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The development of effective risk sharing mechanisms is one of the main passages for the success and longevity of a monetary union. In this paper, we study risk sharing, measured as income and consumption smoothing, in the EMU. As we employ time-varying estimations, we are able to retrieve time patterns of risk sharing for each member country and to compare them with the degree of economic asymmetry within the EMU. Other than documenting the need for stronger risk sharing mechanisms in the EMU, our results also suggest that much more attention should be dedicated to fostering homogeneity in risk sharing across member countries. We document the existence of increasing heterogeneity in the risk sharing capacity between member countries that can potentially exacerbate and amplify the impact of asymmetric shocks and further destabilize the EMU.

Background: Sit–stand desks have been suggested as an initiative to increase posture variation among office workers. However, there is limited evidence of what would be preferable combinations of time sitting and standing. The aim of this study was to determine and compare perceived pleasantness, acceptability, pain, and fatigue for 5 time patterns of sitting and standing at a sit–stand desk. Methods: Thirty postgraduate students were equally divided into a normal-weight (mean body mass index 22.8 kg/m2) and an overweight/obese (mean body mass index 28.1 kg/m2) group. They performed 3 hours of computer work at a sit–stand desk on 5 different days, each day with a different time pattern (A: 60-min sit/0-min stand; B: 50/10; C: 40/20; D: 30/30; E: 20/40). Pleasantness, acceptability, pain, and fatigue ratings were obtained at the beginning and at the end of the 3-hour period. Results: High ratings of pleasantness were observed for time patterns B, C, and D in both groups. All participants rated acceptability to be good for time patterns A to D. A minor increase in perceived fatigue and pain was observed in time pattern E. Conclusion: For new sit–stand desk users, regardless of body mass index, 10 to 30 minutes of standing per hour appears to be an amenable time pattern.

To analyze missed rib fractures and proper time for evaluation on CT at different ages and to determine factors that favor missed fractures. One hundred patients with rib fractures who underwent CT were classified into three groups according to their age: young, middle-aged, and elderly. CT was performed within 1 to 6 weeks after trauma. The imaging features and temporal changes of rib fractures were analyzed. At the first CT during the initial week, 638 ribs were detected with one or several fractures, overall 838 fractures were confirmed, and 6 were suspected. In the next 2–6 weeks, 47 occult rib fractures were additionally detected. The number of additionally diagnosed fractures was the highest in respectively the 3rd week among younger, 4th week in the middle-aged, and 6th week in the elderly groups. The detection of occult rib fractures was significantly delayed in the middle-aged and elderly groups compared with the young group (p < 0.05). The time to form bony callus was also significantly (p < 0.05) delayed with age, with significantly (p < 0.05) more time needed to form bony callus in the middle-aged (23.8 ± 4.5 days) and elderly (28.48 ± 5.1 days) groups than in the young group (18.0 ± 2.2 days). Most rib fractures can be detected within the first week after trauma. Detection of occult rib fractures will be delayed with increase of age, and repeated CT scanning should be appropriately postponed in patients at different ages. Trabecula, inner and outer plates, costal angle, and cartilage are the primary locations for occult and subtle fractures which should be carefully evaluated. • More rib fractures can be detected on repeated CT scans, especially for subtle and occult rib fractures. • Detection of all rib fractures helps relieve the patient’s concerns and determine the degree of personal injury for appropriate evaluation.

Limb position is a factor that negatively affects myoelectric pattern recognition classification accuracy. However, prior studies evaluating impact on real-time control for upper-limb amputees have done so without a physical prosthesis on the residual limb. It remains unclear how limb position affects real-time pattern recognition control in amputees when their residual limb is supporting various weights. We used a virtual reality target achievement control test to evaluate the effects of limb position and external load on real-time pattern recognition control in fourteen intact limb subjects and six major upper limb amputee subjects. We also investigated how these effects changed based on different control system training methods. In a static training method, subjects kept their unloaded arm by their side with the elbow bent whereas in the dynamic training method, subjects moved their arm throughout a workspace while supporting a load. When static training was used, limb position significantly affected real-time control in all subjects. However, amputee subjects were still able to adequately complete tasks in all conditions, even in untrained limb positions. Moreover, increasing external loads decreased controller performance, albeit to a lesser extent in amputee subjects. The effects of limb position did not change as load increased, and vice versa. In intact limb subjects, dynamic training significantly reduced the limb position effect but did not completely remove them. In contrast, in amputee subjects, dynamic training eliminated the limb position effect in three out of four outcome measures. However, it did not reduce the effects of load for either subject population. These findings suggest that results obtained from intact limb subjects may not generalize to amputee subjects and that advanced training methods can substantially improve controller robustness to different limb positions regardless of limb loading.

We model network formation in a firm. Agents learn about the quality of their working relationships with each other. Their good relationships become their networks. Accumulating relationships becomes increasingly costly, however. Over time agents become less open to forming relationships with others unknown to them, leading their networks to be front-loaded with agents they met near the beginning of their careers. The interaction of this dynamic with turnover yields predictions about the time pattern of history dependence in an agent’s network as a function of his tenure. Mutual openness of newly arrived agents in a firm also leads to the cross-section prediction of “cohort attachment,” a tendency for members of an agent’s hiring cohort to be disproportionately represented in his network. When members of a network formed within a firm are subsequently split across many firms, the desire to renew their successful working relationships can lead to job referrals. Former co-workers who provide referrals will be drawn disproportionately from the referred workers’ hiring cohorts at their previous employers.

During tuberculosis (TB) treatment, the period of transmission will shorten and disease will be better controlled in the society if the drugs be more potent and the sputum conversion time from positive to negative be less. There are two drug regimens in the treatment of TB: fixed-dose combination drugs and separate-dose drugs. Our aim in the study was comparing the sputum conversion time pattern in TB smear-positive patients treated with the aforementioned regimens. This randomized clinical trial was done on 331 patients with smear-positive TB. Randomization was based on random numbers table. Intervention group was treated with fixed-dose combination, and nonintervention group was treated with separate drugs. Smear conversion time pattern at the end of second, third, fourth, and sixth months after beginning of the treatment was compared and analyzed by extended Cox regression test. Sputum smear conversion rate in the intervention and control group at the end of second, third, and fourth months of treatment was 70.23 versus 76.47%, 54 versus 67.24%, and 33.33 versus 68.75%, respectively (P>0.05). Variables such as smoking, drug addiction, and sputum bacillary load were effective on smear conversion time in two study groups. The study results showed no difference in efficacy of two-drug regimens in conversion time of sputum smears to negative in TB smear-positive patients.

