a shorter or longer interval duration. In addition, the participants attended two sessions: a first baseline session in which no stimulus was presented during the inter-stimulus intervals, and a second emotional session in which emotional facial expressions (angry, neutral and sad facial expressions) were presented during these intervals. Results showed faster RTs for interval durations close to the reference duration in both the baseline and the emotional conditions and yielded a U-shaped curve. This suggests that implicit processing of time persists in emotional contexts. In addition, the RT was faster for the facial expressions of anger than for those of neutrality and sadness. However, the U-shaped RT curve did not peak clearly at a shorter interval duration for the angry than for the other facial expressions. This lack of time distortion in an implicit timing task in response to arousing emotional stimuli questions the idea of an automatic speeding-up of the interval clock system involved in the representation of time.

Fast prediction method of Archie’s cementation exponent

Archie’s cementation exponent (m) is the most important parameter in calculating water saturation. Using core measurements to obtain m is often expensive and cannot be carried out in all reservoirs. Besides, because of rare uncontaminated connate water samples in most cases, it is difficult to use connate water resistivity (Rw) to calculate accurate m directly by using Archie’s equation in water zone. In this study, based on Archie’s equation in an interconnected water layer, a prediction method of cementation exponent is proposed. The method includes two main steps. The first step is to propose a numerical method and the corresponding program to obtain the fixed Rw and variable m in a water layer. The program calculates formation resistivity values (Rt_cal) at each Rw (a total of 50 values) and m (a total of 161 values) in an interval, and then it consists of two comparisons: (1) the program compares the 161 Rt_cal values for each Rw value with the measured formation resistivity (Rt) at each depth to obtain the Rt_cal of the minimum error; (2) 50 Rt_cal curves of all Rw values are collected in the interval and are used to compare with the Rt curves using the minimum error and smallest standard deviation to obtain the best Rt_cal curve. Therefore, the fixed Rw and variable m can be obtained corresponding to the best Rt_cal curve. The second step includes several steps as follows: (1) establishing the porosity estimation model by using the core scale logging method, porosity curve can be calculated from conventional logs by using it; (2) choosing a representative water layer, the fixed Rw and variable m can be obtained by using the program; (3) calibrating the values of x and y by using the cross-plot method, the regression relationship between φ and m can be established; (4) considering the same geologic setting, the regression relationship can be used to predict variable m in adjacent reservoirs. The synthetic test example can validate the reliability of the proposed numerical method and program, and two field examples from different basins can confirm the availability and applicability of the prediction method. The method could provide an alternative solution in the petrophysical assessment (Rw and m) of exploratory and appraisal wells which are usually lack of rock resistivity measurements.

Probabilistic rainfall thresholds for flood forecasting: evaluating different methodologies for modelling rainfall spatial correlation (or dependence)

AbstractRainfall threshold (RT) method is one of the evolving flood forecasting approaches. When the cumulative rainfall depth for a given initial soil moisture condition intersects the threshold rainfall curve, the peak discharge is expected to be equal or greater than the threshold discharge for flooding at the target site. Besides the total rainfall depth, spatial and temporal distribution of rainfall impacts the flood peak discharge and the time to peak. To revisit a previous study conducted by the authors, in which spatially independent rainfall pattern was assumed, the spatial distribution of rainfall was simulated following a Monte Carlo approach. The structure of the spatial dependence among sub‐watersheds' rainfalls was taken into account under three different scenarios, namely independent, bivariate copula (2copula) and multivariate Gaussian copula (MGC). For each set of generated random dimensionless rainfalls, the probabilistic RT curves were derived for dry moisture condition. Results were evaluated with both historical and simulated events. For the simulated events, threshold curves were assessed by means of categorical statistics, such as hit rate, false rate and critical success index (CSI). Results revealed that the best performance based on the CSI criterion corresponded to 50% curve in 2copula and MGC scenarios as well as 90% curve in the independent scenario. The recognition of 50% curve in 2copula and MGC scenarios is in agreement with our expectations that the mean probable curve should have the best performance. Moreover, the proposed inclusion of spatially dependent rainfall scenario improved the performance of RT curves by about 25% in comparison with the presumed spatially uniform rainfall scenario. Copyright © 2011 John Wiley &amp; Sons, Ltd.

