Probability Of People Research Articles

Seismic fragility analysis of human perception in high‐rise buildings subjected to far‐field long‐period earthquake ground motions: A case study for Shanghai tower

AbstractHuman perception in high‐rise buildings during far‐field long‐period earthquake ground motions often induces psychological discomfort, including fear and anxiety. A comprehensive understanding on human perception of seismic events is vital for city planning and emergency management, facilitating effective evacuation plans and minimizing stampede risks. This study addresses a gap by employing the seismic fragility analysis method to delineate how human perception in high‐rise buildings is affected during far‐field long‐period ground motions. The methodology involves several key steps. First, the far‐field long‐period earthquake ground motion was identified by detecting the later‐arriving surface waves, and a series of records were selected from the next generation attenuation (NGA) West‐2 ground motion database of the Pacific Earthquake Engineering Research center. Then, a high‐rise building in Shanghai, China was modeled using ETABS 20. Through the linear‐elastic time history analysis, the structural seismic response at each floor was computed. Furthermore, human perception thresholds to vibration were introduced to assess the degree of human perception at each floor, illustrating the difference of human perception to seismic tremor at different floors. Finally, a novel earthquake intensity measure (IM), namely average response spectrum intensity (ARSI) within the vibration period ranging from 0.1 s to 10 s was introduced to generate seismic fragility curves for human perception. According to the investigation, it was found that the corner frequency and the associated energy ratio are useful indicators to identify the far‐field long‐period earthquake ground motions. The ARSI is an effective parameter to assess human perception to seismic tremor compared to the spectral acceleration at a given fundamental period. The generated seismic fragility analysis can provide a complete and thorough understanding on the probability of people that should be evacuated under different earthquake intensity levels. The probability of human perception at different floors varies along the building height, demonstrating the difficulty to make crowd evacuation plan in practice. This insight is vital for understanding and mitigating seismic concerns in high‐rise buildings, particularly in low‐to‐moderate seismicity regions.

Dynamical vaccination behavior with risk perception and vaccination rewards.

Vaccination is the most effective way to control the epidemic spreading. However, the probability of people getting vaccinated changes with the epidemic situation due to personal psychology. Facing various risks, some people are reluctant to vaccinate and even prefer herd immunity. To encourage people to get vaccinated, many countries set up reward mechanisms. In this paper, we propose a disease transmission model combining vaccination behaviors based on the SIR (Susceptible-Infected-Recovered) model and introduce three vaccination mechanisms. We analyze the impact of the infection rate and the recovery rate on the total cost and the epidemic prevalence. Numerical simulations fit with our intuitive feelings. Then, we study the impact of vaccination rewards on the total social cost. We find that when vaccination rewards offset vaccination costs, both the total cost and the epidemic prevalence reach the lowest levels. Finally, this paper suggests that encouraging people to get vaccinated at the beginning of an epidemic has the best effect.

Will tobacco price increases lead more people who smoke to vape? The results from a discrete choice experiment amongst U.S. adults

ObjectiveTo understand the extent to which people who smoke, people who vape and nonsmokers would switch between smoking cigarettes and vaping in response to policies (price increases, restrictions on nicotine, places, and information on addictiveness and/or health risks) aimed at decreasing tobacco use by people who smoke and vaping by nonsmokers.DesignA total of 525 adults aged 18 to 88 years completed a discrete choice survey of 16 choices between two smoking/vaping alternatives. Analysis was conducted using conditional logistic regression for the entire sample and stratified by nonsmokers, people who smoke, and people who vape.ResultsThe results suggest that most people who vape also smoke. Nonsmokers were more favorable to vaping and were concerned about long-term health risks and cost associated with vaping. Marginal analysis suggests that price increases will have only modest success in moving people who smoke to start vaping or encouraging people who vape to vape rather than use cigarettes. Nonsmokers are not very sensitive to price changes but are sensitive to information about health impacts.ConclusionsFindings indicate that increasing the price of cigarettes would lead to a limited increase in the probability of people who smoke switch to vaping. The study advances our understanding of the views of current nonsmokers toward cigarettes and vaping, suggesting that price increases and increased knowledge of addiction would likely deter nonsmokers from vaping. Changing the amount of nicotine associated with smoking would increase the probability of vaping slightly and have little impact on nonsmokers or vaping preferences, but the most significant change would come from increasing the perceptions of the risk of smoking.