With the rise of social networking and the awareness of privacy protection, the large-scale positioning data is getting harder to access while the clickstream data of social networking is accumulating. It is necessary to conduct a comprehensive study on the temporal property and spatial distribution of social network’s clickstream to determine the latent relationship between clickstream and location semantics which semantically annotate locations to help us understand the purpose of a social network user at a certain location and a particular time. In this paper, we first infer the location semantics from Internet logs as our baseline which is a large scale, imprecise positioning mobile dataset through combining the utilization of derived time pattern and speed pattern. Then we design a method to reconstruct location semantics through the social network. We are the first to our knowledge that define “click motif” of social network’s clickstream which is the combination of clicks in clickstream that occurs repeatedly and has significance. Click motif not only can help us to classify location semantics but also enhance the user experience of social networking. Besides, we propose a completed process to extract typical click motifs from a large-scale complicated clickstream data via embedding and clustering method. By extensive experiments and analysis, we demonstrate that different combination of click motifs can convey the users’ location semantics, therefore clickstream may disclose location privacy.

Background and Aim: Metaphor is a systematic relationship between two conceptual domains. In metaphor; an experimental or sensual domain called source domain, is related to another domain as target domain. The purpose of this study was to review understanding of metaphorical time pattern in the medical and paramedical students based on gender, age and academic status. Materials and Methods: This descriptive study included 120 medical and paramedical students of Tehran medical university with minimum undergraduate university degree. Time metaphorical pattern questionnaire which had been designed by Raiisi (2019) on the basis of time metaphor corpus analysis included 3 subscales of object, place and matter. Pearson correlation test, T test, analysis of one-way variance and post hoc test (least significant difference) were used for data analysis. Results: The results showed that there was no difference between gender and understanding of metaphorical time pattern. Higher educational levels (from undergraduate to postgraduate and specialty courses) led to better understanding of metaphorical time pattern in Persian speaker students. Students of higher age showed improved understanding of metaphorical time pattern in relation to the object subclass. Conclusion: Perception of the time is not dependent on gender but can be improved with increasing age and higher academic levels.

Introduction Routine follow‐up after curative treatment of patients with oral squamous cell carcinoma (OSCC) is common practice considering the high risk of second primaries and recurrences (ie second events). Current guidelines advocate a follow‐up period of at least 5 years. The recommendations are not evidence‐based and benefits are unclear. This is even more so for follow‐up after a second event. To facilitate the development of an evidence‐ and personalized follow‐up program for OSCC, we investigated the course of time until the second and subsequent events and studied the risk factors related to these events. Materials and methods We retrospectively studied 594 OSCC patients treated with curative intent at the Head and Neck Cancer Unit of the Radboud University Medical Centre from 2000 to 2012. Risk of recurrence was calculated addressing death from intercurrent diseases as competing event. Results The 1‐, 5‐ and 10‐year cumulative risks of a second event were 17% (95% CI:14%;20%), 30% (95% CI:26%;33%), and 37% (95% CI:32%;41%). Almost all locoregional recurrences occurred in the first 2 years after treatment. The incidence of second primary tumors was relatively stable over the years. The time pattern of presentation of third events was similar. Discussion Our findings support a follow‐up time of 2 years after curative treatment for OSCC. Based on the risk of recurrence there is no indication for a different follow‐up protocol after first and second events. After 2 years, follow‐up should be tailored to the individual needs of patients for supportive care, and monitoring of late side‐effects of treatment., There is no rationale for a follow‐up of 5 years after treatment for oral cancer, as the great majority of recurrences occurs in the first 2 years and because the risk of second primary tumors is constant. Patients should receive a core follow‐up of 2 years which can be extended based on an individual patients needs.

Internet counseling can be a valuable resource for people who cannot seek mental health care due to various reasons. The aim of this study was to analyze the time patterns of first-time contacts ma...

We would like to thank to A. Bueno for all the support and useful discussions during the development of this work. The authors thank also for the financial support by OE Portugal, FCT, I. P., under project PTDC/FIS-PAR/29158/2017. R. C. is grateful for the financial support by OE-Portugal, FCT, I. P., under DL57/2016/cP1330/cT0002. B.S.G. is grateful for the financial support by Grant LIP/BI-14/2020, under project IC&DT, POCI-01-0145FEDER-029158., The muon tagging is an essential tool to distinguish between gamma and hadron-induced showers in wide field-of-view gamma-ray observatories. In this work, it is shown that an efficient muon tagging (and counting) can be achieved using a water Cherenkov detector with a reduced water volume and 4 PMTs, provided that the PMT signal spatial and time patterns are interpreted by an analysis based on machine learning (ML). The developed analysis has been tested for different shower and array configurations. The output of the ML analysis, the probability of having a muon in the WCD station, has been used to notably discriminate between gamma and hadron induced showers with S/ √ B ∼ 4 for shower with energies E0 ∼ 1 TeV. Finally, for proton-induced showers, an estimator of the number of muons was built by means of the sum of the probabilities of having a muon in the stations. Resolutions about 20% and a negligible bias are obtained for vertical showers with Nμ > 10., OE Portugal, FCT, I. P. PTDC/FIS-PAR/29158/2017 DL57/2016/cP1330/cT0002, ICDT LIP/BI-14/2020 POCI-01-0145FEDER-029158

Using intraday 2015-2019 short sale data from CBOE and FINRA, we examine the intraday time patterns and information content of on-exchange and off-exchange shorting. Midday short sales and those near the open strongly and negatively predict the cross-section of stock returns at daily horizons and up to 12 weeks ahead. Short sales near the close are only informative at next-day horizons. We also connect earnings/analyst news to shorting flows. Shorting near the open reacts strongly to and anticipates bad-news releases. Shorting near the close only anticipates post-close firm news. Our evidence supports both Kyle (1985) and Holden and Subrahmanyam (1992).

