Time Elapse Research Articles

Development of an estimation method for accidental hypothermia risk due to cold exposure in disasters triggered by earthquakes and tsunamis

Freezing deaths due to accidental hypothermia cause human casualties in disasters triggered by earthquakes and tsunamis during severe winters. However, until now, scientific estimates for frozen deaths are not included in earthquake damage estimates. The newly published earthquake damage estimation methodology of Japan's Cabinet Office only considers outdoor evacuees as victims of hypothermia. In this study, we developed a method to estimate the number of frozen deaths due to earthquake disasters, using the International Standards Organization's (ISO11079) coldness index to evaluate the “Duration of Limited Exposure” for disaster victims. Furthermore, we applied the proposed function on the damage assumption for the Hokkaido region in Japan and estimated the number of hypothermia sufferers owing to time elapse. This is the first method to estimate the number of frozen deaths owing to time elapse in earthquake disasters, which will be useful for considering measures to reduce the number of frozen deaths.

Soil, water and plants contamination by total chrome and chrome VI

AbstractThe chrome (Cr) is a metal utilized in various industrial sectors and its investigation in the environment is necessary, for the Cr (III) contain aessential micronutrients in the human nourishment and the Cr (VI), on the other hand, is toxic. In the present work soil contamination with Cr was realized in drainagelysimetersset in concentrations of 0, 200, 400, 600, 800 and 1000 mg kg−1 of total Cr, with the intuition to determine the total Cr and Cr (VI) flux in leached water, in soil and in plants of lettuce (Lactuca sativa L.). In the lysimeters were cultivated four plants, in three cultivation circles. In the end of the cultivations was observed, that the total applied Cr leached in the soil, evidencing the Cr mobility in latossoil with simulant characteristics to the ones utilized in this paper. The Cr (VI) concentrations in the soil increased soon after the treatment applications, but tend to decrees in the time elapse, the same tendences were observed for the total Cr concentrations in the leached water. The Cr absorption by plants was related to the Cr disponibility in the soil, for the soil concentration and the plants decreased with time passing. The Cr mobility in the soil possibilitated the groundwater contamination presenting risks to the water quality and, consequently to public health.

Clinical features and prognosis of pediatric idiopathic sudden sensorineural hearing loss: A bi-center retrospective study.

Limited research has focused on the clinical features of sudden sensorineural hearing loss (SSNHL) in pediatric patients. This study is aimed to investigate the relationship between clinical features and the baseline hearing severity and outcomes of SSNHL in the pediatric population. We conducted a bi-center retrospective observational study in 145 SSNHL patients aged no more than 18 years who were recruited between November 2013 and October 2022. Data extracted from medical records, audiograms, complete blood count (CBC) and coagulation tests have been assessed for the relationship with the severity (the thresholds of the initial hearing) and outcomes (recovery rate, hearing gain and the thresholds of the final hearing). A lower lymphocyte count (P = 0.004) and a higher platelet-to-lymphocyte ratio (PLR) (P = 0.041) were found in the patient group with profound initial hearing than in the less severe group. Vertigo (β = 13.932, 95%CI: 4.082-23.782, P = 0.007) and lymphocyte count (β = -6.686, 95%CI: -10.919 to -2.454, P = 0.003) showed significant associations with the threshold of the initial hearing. In the multivariate logistic model, the probability of recovery was higher for patients with ascending and flat audiograms compared to those with descending audiograms (ascending: OR 8.168, 95% CI 1.450-70.143, P = 0.029; flat: OR 3.966, 95% CI 1.341-12.651, P = 0.015). Patients with tinnitus had a 3.2-fold increase in the probability of recovery (OR 3.222, 95% CI 1.241-8.907, P = 0.019), while the baseline hearing threshold (OR 0.968, 95% CI 0.936-0.998, P = 0.047) and duration to the onset of therapy (OR 0.942, 95% CI 0.890-0.977, P = 0.010) were negatively associated with the odds of recovery. The present study showed that accompanying tinnitus, the severity of initial hearing loss, the time elapse and the audiogram configuration might be related to the prognosis of pediatric SSNHL. Meanwhile, the presence of vertigo, lower lymphocytes and higher PLR were associated with worse severity.