Community’s Potential and Preferences for Islamic Banking : the Case of Indonesia

Islamic Banking is an increasingly important part of the Indonesian economy and finance. The competition between conventional and Islamic banks and customer demographic factors affect the performance of Islamic Banking. The purpose of this study was to analyze the potential and preferences of the community towards Islamic banking in terms of a demographic perspective consisting of four factors, namely age, income, education, and occupation. The potential and preferences of the community are proxied by the ownership of Islamic banking accounts. The study uses a sample of 620 questionnaires. The methodological approach is binary logistics regression or multinomial logistic linear regression using IBM SPSS statistics 25 software. The dependent variable (Y) is the probability of people who have an account in Islamic banking as a proxy to measure the potential and preference of Islamic banking. The independent variable (X) is several factors that affect account ownership in Islamic Banking like age, education, occupation, and income. The paper’s findings show that respondents in the segment aged less than 40 years old, in middle education, and working as entrepreneurs have a lower and significant probability of having an account in Islamic banking than respondents aged more than 40 years old, highly educated, and working in the company. There is no significant difference in the probability of account ownership in Islamic banking.

Construction of Smart Marketing Model of Agricultural Products E-Commerce in the Era of Big Data

With the rapid development of China, the marketing mode of agricultural fruit is also keeping pace with the times. The old sales model of agricultural fruit is also affected, which has a huge impact on marketing models, channels, and sales amount. And the sales methods of agricultural fruit have also undergone great changes, from offline transactions to online platform transactions. Comparing the profit, popularity, proportion of agricultural fruits, and turnover of agricultural fruits in e-commerce with the traditional marketing model, the smart marketing model in the data age increases the turnover by 50% and the profit by 15%. And in the network environment that extends in all directions, the probability of people knowing about agricultural fruits will be greater. It can better build the agricultural product marketing system in the information age and make it conform to the characteristics of contemporary marketing. Through the marketing mode in the information age, the judging project was set up, using estimated calculations to draw conclusions. In the era of rapid network information, e-commerce of agricultural fruits can help agriculture to advance rapidly and slowly go to the world.

Estimation of the Reproductive Number Trend of the Novel Coronavirus "COVID-19" in Southern Iran from July to November 2020.

Background: Effective measures to control COVID-19 should be based on an understanding of its epidemiological pattern and the evaluation of its prevalence in the community. This study aimed to examine the reproductive number (R) of COVID-19 and its trend in Fars Province in southern Iran.Methods: In this ecological study, the R trend was examined from July to November 2020. Data were collected from the daily reports of Shiraz University of Medical Sciences. R is the product of three components, namely the number of infection-producing contacts per unit time, the probability of transmission per contact, and the contagiousness period. Incidence and prevalence rates were used to calculate R. The R value was calculated in Microsoft Excel 2016.Results: The first and second peaks of COVID-19 were observed on July 6th and November 22nd, respectively. The median and mean of R were 1.42 and 1.41, respectively. The highest and lowest values of R were observed on October 20th (2.60) and September 1st (0.46), respectively. The values of R had a slightly decreasing trend in the second half of July and November than the first half. In the second half of August and September, an increasing trend was observed than the first half. There was not much change in the second half of October.Conclusion: The highest value of R was related to the dates when there was a higher probability of exposure to the virus, including public holidays and different occasions on which the probability of people’s participation in ceremonies, communities, and gatherings was higher.

Who Have a Higher Risk of Falling Into Catastrophic Health Expenditures?