This is the first of four chapters that explain and apply the dynamic simulation approach to health risk assessment modeling introduced in Chap. 2. The exposition in this chapter is motivated by an observation made by toxicologist Julie Goodman of Gradient, who coauthored the article on which this chapter is based (Cox Jr et al. 2020): most of the key ideas of the dynamic simulation approach can be explained through relatively simple diagrams, without going through the underlying equations. This chapter undertakes such a high-level diagrammatic exposition. It returns to two of the diagrams used in Chap. 2 to introduce simulation modeling, and adds further discussion and diagrams to help understand and visualize the dynamic responses of internal doses to different time patterns of exposure. Chapters 4, 5, and 6 and their appendices then cover the same material in much greater depth, providing the underlying systems of equations used to model biological responses to exposures to inhaled respirable crystalline silica (Chap. 4) and asbestos (Chap. 5) and highlighting the importance of nonlinearities in these responses for risk assessment and risk management (Chap. 6).

In the electricity market environment, an efficient and accurate load forecasting model plays a vital role in the operation and dispatch of the power grid system. However, the deep learning method represented by the recurrent neural network is difficult to capture the effective features of mixed time pattern sequences, and there is a problem of important information loss when the sequence is too long. To solve this problem, we propose a short-term load forecasting model of TCN (temporal convolutional network)-GRU (gated recurrent unit) based on the sparse attention mechanism. This model utilizes the sparse attention GRU network to capture the node features of different time patterns and highlight their importance and then uses TCN's causal dilated convolution operations to extract long-term temporal features of the sequence. Finally, the proposed model integrates two captured feature information to complete the load forecast. Taking the public data set of a certain area in Australia and the load data of a certain area in Shanghai, China as examples, we compare this model with the typical model respectively. The results show that the proposed model has higher prediction accuracy and model robustness.

Introduction: Several studies identified temporal variations in stroke care and suggested that quality of care declines during off-hours and on weekends. Methods: We specified 2 time definitions: a) 8-hour blocks: night (midnight – 7:59), day (8:00 – 15:59), evening (16:00-23:59); b) weekday vs. weekend. We compared process measures and outcomes of the EVT-treated DEFUSE 3 patients based on these definitions. To assign patients to time-blocks, we used date and time of admission to hospital that performed EVT. Results: 92 patients were randomized to EVT treatment: 30% arrived to the treating hospital at night, 49% at day, 21% at evening. Mean age by arrival time 71±14, 70±12, 63±15 (p=0.09); NIHSS 17±5, 15±6, 15±8 (p=0.40); female 39%, 51%, 63% (p=0.27). Weekend admission occurred in 21%. Weekday vs weekend mean age 68±14 vs 72±11 (p=0.19); female 53% vs 37% (p=0.20), higher weekend NIHSS 15±6 vs 18±6 (p=0.04). Onset to arrival at the EVT center varied by time of day: (hrs:mins) 7:04±2:43 night, 8:05±3:01 day, 4:51±2:30 evening, p Conclusions: DEFUSE 3 patients admitted during the day had the longest time from last known well to arrival at the study site due to the high percentage of wake-up strokes admitted during this time period, however, these patients had the shortest arrival to groin puncture times. Although mortality rates were higher for patients who presented on weekends, this may be explained by the fact that these patients were older and had higher NIHSS.

Objective: To investigate whether patients with an acute heart failure (AHF) episode triggered by infection present different outcomes compared to patients with no trigger and the effects of early antibiotic administration (EAA) and hospitalisation. Methods: Two groups were made according to the AHF trigger: infection (G1) or none identified (G2). The primary outcome was 13-week (91-days) all-cause mortality, and secondary outcomes were 13-week post-discharge mortality, readmission or combined endpoint. Comparisons are presented as unadjusted and adjusted (MEESSI risk score) hazard ratios (uHR/aHR) for G1 compared to G2 patients, also estimated by weeks. Stratified analysis by EAA (provided/not provided) and patient disposition (discharged/hospitalised) was performed. Results: We included 6727 patients (G1 = 3973; G2 = 2754). The 13-week mortality uHR was 1.11 (0.99-1.25; p = 0.06; with significant increases in the first 3 weeks), and the aHR was 0.91 (0.81-1.02; p = 0.11). There were no differences in unadjusted secondary post-discharge outcomes; however, G1 outcomes significantly improved after adjustment: aHR 0.83 (0.71-0.96; p = 0.01) for mortality, 0.92 (0.84-0.99; p = 0.04) for readmission, and 0.92 (0.85-0.99; p = 0.04) for the combined endpoint. We found a differentiated effect of hospitalisation (p < 0.05 for interaction; better post-discharge readmission and combined outcomes in G1), and a trend (p = 0.06) to lower mortality in G1 patients with EAA. Additionally, there were some differences between groups in baseline and acute episode characteristics. Conclusion: AHF triggered by infection is not associated with a higher mid-term mortality and has better post-discharge outcomes; however, the first 3 weeks are an extremely vulnerable period. Since hospitalisation could have a role in limiting adverse post-discharge events, and EAA in reducing mortality, these relationships should be prospectively explored in further studies.

The occurrence of births of children with orofacial clefts in Slovenia during the forty-year period 1973-2012 was recorded daily. Days with one birth with cleft, with much less frequent two, and with exceptionally rare three births with clefts were recorded by date. Incidence was calculated as the ratio of number of clefts per thousand live births in a time period. Numbers of live births, recorded monthly, were accessed on the web site of the Statistical Office of Republic of Slovenia. The purpose of the article was the investigation of the time pattern of births with clefts, in particular the presence of an assumed Poisson process. The data made statistical analysis on several levels of aggregation (daily, quarterly, yearly) possible. However, the approaches on different aggregation levels had to be adapted, partly due to the changing birth rate. Overwhelming majority of results is compatible with the assumed Poisson process hypothesis. An additional purpose was testing the suspected time periodicity of the cleft incidence. A non-traditional approach using the Siegel's test was applied. No periodic frequency could be confirmed at the 0,05-significance level.

A formal model of system-wide equilibrium is constructed where regulatory policy backs exchange by means of synallagmatic contracts. The model economy comprises three explicit sectors (business sector, household sector and state sector) and is engaged in three basic economic activities (production, exchange and consumption). Three basic time patterns are possible for exchange contracts (spot contracts, financial contracts and forward contracts; in total referred to as inner exchange contracts).