Characterizing Pelvis Dynamics in Adolescent With Idiopathic Scoliosis

Pelvic dynamic analysis in adolescents with idiopathic scoliosis (AIS). To examine and characterize pelvis dynamics in AIS. Although studies have examined spine and pelvis postural differences between female adolescents with and without scoliosis much is still unknown about the dynamics of pelvis in trunk-pelvic interaction and how the type of scoliosis compromises pelvic mobility consequently affecting the overall dynamics of the trunk-pelvis kinematic chain. A total of 25 female AIS (18 right thoracic: RT and 7 right thoracic-left lumbar: RTLL) and 12 controls were recruited. Reflective markers were placed on the trunk and pelvis and their trajectories were recorded using a 5-camera motion capture system. Three trials were carried out, one for each of the various trunk-pelvis movements (flexion/extension, lateral bend, and axial rotation on either side) performed by the subjects. Pelvic alignment in the 3 planes were significantly different for all movement types (P < 0.001), with distinct differences in pelvic sagittal tilt and transverse plane rotation, particularly during lateral bending and axial rotation in patients with RT and LL curves (P = 0.035, P = 0.006, respectively). A majority of the patients from the 2 scoliotic groups had the pelvis rotated to the side of the major curve (right). Although RT subjects had similar dynamic pelvic responses as the controls, the RT-LL patients had relatively more pelvic sagittal tilt during lateral bending and axial rotation toward the major curve. In AIS, the initial three-dimensional alignment of the pelvis (sagittal and frontal tilt, transverse plane rotation) plays an essential role in dictating the biomechanics of the pelvis for any movement type. A spatial concurrency in pelvic alignment was noted wherein a change in 1 parameter will affect the remaining 2. Increased pelvic sagittal tilt in the RT-LL subjects was substituted by more pelvic rotation in the RT subjects during trunk flexion/extension. Differences in pelvic dynamics in AIS are not evident in discrete parameters, for example, total ranges-of-motion but more so in its biomechanics during the movement, which in turn is dictated by the initial alignment of the pelvis.

Modeling the survival of Salmonella spp. in chorizos

The survival of Salmonella spp. in chorizos has been studied under the effect of storage conditions; namely temperature ( T = 6, 25, 30 °C), air inflow velocity ( F = 0, 28.4 m/min), and initial water activity ( a w0 = 0.85, 0.90, 0.93, 0.95, 0.97). The pH was held at 5.0. A total of 20 survival curves were experimentally obtained at various combinations of operating conditions. The chorizos were stored under four conditions: in the refrigerator (Ref: T = 6 °C, F = 0 m/min), at room temperature (RT: T = 25 °C, F = 0 m/min), in the hood (Hd: T = 25 °C, F = 28.4 m/min), and in the incubator (Inc: T = 30 °C, F = 0 m/min). Semi-logarithmic plots of counts vs. time revealed nonlinear trends for all the survival curves, indicating that the first-order kinetics model (exponential distribution function) was not suitable. The Weibull cumulative distribution function, for which the exponential function is only a special case, was selected and used to model the survival curves. The Weibull model was fitted to the 20 curves and the model parameters ( α and β) were determined. The fitted survival curves agreed with the experimental data with R 2 = 0.951, 0.969, 0.908, and 0.871 for the Ref, RT, Hd, and Inc curves, respectively. Regression models relating α and β to T, F, and a w0 resulted in R 2 values of 0.975 for α and 0.988 for β. The α and β models can be used to generate a survival curve for Salmonella in chorizos for a given set of operating conditions. Additionally, α and β can be used to determine the times needed to reduce the count by 1 or 2 logs ( t 1 D and t 2 D ). It is concluded that the Weibull cumulative distribution function offers a powerful model for describing microbial survival data. A comparison with the pathogen modeling program (PMP) revealed that the survival kinetics of Salmonella spp. in chorizos could not be adequately predicted using PMP which underestimated the t 1 D and t 2 D . The mean of the Weibull probability density function correlated strongly with t 1 D and t 2 D , and can serve as an alternative to the D-values normally used with first-order kinetic models. Parametric studies were conducted and sensitivity of survival to operating conditions was evaluated and discussed in the paper. The models derived herein provide a means for the development of a reliable risk assessment system for controlling Salmonella spp. in chorizos.