Catastrophic health expenditure is one of the challenges Indonesia faces in achieving Universal Health Coverage. Aside from being a financial disaster, the incident caused by out-of-pocket health expenditure exceeding a fixed limit can drive people into poverty. Unfortunately, the availability of the data causes the limitation of the study in Indonesia. This study aims to analyze the association between catastrophic health expenditure and several social-economic factors by using the latest data of out-of-pocket expenditure collected at the individual level from the 2019 Susenas Module of Health and Housing. Using the Chi-square test, this study confirms a significant association between catastrophic health expenditures and the following social-economic factors: outpatient and inpatient service use, health insurance ownership, age, sex, marital status, educational level, work status, welfare status, type of area, and geographic location. From the logistic regression, the probability of the population to experience catastrophic health expenditure is higher for people in the following categories: use inpatient or outpatient services, do not have health insurance, are elderly, ever-married, not working, not poor, and live in the rural areas or Java island. Disaggregation by outpatient and inpatient service use shows the large gap in the probability of falling into catastrophic health expenditures. The probability for people who used inpatient service is more than four times people who never used the service. Meanwhile, for outpatient service, the probability is almost three times. Therefore, people can strengthen preventive care, especially those with low or no cost, to avoid falling into catastrophic health expenditure.

The similarity-updating model of probability judgment and belief revision.

People often take nondiagnostic information into account when revising their beliefs. A probability judgment decreases due to nondiagnostic information represents the well-established "dilution effect" observed in many domains. Surprisingly, the opposite of the dilution effect called the "confirmation effect" has also been observed frequently. The present work provides a unified cognitive model that allows both effects to be explained simultaneously. The suggested similarity-updating model incorporates two psychological components: first, a similarity-based judgment inspired by categorization research, and second, a weighting-and-adding process with an adjustment following a similarity-based confirmation mechanism. Four experimental studies demonstrate the model's predictive accuracy for probability judgments and belief revision. The participants received a sample of information from one of two options and had to judge from which option the information came. The similarity-updating model predicts that the probability judgment is a function of the similarity of the sample to the options. When one is presented with a new sample, the previous probability judgment is updated with a second probability judgment by taking a weighted average of the two and adjusting the result according to a similarity-based confirmation. The model describes people's probability judgments well and outcompetes a Bayesian cognitive model and an alternative probability-theory-plus-noise model. The similarity-updating model accounts for several qualitative findings, namely, dilution effects, confirmation effects, order effects, and the finding that probability judgments are invariant to sample size. In sum, the similarity-updating model provides a plausible account of human probability judgment and belief revision. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Employment structure in China from 1990 to 2015

Using nationally representative samples from population census and mini-census of China, this study analyzes important employment dynamics in China from 1990 to 2015. The share of routine manual jobs decreased significantly, from 57% to 32%. The share of routine cognitive jobs as well as that of adults not working increased significantly, from 8% to 19%, and from 16% to 31%, respectively. However, the share of non-routine jobs did not change significantly. Our decomposition analysis reveals the composition effect resulting from the change in the composition of population demographics, the propensity effect from change in the probability of people with given demographic characteristics sorting into different employment categories, and the interaction effect of the co-movement of demographic group size changes and propensity changes given demographic characteristics. For the decline in routine manual jobs, each of these three effects contributes 68%, 66%, and −34%, respectively. Meanwhile, for the rise in routine cognitive jobs, each effect is 16%, 74%, and 11%, respectively. Finally, for the rise in the not-working population, each effect is 7%, 93%, and 0.3%, respectively.

Employment Structures in China from 1990 to 2015: Demographic and Technological Change

Using national representative samples from population census and mini-census of China, this paper documents important employment dynamics in China from 1990 to 2015. The share of routine manual jobs decreased significant from 57% to 32%; both the share of routine cognitive jobs and the share of not-working increased significantly, from 8% to 19%, and from 16% to 31%, respectively; however, the share of non-routine jobs had no significant change. Our decomposition exercises suggest that the composition effect resulting from change in the composition of population demographics, the propensity effect from change in the probability for people with given demographic characteristics into different employment categories and the interaction effect contribute to 68%, 66% and -34% to the fall in routine manual jobs, respectively. Meanwhile, these effects for the rise in routine cognitive jobs and for the increase in not-working are 16%, 74%, 11%, and 7%, 93%, 0.3%, respectively.