Urban growth originates multiscale spatial patterns, such as those of transportation networks. Here, the public transportation network (PTN) of the city of Lisbon is analysed from 1901 to 2015, employing several mathematical tools. In a first stage, the fractal dimension and the fractional entropy are used to quantify the evolution of the structure of the PTN in space and time. In a second stage, the PTN is analysed adopting additional information, namely considering different levels of the network based on transportation schedule and passenger capacity, and studying the significance of the distance between stops. Both the fractal dimension and the fractional entropy reveal time patterns compatible with known historical events, showing them to be appropriate for quantifying the growth of the PTN. When the routes’ schedules are used to stratify the PTN, not only the fractal behaviour is observed at different levels, but also the evolution of the network in respect to the homogenization of the capacity of different routes. Finally, when the distance between consecutive stops is analysed, a power law behaviour is revealed, as expected from the fractal geometry of the network. This result is then confirmed using the ht-index.

Background Numerous studies have identified various risk factors for a poor health-related quality of life (HRQOL) after severe trauma. The relative importance of the time elapsed after injury, however, is unknown and results of clinical studies have been conflicting. Methods A cross-sectional study was performed in two trauma centres using data from the German TraumaRegister DGU®, which contained prospectively collected information on the type and severity of the injury, on critical care, and on outcome. To evaluate HRQOL in patients surviving more than 500 days after the injury, we used a self-rating instrument, the EQ-5D which contains a visual analogue scale (EQ-VAS), and which allows the calculation of a global outcome indicator, the EQ-D5 index value. Complex statistical models were used to evaluate independent associations between the time elapsed after injury and a poor HRQOL. Results Of 380 contacted patients, follow-up assessments could be obtained in 168 patients (44.2%) 3.6 ± 1.6 (SD) years after the injury. There was a linear association between the time elapsed after the injury and the% of contacted patients not participating in the study (p = 0.013). In participating subjects, average EQ-5D index value was 0.599 ± 0.299, and average EQ-VAS rating 67.8 ± 22.0. A very poor quality of life (EQ-5D index value Conclusions There is an independent, U-shaped association between the frequency of extreme values of HRQOL and the time elapsed after injury. Time patterns of HRQOL may be sensitive to increasing rates of attrition since patients with a good outcome are less likely to respond to questionnaires. Time from injury should be incorporated into all future cross sectional studies trying to identify predictors of HRQOL.

Remodeling of pulmonary resistance arteries in rats due to 4-day hypoxia could be successfully suppressed by sodium cromoglycate. In this study, we tested the difference in the suppression between two distinct time patterns of cromoglycate administration during 21-day hypoxia. In the experiment, we focused on some details in both smooth muscle cells and extracellular matrix of pulmonary arterial walls.During 21-day hypoxia, rats were treated with sodium cromoglycate either in the first four days or in the last four days. The first four days were chosen to test efficiency of an initial pulse of cromoglycate to suppress pulmonary vascular remodeling. The last four-day administration tested possibility to block remodeling post hoc.Initial pulse reduced and modified remodeling in all levels of pulmonary arteries, which comprises neomuscularization of prealveolar arteries, asymmetrical hypertrophy of tunica media in muscular pulmonary arteries and hypertrophy of tunica media and tunica adventitia in large conduit arteries. Terminal pulse had only negligible effect.Only the initial cromoglycate therapy led to significant morphological suppression of remodeling. We therefore assume important role of initial remodeling influencing during long time hypoxia experiment.

Disease relapse occurs in ~30% of children with medulloblastoma, and is fatal in the majority. We sought to establish whether clinico-molecular characteristics at diagnosis are associated with the nature of relapse, subsequent disease-course, and whether these associations could inform clinical management. We surveyed the clinical features of medulloblastoma relapse (time-to-relapse, pattern-of-relapse, time-to-death and overall outcome) in 247 centrally-reviewed patients who relapsed following standard-upfront-therapies. We related these to clinico-molecular features at diagnosis, prognostic factors, and first-line/relapse treatment. Patients who received upfront craniospinal irradiation (CSI-treated) displayed prolonged time-to-relapse compared to CSI naïve patients (p

Objectives Low-back pain (LBP) is a substantial health challenge due to the risk for long-term sickness absence and early retirement. Several biomechanical exposures at work, including sitting, have been suggested to increase the risk for LBP. The objectives of this study were to determine (i) the extent to which temporal patterns and total amount of objectively measured sitting is associated with LBP intensity and (ii) whether selected modifiers influence these associations. Methods This cross sectional study uses baseline data from the Danish PHysical ACTivity cohort with Objective measurements (DPhacto) of physical activities in the cleaning, transport and manufacturing sectors. Peak intensity of LBP was collected by questionnaire on a 0–10 scale and sitting was expressed in terms of total duration and temporal pattern, ie, time spent in brief bursts (≤5 minutes), moderate periods (>5–≤20 minutes), and prolonged periods of sitting (>20 minutes); both during work and whole day (waking hours only). Associations were determined using linear regression in models accounting for moderation and confounding. Factors evaluated as moderators or confounders were assessed by questionnaire. Results The population consisted of 704 participants. No significant associations were found between total duration or temporal patterns of sitting and LBP intensity, neither during work nor for the whole day. Body mass index (BMI) significantly moderated the association between sitting and LBP; participants with a high and low BMI showing a negative and positive association, respectively. Conclusion Sitting was not independently associated with peak LBP intensity, suggesting other exposures are more powerful risk factors for LBP.

Accurate estimations of the stochastic natures of energy demand for air-conditioner (A/C) use, which are affected by the diverse occupant behaviour, are needed, for the design and operation of residential cogeneration systems and distributed generation systems coupled with renewable energy sources and supply-demand management technologies. However past studies have mainly focused on developed countries, and knowledge of tropical regions, including many emerging countries with large populations, remains limited. We conducted field measurements of occupants’ A/C usage behaviour in 38 dwellings in Kuala Lumpur, Malaysia. Measured data were considered as a function of start and end times, duration, and frequency of A/C usage in each dwelling. Analysis showed that A/C events were rare during daytime; however, there was a drastic increase in the frequency of A/C usage at night. Based on this, a simple algorithm to synthesize stochastic time patterns of A/C operation schedules was developed. The validity of the model was demonstrated through comparison with observational data.