Monte Carlo study of uncertainty propagation in Euler rotational kinematic equation

We perform a Monte Carlo simulation to study the propagation of uncertainty in Euler rotational kinematic equation. The rate gyro data from an IMU sensor are inserted into the Euler rotational kinematic differential equation to calculate the sensor orientation, which is specified by its Euler angles. The uncertainty of sensor orientation is determined by simulating the variation of rate gyro input due to its uncertainty obtained from the calibration process. We find that the uncertainties of the Euler angles grow with time. Their values are proportional to the square root of time elapse. We find also that the uncertainties are linearly proportional to the uncertainties of rate gyro data and the square root of sampling time. These results interestingly resemble the behaviour of the Wiener process, with the step size of random walk depends on the time step. We can use these results as a criterion to choose a suitable IMU due to the characteristic of the integrated rate gyro sensor, especially in the application like the vehicle tracking or posture warning for elderly/disable people, where the precise sensor orientation is needed for a long period of operation.

CrowdLoc: Robust image indoor localization with edge-assisted crowdsensing

Image indoor localization, which is advantageous in infrastructure-less deployment and high positioning accuracy among various indoor localization schemes, is usually deployed in a lightweight end (shooting picture) and heavyweight server (searching image for location in the database) manner. Such a scheme is suffered from two major drawbacks: (1) The uploading and searching of the shooting pictures cause a severe burden to the server. (2) The image map will become defected as time elapse, such as missing features in initialization maps and continuous changes in the scene. To keep the image map up-to-date, a labor-intensive site survey is required with dedicated devices. The frequent updating will further exhaust the limited resources in the server. These two drawbacks have greatly hindered the image-based indoor localization from large-scale deployment. To this end, we study how to use crowdsourcing data to mitigate map defects and optimize location computation and map storage through edge architecture. In this paper, we propose CrowdLoc, an edge-assisted image localization architecture with lightweight multi-view localization on clients and crowdsourcing map-cache on the edge. Our method is mainly innovative in three parts. Firstly, CrowdLoc provides a lightweight multi-view localization on the client-side and the low-confidence localization can be offloaded to the edge server to use the crowdsourcing map for more accurate calculation. Secondly, CrowdLoc uses a map defect perception algorithm to recognize the update of the scene during user localization and update the crowdsourcing map-cache automatically on the edge side. Thirdly, in order to improve cache utilization, we propose a cache elimination strategy that runs periodically on the edge side. It can classify cache data according to the frequency of cache hits on a regular basis, remove invalidation data, and persist long-term updated data to the client map to reduce clients’ computing offload. We evaluate the performance of our method based on the real data in the lobby of an experimental building with a map missing rate of 20% and a map update rate of 40%. The results show that the mean localization error of CrowdLoc is 1.54 meters, which is 59.4% lower than that of multi-view localization without crowdsourcing maps, and only 0.56 meters higher than localization in non-defective maps.

Optimal Pricing, Ordering, and Replenishment Policies in a Multi-Item Inventory System for Deteriorating Items Under Time-Varying Backlogging Rate

In today’s advanced society, customers are influenced by products full of choices. For more sales, the retailer should maintain an inventory of each variety of items. These varieties have been seen in most food shops, fruit shops, fashion shops, electronic shops, etc., where the products deteriorate with time elapse. Depending on the customer’s demand, the stock out time of different deteriorating items is different. Assimilating all these varieties, in this paper, we have developed a multi-item inventory model for deteriorating items where demands depend on the sales price of the product. Shortages are allowed and partially backlogged with a time-dependent backlogging rate. The multi-item mechanism’s prime objective is to find the optimal sales price, order quantity, time length up to zero inventory, and cycle length to maximize the retailer’s overall profit. Finally, numerical examples are provided to illustrate the model with some managerial insights.

Application of sono-electrocoagulation in arsenic removal from aqueous solutions and the related human health risk assessment