ALTRUISM AND MORAL ENHANCEMENT

ABSTRACT In this article I will be discussing what altruism is, distinguishing altruistic motivations (pure and impure) and altruistic behaviour (soft and robust). Pure altruism is when the motivation to benefit another is exclusively to increase the other's welfare, and impure altruism is when the motivation to benefit another is solely to increase your own wellbeing, or includes on some level, increasing your own welfare. Soft altruism is helping behaviour and robust altruism is improving the welfare of another individual at the expense of the altruist. Having made these distinctions I move on to show that altruism is a requirement of morality. I argue that the three main principles of morality (categorical imperative, golden rule and the greatest happiness principle) are not only compatible with, but also recommend soft altruism. Finally I argue that the probability of people continuing to practise altruistic acts is higher when we are purely motivated, and if that is the case not only classic moral enhancement but also biotechnological moral enhancement can have a role in bringing people over to the altruistic side, stimulating their ‘other regarding ’ motivations, thus contributing to spreading altruistic behaviour and morality throughout the world.

Assessment of Willingness to Pay for Good Agricultural Practice Cabbage

This paper aims to investigate factors determining the probability of consumers’ willingness to pay a premium price for safe cabbage, as well as to estimate the mean willingness to pay a premium price for safe cabbage of consumers. Interviews with survey questionnaire are conducted in Bangkok with 540 respondents. The contingent valuation method with single- and double-bounded models is employed. The coefficients used to calculate mean willingness to pay are estimated by Maximum Likelihood method. The estimation of the change in the probability of people willing to pay for standardized cabbage is assessed by marginal effects of each factor, which are calculated by probit model. The result finds 9 significant variables as the determinants of consumers' willingness to pay. 329 respondents express their willingness to pay for GAP cabbage while 143 respondents show their true zero bids. The estimation of mean willingness to pay, therefore, is done based on these two groups of respondents. The weighted mean willingness to pay for GAP cabbage is 3.54 baht/kilogram over the current market price of normal cabbage. This amount is much lower than the difference in the variable cost between non-GAP and GAP cabbage producers, making it difficult for farmers to turn to standardized process of production.

HUBUNGAN SANITASI RUMAH DENGAN KEJADIAN PENYAKIT TUBERKULOSIS (TB) DI KECAMATAN KUTA

RELATIONSHIP HOUSING SANITATION WITH TUBERCULOSIS DISEASES (TB) INCIDENCE IN KUTA DISTRICTOne of the endemic infectious diseases occured in the community is tuberculosis (TB). The World Health Organization (WHO) estimated about one third of the world's population has been infected by the bacteria mycobacterium tuberculosis. Badung regency as one of the districts in the province of Bali also having cases of tuberculosis. From the report Badung Health Agency in 2015 was recorded 275 TB patients. From 6 districts in Badung district, subdistrict of Kuta occupy the highest number of cases recorded 100 patients. tuberculosis is closely related to homes sanitation that do not meet health requirements. The purpose of this study was to determine the relationship of home sanitation with disease incidence of tuberculosis in the district of Kuta. Based on the type of research is observational analytic, design research is a case control studies linking ie risk factors. (Home sanitation) with TB disease events, by comparing the case group and the control group. The population in this study are patients with TB BTA (+) were treated working area Puskesmas Kuta I and Puskesmas Kuta II sanitation as well as his home. The number of samples in this study was 60 consisting of the case group and the control group. How sampling is the total population of TB patients in the last 3 months of 2015 as well as sanitary home. Data collected from interviews, observations and measurements and then analyzed using chi square and followed by multiple logistic regression test. From the statistic test bivariate home sanitation with tuberculosis disease incidence 6 variables showed that: (1) lighting p = 0,00 (p< 0,05) OR = 21, (2) humidity p = 0,00 (p< 0,05) OR = 21,36 , (3) ventilation p = 0,00 (p< 0,05)OR = 11, (4) the walls of the house p = 0,00 (p< 0,05) OR = 8,64, (5) density residential home p = 0,00 (p<0,05) OR = 16,43 and (6) house floor p = 0,22 (p>0,05) OR = 2,143. To determine the relationship of all independent variables simultaneously multivariate analysis with multiple logistic regression test. Based on the results obtained that there are three independent variables significantly related (p<0,05) with the dependent variable is the humidity (OR = 19,158, 95% CI 3,171 –115,751), ventilation (OR = 6,408, 95% CI = 1,199 to 34,236), residential density (OR = 13,342, 95% CI = 2,261 – 78,733). Probability of people who occupy the house with sanitation (Humidity, Ventilation and Residential density) in the district of Kuta to contract tuberculosis (TB) is 97,08%. Based on these results, we can conclude that from the test bivariate (6 variables) are: lighting, humidity, ventilation, walls of houses, residential density and house floor associated with the incidence of tuberculosis in the district of Kuta. While the advice may be given to: (1). people who live in the district of Kuta in order to build or occupy a dwelling house to take into account the standard of sanitation and healthy home. (2). Government / agencies in order to provide guidance to the public in order to build houses of spatial attention and care homes that meet health requirements so that people who lived in the house to feel safe, comfortable, and avoid the disease especially those stemming from poor sanitation home.