Building on experiences collected in the course of an evaluation of a German cluster policy programme, the Leading-Edge Cluster Competition (LECC, evaluation 2008–2014), this paper scrutinizes central problems that arise in the evaluation of the impacts of large-scale innovation policy programmes. We find that our relatively modest knowledge with regard to the actual effects and impact patterns of comparable programmes is not necessarily due to methodological weaknesses of the evaluation studies, but rather to inherent structural programme characteristics. The present state-of-the-art evaluation methodology does not sufficiently allow us to take into consideration these characteristics. Challenges in the evaluation of technology programs relate closely to different facets of complexity. Our analysis shows that three aspects of programme effects deserve more attention in evaluation research: Emergence and non-linearity, uncertainty, and time patterns of the observed effects. Using the example of the LECC, our paper demonstrates how evaluators’ work is affected by these phenomena. The results lead to the question of whether there are methodological alternatives that are suitable for future evaluations of complex innovation programmes.

Stroke is one of leading causes of death worldwide. Different frequency of stroke occurence is observed in days of the week and months in the year, and incidence of stroke has irregular time pattern. We analyzed 516 patients who had acute stroke and were treated in Clinic of Neurology, Clinical Center Kragujevac from January 1, 2013 to January 1, 2014, mean age 72,11±11,52. Statistical analysis is conducted out using the SPSS software version 20.0. We used descriptive statistic, student T-test, chi-square or Fisher exact test. Friday is day we found the most IS and all stroke types occurences, and Wednesday is day we found the most IS in men. We found the most strokes in women younger than 65 years on Wednesday, but in women older than 65 years on Friday. Monday is day with the most admissions to hospital for patients with IS, and we observed that there is average delay in the refering to the doctor for 1.80±1.44 days. Friday is the day with the most ICH symptom beginings and the most admissions to the hospital, and Saturday is the day with the least symptom beginings and admissions to the hospital in the case of IS and ICH. The most IS occured in winter (in Decembar), and the least in summer (in August). The most ICH occured in May, and the least in July and October. We confirmed that there is a significant weekly variability in the IS symptom onset day.

This paper studies payment variation across locations and time using five years of transactions data from a large discount retail chain with hundreds of stores across the Fifth District. The results show that the median transaction size, demographics, education levels, and state fixed effects are the top factors in explaining cross-location payment variation in the sample. We also identify interesting time patterns of payment variation, particularly the longer-term decline in the cash share of transactions largely replaced by debit.

Background: Seasonality in suicide has been investigated from the early 19th century to explore the productive environmental variables. Seasonality studies can provide information on prevention and interventions in suicide. In this study, we examined seasonality in suicide and aimed to explore the differences in seasonality between rural and urban areas, mental disorders, and genders. Methods: In this cross-sectional study, overall identified suicide cases in Ilam province from 21 March 2010 and 11 December 2014 were identified, using systematic registration suicide data (SRSD). Two methods were used separately to analyze seasonality (Chisquare, Edwards' T). Seasonal effect (peak/ trough seasons) and (deaths/ attempts suicide) was explored by ratio statistics. The null hypothesis was that the completed suicides in each method group were evenly distributed over a year. Results: Significant seasonality was observed in suicide during the study period, with one peak in the spring and one in the winter. Our results showed that suicide seasonality following mental disorders was statistically significant with a peak in the spring, regardless of other factors such as gender and age. When all non- mental suicides are taken into account, the seasonality remains statistically significant, but the peak season is shifted to autumn. Conclusion: Investigating suicide in Ilam revealed a significant seasonality for both rural and urban areas, which was greater in the urban part. A significant seasonality in suicide was observed in attempters with mental disorders. In suicide attempters with mental disorders, findings showed two peaks in the spring and the autumn.

The concept of demand-side management (DSM) was invented in the late 1970s along with the development of many of the frameworks in use to plan and implement it in the years immediately following. It was originally referred to as demand-side load management. It is generally defined as the planning and implementation of those activities designed to influence consumer use of electricity in ways that will result in changes in the utility's load shape—i.e., changes in the time pattern and magnitude of a utility's load. This paper describes the evolution it has undergone since its invention and some likely changes ahead. DSM largely originated in the U.S., but is practiced in various forms through the world today. This paper uses U.S. data as examples.

Background The aim of this study was to detail the time profile and frequency distribution of mortality following an emergency admission and to compare these for weekday and weekend admissions. Methods We profiled in-hospital deaths following emergency medical admission between 2002 and 2014. We determined the frequency distribution, time pattern, causality and influence of day of admission on mortality out to 120 days. We utilized a multivariable regression model (logistic for in-hospital mortality and truncated Poisson for count data) to adjust for major predictor variables. Results There were 82,368 admissions in 44,628 patients with 4587 in-hospital deaths. The 30-day in-hospital mortality declined from 8.2% in 2002 to 3.7% in 2014. The mortality pattern showed an exponential decay over time; the time to death was best described by the three-parameter Weibull model. The calculated time to death for the 5th, 10th, 25th, 50th, 75th, and 90th centiles were 0.5, 1.2, 3.8, 11.1, 26.3 and 49.3 days. Acute Illness Severity Score, Chronic Disabling Disease Score, Charlson Co-Morbidity Index and Sepsis status were associated with mortality. The risk of death was initially high, lower by day 3, and showed a cumulative increase over time. The mortality pattern was very similar between a weekday or weekend admission; however, the risk of death was greater at all time points between 0 and 120 days for patients admitted at a weekend OR 1.08 (95% CI 1.01–1.15). Conclusion We have demonstrated the pattern of mortality following an emergency admission. The underlying pattern is similar between weekday and weekend admissions.