Among the contaminants found in groundwater, arsenic poses a great threat to human health and the ecosystem. Therefore, it is vital to eliminate arsenic from water sources. This study utilizes one of the most efficient and emerging decontamination techniques known as the sono-electrocoagulation method. In recent years, sono-electrocoagulation has attracted many scientists due to its unique features, such as being cost-effective, rapid process, and high efficiency. The required groundwater samples were artificially synthesized in the laboratory, where the anode and cathode were determined to be Fe, Ti/PbO2, and Al, respectively. During the experiment, the impact of pH (5,6,7,8), various initial concentrations (100, 200, 300,400, 500, 600 μg/l), exposure times of 5,10,15,20,25 min, electrode distances of 1.5,2,2.5,3,3.5 cm and different current intensities of 5,10,15,20,25 mA/cm2 were examined. The ambient temperature of the laboratory was kept at 30 and 40 °C. Furthermore, this study showed that the system containing Ti/PbO2 as the anode and Al as the cathode electrodes removed arsenic contamination more effectively in the base environment. The performance of arsenic removal was directly related to current intensity, pH, and time. Nevertheless, time elapse played a negative factor due to the corrosion of the electrodes' surface and the dissolution of floating materials in the solution. With the surge of arsenic concentration from 100 to 300 mg/L, the arsenic removal efficiency increased from 61.9 to 98.5 percent, where the maximum removal efficiency due to the rise of the current intensity was 84.16 percent. The sono-electrocoagulation method reduced the risk of carcinogenic and non-carcinogenicity from 5.15E-03 to 7.73E-05 and 26.71 to 0.40. Accordingly, it was found that a combination of ultrasonic and electrocoagulation processes is a promising approach for arsenic removal.

Predicting in-hospital mortality in adult non-traumatic emergency department patients: a retrospective comparison of the Modified Early Warning Score (MEWS) and machine learning approach.

BackgroundA feasible and accurate risk prediction systems for emergency department (ED) patients is urgently required. The Modified Early Warning Score (MEWS) is a wide-used tool to predict clinical outcomes in ED. Literatures showed that machine learning (ML) had better predictability in specific patient population than traditional scoring system. By analyzing a large multicenter dataset, we aim to develop a ML model to predict in-hospital morality of the adult non traumatic ED patients for different time stages, and comparing performance with other ML models and MEWS.MethodsA retrospective observational cohort study was conducted in five Taiwan EDs including two tertiary medical centers and three regional hospitals. All consecutively adult (>17 years old) non-traumatic patients admit to ED during a 9-year period (January first, 2008 to December 31th, 2016) were included. Exclusion criteria including patients with (1) out-of-hospital cardiac arrest and (2) discharge against medical advice and transferred to other hospital (3) missing collect variables. The primary outcome was in-hospital mortality and were categorized into 6, 24, 72, 168 hours mortality. MEWS was calculated by systolic blood pressure, pulse rate, respiratory rate, body temperature, and level of consciousness. An ensemble supervised stacking ML model was developed and compared to sensitive and unsensitive Xgboost, Random Forest, and Adaboost. We conducted a performance test and examine both the area under the receiver operating characteristic (AUROC) and the area under the precision and recall curve (AUPRC) as the comparative measures.ResultAfter excluding 182,001 visits (7.46%), study group was consisted of 24,37,326 ED visits. The dataset was split into 67% training data and 33% test data for ML model development. There was no statistically difference found in the characteristics between two groups. For the prediction of 6, 24, 72, 168 hours in-hospital mortality, the AUROC of MEW and ML mode was 0.897, 0.865, 0.841, 0.816 and 0.939, 0.928, 0.913, 0.902 respectively. The stacking ML model outperform other ML model as well. For the prediction of in-hospital mortality over 48-hours, AUPRC performance of MEWS drop below 0.1, while the AUPRC of ML mode was 0.317 in 6 hours and 0.2150 in 168 hours. For each time frame, ML model achieved statistically significant higher AUROC and AUPRC than MEWS (all P < 0.001). Both models showed decreasing prediction ability as time elapse, but there was a trend that the gap of AUROC values between two model increases gradually (P < 0.001). Three MEWS thresholds (score >3, >4, and >5) were determined as baselines for comparison, ML mode consistently showed improved or equally performance in sensitivity, PPV, NPV, but not in specific.ConclusionStacking ML methods improve predicted in-hospital mortality than MEWS in adult non-traumatic ED patients, especially in the prediction of delayed mortality.