What is the effect of university education on chances to be self-employed in transitional countries?: Instrumental variable analysis of cross-sectional sample of 29 nations

We used a high-quality cross-sectional data set that covers a diverse set of 29 transitional countries, to find the effect of education of probability of people being self-employed using standard probit models and instrumental variable biprobit that address endogeneity. Our findings suggest a negative effect of university education on the propensity of being self-employed. This finding remains the same for the single-stage model (i.e. standard probit) and the instrumental variable model (i.e. biprobit). We found strong endogeneity in the estimation of education effect on the propensity of being self-employed, ignoring which renders estimations biased. Regression models, which do not address endogeneity tend to underestimate the negative effect of the education on the probability of being self-employed in the countries of transition. Researchers should use alternative approaches to reduce endogeneity, such as instrumental variables and longitudinal analysis.

Explaining High Conjunction Fallacy Rates: The Probability Theory Plus Noise Account

AbstractThe conjunction fallacy occurs when people judge the conjunctive probability P(A ∧ B) to be greater than a constituent probability P(A), contrary to the norms of probability theory. This fallacy is a reliable, consistent and systematic part of people's probability judgements, attested in many studies over at least 40 years. For some events, these fallacies occur very frequently in people's judgements (at rates of 80% or more), while for other events, the fallacies are very rare (occurring at rates of 10% or less). This wide range of fallacy rates presents a challenge for current theories of the conjunction fallacy. We show how this wide range of observed fallacy rates can be explained by a simple model where people reason according to probability theory but are subject to random noise in the reasoning process. Copyright © 2016 John Wiley & Sons, Ltd.

Heuristics can produce surprisingly rational probability estimates: Comment on Costello and Watts (2014).

Costello and Watts (2014) present a model assuming that people's knowledge of probabilities adheres to probability theory, but that their probability judgments are perturbed by a random noise in the retrieval from memory. Predictions for the relationships between probability judgments for constituent events and their disjunctions and conjunctions, as well as for sums of such judgments were derived from probability theory. Costello and Watts (2014) report behavioral data showing that subjective probability judgments accord with these predictions. Based on the finding that subjective probability judgments follow probability theory, Costello and Watts (2014) conclude that the results imply that people's probability judgments embody the rules of probability theory and thereby refute theories of heuristic processing. Here, we demonstrate the invalidity of this conclusion by showing that all of the tested predictions follow straightforwardly from an account assuming heuristic probability integration (Nilsson, Winman, Juslin, & Hansson, 2009). We end with a discussion of a number of previous findings that harmonize very poorly with the predictions by the model suggested by Costello and Watts (2014).

Probability theory plus noise: Replies to Crupi and Tentori (2016) and to Nilsson, Juslin, and Winman (2016).

A standard assumption in much of current psychology is that people do not reason about probability using the rules of probability theory but instead use various heuristics or "rules of thumb," which can produce systematic reasoning biases. In Costello and Watts (2014), we showed that a number of these biases can be explained by a model where people reason according to probability theory but are subject to random noise. More importantly, that model also predicted agreement with probability theory for certain expressions that cancel the effects of random noise: Experimental results strongly confirmed this prediction, showing that probabilistic reasoning is simultaneously systematically biased and "surprisingly rational." In their commentaries on that paper, both Crupi and Tentori (2016) and Nilsson, Juslin, and Winman (2016) point to various experimental results that, they suggest, our model cannot explain. In this reply, we show that our probability theory plus noise model can in fact explain every one of the results identified by these authors. This gives a degree of additional support to the view that people's probability judgments embody the rational rules of probability theory and that biases in those judgments can be explained as simply effects of random noise.