Control of prosthetic hands is still an open problem, currently, commercial prostheses use direct myoelectric control for this purpose. However, as mechanical design advances, more dexterous prostheses with more degrees of freedom (DOF) are created, then a more precise control is required. State of the art has focused in the use of pattern recognition as a control strategy with promising results. Studies have shown similar results to classic control strategies with the advantage of being more intuitive for the user. Many works have tried to find the algorithms that best follows the user’s intention. However, deployment of these algorithms for real-time classification in a prosthesis has not been widely explored. This paper addresses this problem by deploying and testing in real-time an Artificial Neural Network (ANN). The ANN was trained to classify three different motions: no grasp, precision grasp and power grasp in order to control a two DOF trans-radial prosthetic hand with electromyographic signals acquired from two channels. Static and dynamic tests were made to evaluate the ANN under those conditions, 95% and 81% accuracy scores were reached respectively. Our work shows the potential of pattern recognition algorithms to be deployed in microcontrollers that can fit inside myoelectric prostheses.

This study aims at combining time and quantity of carbohydrate (CH) intake in the definition of eating patterns in UK adults and investigating the association of the derived patterns with type 2 diabetes (T2D). The National Diet and Nutrition Survey (NDNS) Rolling Program included 6155 adults in the UK. Time of the day was categorized into 7 pre-defined time slots: 6&ndash, 9 am, 9&ndash, 12 noon, 12&ndash, 2 pm, 2&ndash, 5 pm, 5&ndash, 8 pm, 8&ndash, 10 pm, and 10 pm&ndash, 6 am. Responses for CH intake were categorized into: no energy intake, CH &lt, 50% or &ge, 50% of total energy. Non-parametric multilevel latent class analysis (MLCA) was applied to identify eating patterns of CH consumption across day-time, as a novel method accounting for the repeated measurements of intake over 3&ndash, 4 days nested within individuals. Survey-designed multivariable regression was used to assess the associations of CH eating patterns with T2D. Three CH eating day patterns (low, high CH percentage and frequent CH intake day) emerged from 24,483 observation days, based on which three classes of CH eaters were identified and characterized as: low (28.1%), moderate (28.8%) and high (43.1%) CH eaters. On average, low-CH eaters consumed the highest amount of total energy intake (7985.8 kJ) and had higher percentages of energy contributed by fat and alcohol, especially after 8 pm. Moderate-CH eaters consumed the lowest amount of total energy (7341.8 kJ) while they tended to have their meals later in the day. High-CH eaters consumed most of their carbohydrates and energy earlier in the day and within the time slots of 6&ndash, 9 am, 12&ndash, 2 pm and 5&ndash, 8 pm, which correspond to traditional mealtimes. The high-CH eaters profile had the highest daily intake of CH and fiber and the lowest intake of protein and fat. Low-CH eaters had greater odds than high-CH eaters of having T2D in self-reported but not in previously undiagnosed diabetics. Further research using prospective longitudinal studies is warranted to ascertain the direction of causality in the association of CH patterns with type 2 diabetes.

DHCP is widely used to dynamically allocate IP addresses to the devices on local area networks, but the explosive increases of WiFi devices and their frequent mobility pose great challenges on DHCP performance in wireless LANs. In this paper, by analyzing large scale real network traces, we observe that the dynamic WiFi user behavior (e.g., online time pattern and spatio-temporal mobility pattern) leads to the poor DHCP performance. The IP pools in some VLANs have been exhausted in rush hours although the total IP utilization in WLAN is only 24%. Therefore, we have to configure IP lease times and IP pools dynamically and make sure that they are adaptive to the WiFi user behavior. In order to achieve this goal, we characterize and model the user behavior across online time pattern and spatiotemporal mobility pattern. Then we propose BDAC, a behaviour-aware dynamic adaptive configuration, which is combined of two strategies: adaptive IP lease time configuration and dynamic IP pool configuration. The former is to set adaptive lease times across user roles and area types based on online time pattern to reclaim IP addresses in time and reduce the peak IP usage, while the latter dynamically migrates the IP addresses across VLANs based on spatio-temporal mobility correlation to save the IP addresses. Using the real network traces of a different week, we conduct experiments to evaluate the performance of BDAC. Results show that BDAC can save up to 60% of IP addresses and the actual IP utilization rises from 24% to 59%. Furthermore, BDAC maintains high IP utilization when the number of VLANs in a WLAN increases.

A high coupling coordination degree of urban land use efficiency promotes sustainable regional economic development. In this study, land use efficiency coupling coordination degrees were calculated for 36 mining cities of western China, with a focus on economic, social, and ecological benefits for land use efficiency. Four years (2000, 2005, 2010, and 2015) of data were selected. A land use efficiency index system was generated and the improved entropy method was used to calculate the index weights of land use efficiency for each year. The spatial distributions of the coupling coordination degree were assessed by the ArcGIS spatial analysis tool. Spatial correlation analysis was conducted for the coupling coordination degree. The following conclusions could be drawn: (1) According to the composite index results, urban land use efficiency could be divided into three stages and showed several different time patterns in mining cities of western China, (2) analysis of the spatial and temporal distributions of the land use efficiency coupling coordination degree identified a low level of coupling coordination and reluctant coupling coordination. An obvious core-periphery and gradual trickle-down trend was observed, (3) the land use efficiency of western mining cities presents negative and positive spatial autocorrelation characteristics. Shizuishan city, Ordos city, Jinchang city, and Wuhai city have significant aggregation types. Therefore, the western mining cities were subjected to different complex time and space characteristics.

Understanding processes that lead people to invest a certain amount of time in challenging tasks is important for theory and practice. In particular, researchers often assume strong linear associations between confidence, consensuality (the degree to which an answer is independently given by multiple participants), and response time. The Diminishing Criterion Model (DCM; Ackerman, 2014) is a metacognitive model which explains the stopping rules people employ under uncertainty in terms of the confidence-time association. This model is unique in predicting a curvilinear rather than a linear confidence-time association. Using consensuality as an alternative to confidence for predicting response time offers theoretical and practical opportunities. In four experiments, including replications and variations, we examined confidence (where collected) and consensuality as predictors of the time people invest in three problem-solving tasks and in real-life web searching. The results using consensuality, like those for confidence, fitted the curvilinear time pattern predicted by the DCM, with one exception: at least 30% of the population must endorse a potential answer for consensuality to predict response time based on the stopping rules in the DCM. Beyond examining consensuality as a predictor, the study brings converging evidence supporting the DCM's curvilinear confidence-time association over alternative models. The methodology used for analyzing web searching offers new directions for metacognitive research in naturally-performed tasks.