Comparison of infiltration models to describe infiltration characteristics of bioretention

Bioretention is one of low-impact development measures, which widely used not only because it can reduce stormwater runoff total volume, decrease peak flow rate and delay peak flow time, but also can remove the runoff pollutants. Infiltration is an important hydrological process for bioretention to evaluate its runoff total volume reduction and pollutants removal. So, it is important to find an optimal infiltration model that can well describe the infiltration performance of bioretention. The Horton, Philip and Kostiakov infiltration models were selected to compare their accuracy when using for describe the infiltration characteristics of bioretention, and the errors between the different models simulate results and experiment results were assessed via the maximum absolute error (MAE), bias and coefficient of determination (R2). The experimental results showed that Horton model is fitting well and flexible under different experiment conditions, especially when the hydraulic head was 10 cm, with MAE of 0.50–0.81 cm/h, bias of 0.1–0.23 cm/h and R2 of 0.98–0.99. R2 of the Philip and Kostiakov models were all over than 0.87 at the initial infiltration period, but the model fitting accuracy decreased significantly with infiltration time elapse. Furthermore, the total runoff volume capture ratio and emptying time were advanced used to evaluate the flexibility of Horton model, and the Nash-Sutcliffe efficiency coefficients of them were over than 0.61 and 0.58, respectively. Therefore, the Horton model can be optimal selected to describe the infiltration process of bioretention and for its hydrological evaluation.

3D concrete printing matrix reinforced with Geogrid

One of the most widely used Construction material is Concrete. The quality of the concrete is highly dependent on the material proportion which in turn depends on the application that it is being used for. In the conventional method, hike in the cost of the project is majorly synonymous to the use of formwork. And this gets added up with a list that includes safety issues, wastage of material, time elapse, space constrain, labour problems, etc. The aforementioned subjects can be made effective with the application of 3D Printing Techniques in Concrete Technology. This Paper targets on optimizing the mortar mix for 3D Printing Concrete with adaptable mineral and chemical admixtures. Use of accelerators reduced the final setting time to 95 min from conventional time of 310 min. Also the use of fly ash as replacement to sand enhanced the compressive strength to 30 MPa compared to conventional concrete that had 25 MPa. Other durability parameters were also improved compared to control mix.

Changing Narratives of Survivors of the 2014 Hiroshima Landslide

The purpose of this study is to understand the fluidity of survivors’ narratives and to clarify the changes such narratives undergo after time has elapsed. Nineteen survivors of the landslide disaster that occurred on August 20, 2014 in Hiroshima City were interviewed twice-three years after the disaster and five years after the disaster-and the changes in the content of their narratives were analyzed. In addition, by analyzing the titles of newspaper articles that were published within one month of the disaster, the characteristics of narrative transformation were quantitatively identified. The narratives of disaster victims that were once accepted as “dominant stories” become “personalized” as “alternative stories” with the elapse of time, even though they are told by the same person. Comparisons of two interviews conducted at different times show that the word “evacuation” undergoes a significant change in context over time elapse, while the word “disaster” appears in a new context in the fifth-year interview. While social or community groups are the bearers of “socialized” memories, individuals are the bearers of “personalized” memories which are expected to continue to change as time elapses. It is necessary to examine what should be shared in order to utilize disaster victims’ memories to prevent and mitigate disasters, and how to such memories should be shared.

Computational Prediction of Cervical Cancer Diagnosis Using Ensemble-Based Classification Algorithm

AbstractCervical cancer is one of the most common cancers among women in the world. As at the earlier stage, cervical cancer has fewer symptoms. Cancer research is vital as the prognosis of cancer enables clinical applications for patients. In this study, we demonstrate a new approach that applies an ensemble approach to machine learning models for the automatic diagnosis of cervical cancer. The dataset used in the study is the cervical cancer dataset available at the University of California Irvine database repository. Initially, missing values are imputed (k-nearest neighbors) and then the data are balanced (oversampled). Two feature selection approaches are used to extract the most significant features. The proposed stacking architecture, applied for the first time on the cervical cancer dataset, used time elapse of 5.6 s and achieved an area under the curve score of 99.7% performing better than the methods used in previous works. The objective of the study is to propose a computational model that can predict the diagnosis of cervical cancer efficiently. Further, the proposed learning architecture is gauged with several ensemble approaches like random forest, gradient boosting, voting ensemble and weighted voting ensemble to perceive the enhancement.