HUBUNGAN KUALITAS SANITASI RUMAH DENGAN KEJADIAN PENYAKIT INFEKSI SALURAN PERNAPASAN AKUT (ISPA) DI WILAYAH KERJA PUSKESMAS IV DENPASAR SELATAN KOTA DENPASAR

Besides positive results, the rapid development and growth of Denpasar City has also brought some problems to the Government of Denpasar City, for example the emergence of housing complexes that did not meet health standards and requirements. This problem can cause negative impacts toward the health condition of city residents, especially in the form of diseases influenced by environment factors such as acute respiratory infections (ARI). Based on that phenomena this study was carried out to examine the causal relationship between home sanitation factors (ventilation, natural lighting, humidity, temperature, population density, and air pollution) and the event of acute respiratory infections (ARI) in the working area of Public Health Centre IV of Denpasar Selatan District, in Denpasar City. This study had an observational nature and employed a cross-sectional design. Based on data analysis applied, this study belong to analytical studies. Population size of this study was 5,777 and covered all inhabited houses in the working areas of Public Health Centre IV of Denpasar Selatan District. Sample of 97 houses were taken using proporsional stratified random sampling. Statistical tests shows that: (1) the quality of house sanitation has a significance value p = 0.000 (sig p <0.05), (2) house ventilation has a significance value = 0.162 (sig p>0.05, (3) natural lighting has a significance value p=0.002 (sig p<0.05), (4) Room humidity has a significance value p=0.003 (sig p<0.05), (5) Room temperature has a significance value p=0.491 (sig p>0.05), (6) house population density has a significance value p=0.123 (sig p>0.05), (7) Air population in the house has a significance value p=0.001(sig p<0.05). Based on the results of our study it can be concluded that the quality of house sanitation affect the event of acute respiratory infections (ARI) diseases. The variables of house sanitation that affect the event of ARI diseases are: room humidity (OR=0.321), air population in the house (OR= 0.233), natural lighting (OR= 0.151). Our study found that the probability of people who live in a house with below-standard-sanitationquality to be stricken by ARI diseases was 97.7%. Based on the results of our study it can be suggested that to the people that built the house of a qualified health.

Bayesian reasoning with ifs and ands and ors

The Bayesian approach to the psychology of reasoning generalizes binary logic, extending the binary concept of consistency to that of coherence, and allowing the study of deductive reasoning from uncertain premises. Studies in judgment and decision making have found that people’s probability judgments can fail to be coherent. We investigated people’s coherence further for judgments about conjunctions, disjunctions and conditionals, and asked whether their coherence would increase when they were given the explicit task of drawing inferences. Participants gave confidence judgments about a list of separate statements (the statements group) or the statements grouped as explicit inferences (the inferences group). Their responses were generally coherent at above chance levels for all the inferences investigated, regardless of the presence of an explicit inference task. An exception was that they were incoherent in the context known to cause the conjunction fallacy, and remained so even when they were given an explicit inference. The participants were coherent under the assumption that they interpreted the natural language conditional as it is represented in Bayesian accounts of conditional reasoning, but they were incoherent under the assumption that they interpreted the natural language conditional as the material conditional of elementary binary logic. Our results provide further support for the descriptive adequacy of Bayesian reasoning principles in the study of deduction under uncertainty.

Affinity based information diffusion model in social networks

There is a widespread intuitive sense that people prefer participating in spreading the information in which they are interested. The affinity of people with information disseminated can affect the information propagation in social networks. In this paper, we propose an information diffusion model incorporating the mechanism of affinity of people with information which considers the fitness of affinity values of people with affinity threshold of the information. We find that the final size of information diffusion is affected by affinity threshold of the information, average degree of the network and the probability of people's losing their interest in the information. We also explore the effects of other factors on information spreading by numerical simulations and find that the probabilities of people's questioning and confirming the information can affect the propagation speed, but not the final scope.