Parkinson’s disease (PD) is the fastest growing neurological disorder worldwide. PD has a huge impact on the patients quality life due to motor alterations and behavioral changes. The advancements in low-cost RGB-D cameras, such as MS Kinect®, generates the possibility to use low-cost devices to obtain motion data, and perform common PD test like gait analysis. In this research project, we explore the use of LSTM and one-dimensional convolutional neural network as a complement for clinical PD diagnose, this could be used to help the doctors and specialist in the complex process of objective PD diagnosis. For this, we automatically extracted features and time patterns of these signals, then we performed some deep learning models and as the main result, Conv LSTM model achieved an 83% prediction accuracy, an 83.5% precision, and 83.4% recall, being able to differentiate between PD and Non-PD gait samples.

Hand gesture recognition has many applications in engineering and medical fields. This paper proposes a real-time hand gesture recognition method using the surface electromyographic (sEMG) signal on the forearm. we apply a sliding window which allow us to observe a segment of the signals. Features are extracted from the signals of each sliding window, and then are inputted into a feed-forward artificial neural network (ANN) classifier which is trained at first. When the number of one hand gesture type of identified features reaches the threshold, it would be considered that the hand gesture is identified. Experiments show that the classification accuracy of real-time systems reaches 96%, and hand gestures can be recognized before they are completed.

The use of big data in transportation research is increasing and this leads to new approaches in modeling the traffic flow, especially for what concerns metropolitan areas. An open and interesting research issue is city-wide traffic representation, correlating both spatial and time patterns and using them to predict the traffic flow through the whole urban network. In this paper we present a machine learning based methodology to model traffic flow in metropolitan areas with the final aim to address short-term traffic forecasting at various time horizons. Specifically, we introduce an ad-hoc neural network model (GBNN, Graph Based Neural Network) that mirrors the topology of the urban graph: neurons corresponds to intersections, connections to roads, and signals to traffic flow. Furthermore, we enrich each neuron with a memory buffer and a recurrent self loop, to model congestion and allow each neuron to base its prediction on previous local data. We created a GBNN model for a major Italian city and fed it one year worth of fine-grained real data. Experimental results demonstrate the effectiveness of the proposed methodology in performing accurate lookahead predictions, obtaining 3% and 16% MAAPE error for 5 min and 1 h forecasting respectively.

“Unstable Network” is one of the most important features of delay tolerant networks (DTNs), where most of services or data dissemination are processed in a mobile environment. Geographic information, therefore, is an important factor needed to be carefully analyzed to overcome this “unstable” environment. In this chapter, how to use geographic information to improve data dissemination in DTNs is presented and two DTN applications based on geographic information are illustrated. The first one is vehicle based DTNs, where the vehicle is a carrier to disseminate data. The second one is human associated DTN, where the human is the carrier.

Available online 12 December 2018 This paper analyses installation entries and exits in the EU ETS, over 2005–2013. Patterns of entries and exits are identified across countries, sectors, and time. The limitations of the EUTL as a data source for research purposes mean that only genuine exits (reflecting production capacity reduction), and not genuine entries (reflecting production capacity increases), can be systematically identified. Exits are found to be relatively frequent events, more so in manufacturing sectors with small average installation size. Moreover, exits were concentrated in 2007 and in 2012, the final years of Phase I and Phase II. We investigate whether the perverse incentives of closure provisions, in free allocation, explain such time pattern. A discrete-time hazard model for the exit event is estimated using a three-tier dataset combining installation-, firm-, and macro-level information. The results indicate that, most likely, closure provisions delayed installation exits, especially in Phase II. Published version of EUI RSCAS Working Paper 2016/19

Chronic pain patients constitute 65% of those ages 65 and older in the US. Many affected older adults are challenged to manage physical and psychological consequences tied to the intensity, interference, and temporal pattern of their pain. However, little quantitative research highlights the psychological impact of constant versus intermittent or ever-present-yet-variable pain, even though temporal pain pattern may have meaningful predictive power for wellbeing and future time perspective (FTP). A positive and expansive view of the future is particularly adaptive for this population because it is positively associated with treatment adherence. In this study, we analyzed secondary data to determine whether pain temporal pattern and pain duration are associated with differences in participant scores on Carstensen & Lang’s Future Time Perspective scale. All participants (N=142) were 45 years old and older with non-cancer chronic pain lasting three months or more. There was no significant association between pain time pattern and FTP (p=.35). Additionally, controlling for pain duration, average FTP scores did not vary significantly as a function of time pattern (p=.07). Our analyses demonstrated no significant relationship between pain time pattern and FTP and no significant moderating effect of pain duration. However, in contrast to the previous literature, FTP was not significantly associated with age and negatively (rather than positively) associated with subjective health (r=-.08, p=.35; r=-.24, p

The daily shopping, so activities that aim at the acquisition of mainly household-related goods, food and services, is a constituent element of modern consumer society. In addition to the monetary aspect of the extraction of goods and services from the market, the temporal aspect weighs in as opportunity costs for shopping activities, . Against the background of a postulated social change in recent decades that has led to an increase in the daily pace of life, the question is whether and how these accelerating changes have also transformed the time patterns of everyday shopping, such as shopping frequency and shopping time. To investigate this question, data of the time use surveys of the Federal Statistical Office from 1991/92, 2001/02 and 2012/13 is analyzed. The results suggest that both the average shopping frequency as well as the average shopping duration has increased during that period of time. It is discussed how these results are consistent with the hypothesis of an extensive social acceleration.

Objective To describe the current situation of animal bites in the Babol County, North of Iran. Methods This was a cross-sectional study based on recently collected data of 3 798 victims bitten (656 females and 3 142 males) from 2010 to 2014 in the Health Center of Babol, Iran. The interest variables in the study included demographic variables, characteristics of animal, some of the time patterns, and some clinical patterns provided to victims. Results The average age of victims was (33.68 ± 17.23) years. The age group with the max proportion (for males, 32.1%; for females, 26.2%) of bites occurred in 18–30 years old group for males and 30–45 years for females. The ratio of male victims to female ones was 4.78. In terms of place of incident, 2 502 (65.9%) cases of animal bites occurred in rural areas. Dogs and cats were the most dominant biters with 3 340 (87.9%) and 395 (10.4%) bites, respectively. For the kinds of biters, 3 643 (95.9%) were pets, 133 (3.5%) were strays and 22 (0.6%) were wild animals. Most of the lesions were on shoulder as well as upper organs (46.9%) and lower organs (41.0%), respectively. Conclusions Since the average age of the subjects with injuries on the head and upper organs was lower than that of victims with other organs injured and since that pet dogs were the major biter, structured monitoring programs that focus on specified target groups in collaboration with other organizations are essential to control the animal bites.