DNAzyme-catalyzed etching process of Au/Ag nanocages visualized via dark-field imaging with time elapse for ultrasensitive detection of microRNA

Abstract Dark-field imaging techniques based on the localized surface plasmon resonance (LSPR) of metal nanoparticles provide new insights for real-time monitoring of dynamic reaction processes at single particle level. In this work, the Au/Ag nanocages (NCs) are employed as optical plasmon probes for microRNA detection based on visualized scattering signal changes. Induced by DNAzyme-catalyzed etching process, the scattering signals of plasmon probe “turns-off” due to the decreased silver proportion of Au/Ag NCs with time elapse. The dynamic process is monitored under dark-field microscopy, in which the waiting time that elapsed before a nanocage stochastically disappeared is found directly related to the concentration of the target microRNA. Combined with the strand displacement and hybridization cascade amplification strategy, the concentration of microRNA-21 in cell lysate is determined by statistical analysis with high sensitivity and selectivity. The proposed dark-field scattering biosensing based on nanocage probes is convenient for accurately judging end-point during real time monitoring over time, and provides a novel strategy for the development of biosensing at single particle level.

Heat transfer in electrokinetic micro-pumps under the influence of various oscillatory excitations

Thermal characteristics of time-periodic electroosmotic flow are analyzed in a micro-annulus under the influence of various alternating electric fields. Representative hydrodynamic and thermal quantities, i.e. volumetric flow rate and Nusselt number, demonstrate oscillatory behaviors approaching a quasi-steady state if few periods of time elapse. An important parameter named dimensionless frequency, which normally affects the diffusion mechanism, is responsible for the penetration depth of momentum and energy into the fluid in the radial direction. The higher the dimensionless frequency, the smaller the transport phenomena diffuse radially into the bulk fluid; while the advection mechanism is intensified and consequently Nusselt number is increased. The cooling-mode mean Nusselt number is slightly smaller than the heating- mode one. A variety of waveforms is examined in the present research; their performances are then compared together using proper measures. A strength index is introduced to evaluate the relative ability of each individual excitation in a half period of time. A key parameter named thermal/frictional index is also utilized to assess the total effectiveness of the system in different circumstances especially when the basic excitation functions are applied. Unlike the vigorous square waveform, the sawtooth one is the most efficient.

The Dissipation of Cyazofamid and Its Main Metabolite CCIM During Wine-Making Process.

Few studies have focused on the residues of cyazofamid and its main metabolite CCIM (4-chloro-5-p-tolylimidazole-2-carbonitrile) in the wine making process, which is crucial to evaluate the potential food risk of cyazofamid and CCIM. In this work, detailed study has been conducted on the evaluation of the fate of cyazofamid and its main metabolite CCIM during the wine-making process. The targeted compounds cyazofamid and CCIM were separated and determined by high-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS) and processing procedure including washing, peeling, fermentation, and clarification. Results showed that residues of cyazofamid and CCIM decreased significantly in wine processing. The dissipation of cyazofamid in the fermentation process followed the first-order of kinetics, and the half-life of cyazofamid was 46.2–63.0 h, whereas, the residues of CCIM, in the three treatments, decreased with time elapse. The processing factors (PFs) were all less than one in different processing processes, and the PFs ranges of cyazofamid and CCIM were 0.003–0.025 and 0.039–0.067 in three treatments in the overall process. The outcome indicated that the whole process could significantly reduce the residues of cyazofamid and CCIM in red and white wines. The results might provide more precise risk assessments of cyazofamid in the wine-making process.

Effect of human stromal vascular fraction gel on the treatment of patients with skin depressed scar and its mechanism