Frozen magnetoresistance in the magnetization reversal of granular Bi(Pb)-HTSCs

The frozen magnetoresistance of ceramic Bi(Pb)-HTSC samples is investigated as a function of the fields initiating magnetic flux trapping and the magnetization-reversing fields: Rt(Hi,Hr). It is found that the Rt(Hr) curves are nonmonotonic. The value of the frozen magnetoresistance decreases substantially after application of the first Hr pulse (Hr&amp;lt;Hi) but remains practically unchanged upon subsequent magnetization reversals by pulses of the same magnitude but of either polarity. The influence of the magnetization reversal on the anisotropy of the magnetoresistance and the negative magnetoresistance effect are studied. It is shown that the results are in conflict with models of the critical state for the granules and superconducting loops but are well described quantitatively by the proposed model of granular Bi(Pb)-HTSCs, according to which the magnetic flux trapping occurs in “normal” granules wrapped in superconducting shells, while the resistance of the samples is determined by chains of weak links.

Is Rotation of Visual Mental Images a Motor Act?

The relationship between the mechanisms of vision and of visual mental imagery, such as mental rotation, has been well established. The relations between mental rotation and motor action, on the other hand, have hardly been studied, despite the fact that, ecologically, most non-mental rotation is the result of motor actions such as manual manipulation of medium-sized objects. I propose the following motor/imagery hypothesis: transformations of visual mental images are functionally closely related to the planning stages of the motor system. There is a certain amount of indirect support for this hypothesis in the literature. In the present work the motor/imagery hypothesis was tested directly, by means of a dual task paradigm. Subjects performed two tasks simultaneously: the Shepard - Cooper visual imagery task, which involves mental rotation; and a motor rotation (which could not be seen), turning a joystick handle in the plane of the visual image at a previously learned angular speed and direction. The motor/imagery hypothesis predicts a correlation between corresponding features of the two rotations. The results strongly confirm the motor/imagery hypothesis. The concurrent motor task shifts the classic V-shaped mental rotation RT curve: mental rotation is faster and less error-prone when it is in the same direction as the motor rotation than when it is in the opposite direction. Moreover, there is a strong correlation between the speeds of the two rotations: all else being equal, subjects' mental rotations were slower when their manual rotations were slower, and vice versa.

Reaction Times in the Study of Strategies in Sentence–Picture Verification: A Reconsideration

Investigations of cognitive strategies based on chronometric data may appear to contradict findings from verbal-report-based approaches. These inconsistencies may be due to misuse of RTs to infer subjects’ behaviour. To test this hypothesis, 15 subjects were successively required to adopt 4 different strategies in a sentence–picture verification task. Trend analyses provide evidence that (1) highly dissimilar strategies can nevertheless yield similar mean RT curves as well as similar individual subjects’ RT curves; (2) subjects using similar strategies can produce individual RT curves presenting vastly different features due partly to random variation and partly to idiosyncrasies. These findings suggest that RTs are an unreliable behavioural indicator for inferring individual or group strategies on certain experimental tasks and should be analysed in conjunction with other sources of information. An approach consisting of using RTs to test hypotheses based on subjects’ verbal reports is described along with the appropriate controls. Results show that this approach provides an improved account for observed RTs.