Technological evolution, heading for industry 4.0, makes companies tend to automate their management and operation, ideally defining it through business process models. To describe policies or rules related to the execution order of the activities in an organization, Declarative Business Process Models permit a relaxed description of activity order, which needs monitoring to detect non-conforming behaviors. Commonly, the detection of a violation implies that the malfunction has already occurred, being better to avoid the violation in advance. To predict future violations, prognosis is required. To allow the modeling of real business behavior, an extension of declarative business process models including both time patterns and multiple instances is proposed. This new model can be used to prognosticate if current process instances may violate a defined model in the future, according to the analysis of the robustness of the process instances evolution. The proposed Model-Based Prognosis is based on analyzing the event traces that represent the current instances and propagate their possible progression through the Constraint Programming paradigm. To ascertain if the model could be violated, it is analyzed how its robustness can tackle unexpected behaviors. To complete the formalization and modeling, an implementation applied to a real medical example is included in the paper. The prognosis of concurrent instances is addressed, dealing with formalized time and activity patterns even considering the resource availability, and getting acceptable execution times. The automatic verification and prognosis of declarative business processes are addressed considering concurrency and synchronization of multiple instances, performing well in terms of execution time.

Background:During the last decennium advanced imaging modalities have refined our understanding of the tissues involved in RA and have shown that not only joints but also bones and tendons can be inflamed at diagnosis. However, the time-order of decrease of these inflammatory features after initiation of DMARDs is unknown. Whether this differs for ACPA-positive and ACPA-negative patients is also unknown.Objectives:To achieve better understanding of the time order in which the different inflamed tissues (joint, tendon, bone) respond to DMARD-treatment and whether this differs between ACPA-subgroups.Methods:216 consecutive patients with early undifferentiated or rheumatoid arthritis, who received DMARD-treatment, were studied. Unilateral 1.5 Tesla contrast-enhanced MRIs of MCPs, wrists and MTPs were performed at baseline (before treatment) and after 4, 12 and 24 months. MRIs were scored for synovitis, osteitis and tenosynovitis in line with the RAMRIS, in known time-order but blinded for clinical data. Data of 4 serial time-points (three time intervals) were studied with autoregressive cross-lagged models. These models evaluated the influence of two time patterns in one model: 1) a simultaneous pattern (“extra change in one inflammatory feature was associated with extra change in another feature”) and 2) a subsequent pattern (“change in one inflammatory feature preceded change in another feature”). All analyses were repeated stratified for ACPA-status (anti-CCP2).Results:In all patients, all combinations of inflammatory features showed significant simultaneous decrease in all time intervals (0 – 4 /4 – 12/12 – 24 months; all pWhen considering ACPA-negative and ACPA-positive patients separately, similar results were obtained. In addition, in ACPA-positive patients, synovitis change between 4 - 12 months preceded osteitis change at 12 – 24 months (p = 0.002); this was significantly different from ACPA-negative patients (pConclusion:This study increased the understanding of the response to treatment on tissue level. In addition to simultaneous decrease of synovitis, osteitis and tenosynovitis, also time orders of inflammation decrease were identified. These differed between ACPA-subgroups, implying a different interaction of synovium and bone in these patients.Disclosure of Interests:None declared

Background: Unintentional injuries are one of the major causes of death in Iranian children. Information on epidemiological pattern of injury among one-to 5-year-old children is limited in Hamadan. The aim of this study was to clarify the person, space and time pattern of injury among 1–5-year-old children in Hamadan Province. Methods: All registered incidence cases of injury among 1–5 year-old children in Hamadan Province from March 2009 to March 2015 were included in this cross-sectional study. We analyzed the data on county, gender, age category, type of injury, season and outcome of injury. Temporal trend was explored using time series regression with accounting autocorrelation, seasonality, and short-term variation. Results: This study included 4523 injury cases. During the studied period, urban residents and boys had a higher number of injuries. Motor vehicle-related injuries were the most common type of injury. A seasonality pattern was found so that most of the cases were occurred in summer months. The lowest and highest incidence rate ratios (IRRs) were occurred in January 2011 (IRR = 0.61 with 95% confidence interval [CI]: 0.31, 1.18) and May 2014 and August 2013 (IRR = 6.78 with 95% CI: 4.38, 10.51), respectively. Conclusion: In Hamadan Province, childhood injury has a variation in person, place, and time pattern, as some groups such as boys and urban residents among 1–5 year-old children are at a higher risk for the incidence of injury. Therefore, it is recommended that health service managers and health policymakers devote more healthcare and resources to the high-risk groups.

Background: At workplaces, the workers exposed to several harmful agents such as physical, chemical, and biological pollutant that cause occupational diseases. There are a lot of jobs that not allow a certain pattern of exposure to this agent. In this article, we introduce a technology named radio-frequency identification (RFID) to estimate the exposure time of workers to harmful agent. Materials and Methods: This applied study was carried out experimentally in an industry in Isfahan province, Iran. Twenty-nine participants selected from the workers without a fixed pattern of exposure. Two methods used to measure the exposure time of them. The first method was based on a self-made RFID device and conducted by the workers. The second method performed by stopwatch, which was carried out by the occupational hygienist. The results were analyzed using SPSS 20 and descriptive statistics, Spearman correlation coefficient, and paired samples t-test. Results: The mean age of the participants was 36.48 ± 5.889 and job experience was 9.06 ± 6.316 years. Spearman correlation coefficient shows that there is a significant correlation between the exposure times measured by the workers and occupational hygienist (R in all zones was higher than 0.9, P < 0.05). Paired samples t-test shows that there are no significant differences between the mean exposure times measured by the workers and occupational hygienist in each zone and in all the zones (P > 0.05). Conclusion: RFID technology is an appropriate method to evaluate the exposure time of workers without fixed pattern of exposure to causative factors of occupational diseases. It can also be used in other fields of occupational health engineering.