Objective: To observe content of cytokine in human stromal vascular fraction gel (SVF-GEL) and effect of SVF-GEL on biological behaviors of epidermal and dermal cells in vitro and clinical efficacy of SVF-GEL. Methods: (1) SVF-GEL was prepared using liposuction aspirates harvested from females who received abdomen liposuction in author's unit. SVF-GEL (1 mL) and high-glucose Dulbecco's modified eagle medium (DMEM, 1 mL) were respectively cultured for 24 h with high-glucose DMEM containing 10% fetal calf serum, 10 g/L penicillin, and 10 g/L streptomycin, denoted as SVF-GEL group and negative control group, with 6 samples in each group. Content of epidermal growth factor (EGF) and vascular endothelial growth factor (VEGF) in the supernatant was determined by enzyme-linked immunosorbent assay. (2) A number of 5×10(5) human skin fibroblasts (HSF) and HaCaT cells in logarithmic phase were inoculated and cultured in Transwell chambers for 12 h. All Transwell chambers containing cells were divided into SVF-GEL group (0.5 mL SVF-GEL was added for co-culture) and control group (0.5 mL high-glucose DMEM was added for co-culture), with 9 samples in each group for HSF and HaCaT cells. Scratch assay was performed after culture for 24 h, and residual scratch width was observed at post scratch hour (PSH) 0 (immediately), 24, and 48. Cell migration distance was measured at PSH 24 and 48. After culture for 24, 48, and 72 h, the number of living cell was counted using cell counter. (3) From June 2018 to June 2019, SVF-GEL was applied clinically to treat 15 patients with depressed scars on face, including 2 males and 13 females, aged 19 to 42 years. Survival condition of SVF-GEL and whether complications or not were observed 6 months after surgery. Before surgery and 6 months after surgery, depressed degree, color, and pliability of scar were compared. Vancouver Scar Scale (VSS) was employed to access color, vascularity, and pliability before surgery and 6 months after surgery, and total score was calculated. The number of patients with complete satisfaction or satisfaction was counted six months after surgery. Data were processed with analysis of variance of factorial design, paired samples t test, and Wilcoxon rank sum test. Results: (1) The content of EGF in SVF-GEL group and negative control group was (316.6±12.8) and (3.4±0.6) pg/mL, and the content of VEGF in SVF-GEL group and negative control group was (568.67±12.19) and (4.93±0.16) pg/mL, with statistically significant differences between the two groups (t=48.777, 92.485, P<0.01). (2) Residual scratch widths of HSF and HaCaT in SVF-GEL group and control group were decreased gradually along with time elapse, in which those in SVF-GEL group at PSH 24 and 48 were less than those in control group. At PSH 24 and 48, cell migration distances of HSF and HaCaT in SVF-GEL group were more than those in control group (t(HSF)=-20.304, -43.516, t(HaCaT)=-15.060, -8.684, P<0.01). After culture for 24, 48, and 72 h, the number of living cell of HSF and HaCaT in SVF-GEL group was significantly more than that in control group (t(HSF)=-3.374, -6.809, -18.036, t(HaCaT)=-4.793, -6.028, -8.141, P<0.05 or P<0.01). (3) Six months after surgery, SVF-GEL grafted into patients survived well without complications, and depressed degree of scar ameliorated obviously with lightened pigmentation and softer texture as compared with before surgery. Compared with those before surgery, VSS scores of color, vascularity, and pliability, and total score of 15 patients with depressed scars on face were obviously decreased 6 months after surgery (Z=-2.06, -2.07, -2.07, t=-15.811, P<0.05 or P<0.01). One patient was satisfied with the clinical outcome, and the rest 14 patients were completely satisfied with the clinical outcomes. Conclusions: SVF-GEL contains cytokines EGF and VEGF, which can enhance cell migration ability and proliferation ability of HSF and HaCaT cells and have obvious effects on depressed scars for clinical application.

EFFICIENT ROUTING PROTOCOL WITH COLLISION AVOIDANCE IN VEHICULAR NETWORKS

The vehicle-Adhoc Networks are the specific type wireless adhoc networks, framed using the group of vehicles supporting the “on the fly’ communication between vehicles on the roadside. This is basically developed to handle the traffic in an intelligent manner avoiding the unnecessary time elapse, discomfort and the fatalities during the travelling and in turn improvise the convenience in the transportation providing a continuous traffic movement. But certain emergent situations such as the natural disasters, accidents, damaged roads, sudden break down of the vehicles and the appearance of the emergency vehicles disturb the regular traffic flow and safety of the on road vehicles. To ensure the safety of on road vehicles and elude the collision of the vehicles that take place due to improper communications or communication attacks, the paper puts forth an effective routing protocol with collision avoidance, (ERPCA) to identify vehicles with the reliability to transfer information on time and evade the discomforts in travelling. The evaluation of the ERPCA with the network simulator-2 evinces the improvement in the performance of the vehicular-adhoc networks

The Persian Version of the Fear of Cancer Recurrence Inventory (FCRI): Translation and Evaluation of Its Psychometric Properties

Background: This study aimed to translate and validate the Fear of Cancer Recurrence Inventory (FCRI) questionnaire into Persian and to investigate its psychometric properties.&#x0D; Methods: The FCRI was translated to Persian using a linguistic methodology according to WHO guidelines. A total of 450 breast cancer survivors who had the following inclusion criteria were included: time elapse of more than six months after the treatment prior to the study; absence ofobjective markers of recurrence, fluency in the Persian language, and signing the informed consent. Internal consistency was estimated with Cronbach's α coefficient and test-retest reliability with Interclass correlation. Concurrent validity was estimated through Pearson’s correlation between the FCRI and Hospital Anxiety and Depression Scale (HADS). Principal component analysis (PCA) and confirmatory factor analysis (CFA) were employed to evaluate dimensionality.&#x0D; Results: The Persian version was acceptable for patients. The content validity index (CVI) was 0.80. The instrument had good test-retest reliability (ICC= 0.96) and internal consistency (Cronbach’s α=0.86). PCA and CFA indicated that the factor structure of the Persian version was similar to the original questionnaire and had acceptable goodness of fit. Correlations between the FCRI and HADS was remarkable (r= 0.252 – 0.639), indicating acceptable concurrent validity.&#x0D; Conclusions: The Persian version of FCRI could be considered a good cross-cultural equivalent for the original English version. The questionnaire was a reliable and valid instrument in terms of internal consistency, test-retest reliability, and dimensionality.

An IMPC Based Parking Assistance System

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;This paper summarizes progress and outcome from our research projects on adaptive model predictive control based parking management system, including parking motion planning and control strategy, as well as a localization strategy for parking spot. IMPC here refers to interactive model predictive control regime, which is characterized in that multiple agents implementing separate MPC strategy are incorporating information about their state, objective, and constraints. To predict future parking parameters, we proposed a practical framework which integrates anticipatory techniques with a model predictive approach that robustly models the uncertainty intrinsic of parking environment. The control regime puts comprehensive consideration into the interactions between vehicle subsystems, thus capable of optimizing trajectory under complex input disturbances under real-world driving scenarios. Moreover, Adaptive model predictive control is utilized to optimally minimize a cost function regarding time elapse, peripheral convenience and vehicle dynamics correspondent with surrounding vehicle states. The objective function is solved by dynamic programming under calibrated constraints in terms of velocity and steering accuracy, which yielded superior performance in comparison with convex programming. A dedicated guidance system was developed for navigating user to the parking spot for ease of locating parking location, which is characterized in that swift location and path are generated by BLE-based sensor fusion. Upon parking action finalization, the BLE sensor transmits the parking location to preferred communication equipment of user, which serves as goal of parking retrieve assignment. Simulation results show promising expected cost minimization in typical parking environments under consideration of numbers of trials, parking time and distance to destination. The achieved accuracy of MPC-led parking management strategy is able to improve the precision up to 0.3 meter, within the simulated highly disorganized parking environment. Meanwhile, the state of art park spot search module is able to shorten the time for drivers to locate their vehicle with positioning error of less than 1.2 meter.&lt;/div&gt;&lt;/div&gt;

Nonvibrating energy strings as fundamental building blocks of space and particles

In the proposed Energy String (ES) theory, we assume the existence of fundamental energy strings forming a generally Euclidean four-dimensional fabric of empty space as well as forming all types of particles in the universe. The 4D space fabric is composed of space energy strings bearing dark-energy as well as a newly described dark-momentum. Particles are composed of particle energy strings which interact with space energy strings inducing three-dimensional space curvatures embedded in a flat fourth-space dimension. The induced space curvatures are responsible for gravity of particles and assign a longitudinal and a transverse direction to particles. The proposed ES theory yields an adapted model of the universe with remarkable teachings as follows: (1) The fabric of space and related dark-energy are associated with a newly defined dark-momentum. This dark momentum is the sole contributor to the cosmological constant Λ in Einstein's field equations which describes the accelerated expansion of the universe. The energy of the quantum vacuum becomes nonrelevant to the cosmological constant Λ, enabling a solution to the “Cosmological Constant Problem”; (2) All particles perform an equal distance of translatory displacement in 4D-space, reflecting a universal displacement rate of particles relative to an absolute generally Euclidean 4D-space. This universal principle is equivalent to Lorentz transformation of a fundamental four-displacement vector, representing a new model of Special Relativity with superior compatibility to quantum theories. (3) Time is a displacement property of mass particles in 4D-space. Frames of 3D-space+time are the perspective by which mass particles experience 4D-space. In this perspective, absolute space longitudinally displaces over mass particles experienced as proper time elapse. Temporal momentum is an inherent invariant property of mass particles. Frames of 3D-space+time are mixed domains: three spatial coordinates of position-space and a temporal coordinate of momentum-space, meaning the position-space in the temporal coordinate is totally inaccessible.