scholarly journals Weather and Aggressive Behavior among Patients in Psychiatric Hospitals—An Exploratory Study

2020 ◽  
Vol 17 (23) ◽  
pp. 9121
Author(s):  
Jakub Lickiewicz ◽  
Katarzyna Piotrowicz ◽  
Patricia Paulsen Hughes ◽  
Marta Makara-Studzińska
Keyword(s):  
Aggressive Behavior ◽  
Meteorological Data ◽  
Rank Correlation ◽  
Psychiatric Hospitals ◽  
Weather Conditions ◽  
Mental Illnesses ◽  
Weather Factors ◽  
Coercive Measures ◽  
The Impact ◽  
The Relationship

Background: The number of meteoropaths, or people negatively affected by weather conditions, is rising dramatically. Meteoropathy is developing rapidly due to ever poorer adaptations of people to changes in weather conditions. Strong weather stimuli may not only exacerbate symptoms in people with diseases of the cardiovascular and respiratory systems but may also induce aggressive behavior. Researchers have shown that patients suffering from mental illnesses are most vulnerable to changes in the weather and postulate a connection between the seasons and aggressive behavior. Methods: The goal of the study was to analyze the relationship between coercive measures and weather factors. The researchers identified what meteorological conditions prevailed on days with an increased number of incidents of aggressive behavior leading to the use of physical coercion towards patients in a psychiatric hospital in Poland. In order to determine the impact of weather conditions on the frequency at which physical coercion measures were used, the hospital’s “coercion sheets” from 1 January 2015 to 31 March 2017 were analyzed. The data were correlated with meteorological data. In order to determine the relationship between the occurrence of specific weather conditions and the number of coercive interventions (N), researchers utilized Spearman’s rank correlation analysis together with two-dimensional scatter diagrams (dependency models), multiple regression, stepwise regression, frequencies, and conditional probability (%). Results: Lower barometric pressure and foehn wind increased aggressive behavior in patients that led to coercive measures. For temperature (positive correlation) and humidity (negative correlation), there was a poor but statistically significant correlation. Conclusions: Monitoring weather conditions might be useful in predicting and preventing aggression by patients who are susceptible to weather changes

scholarly journals Effect of ambient temperature on outpatient admission for osteoarthritis and rheumatoid arthritis in a subtropical Chinese city

2020 ◽  
Author(s):  
Desheng Zhao ◽  
Jian Cheng ◽  
Ping Bao ◽  
Yanwu Zhang ◽  
Fengjuan Liang ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Ambient Temperature ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Individual Characteristics ◽  
Effect Of Temperature ◽  
Temperature Decrease ◽  
Distributed Lag ◽  
The Impact ◽  
The Relationship

Abstract Background Current findings on the impact of weather conditions on osteoarthritis (OA) and rheumatoid arthritis (RA) are sparse and not conclusive. This study aimed to investigate the relationship between temperature change and OA/RA admission. Methods Daily OA/RA admission and meteorological data from 1 January 2014 to 31 December 2017 in Hefei, China, were collected. We quantified the relationship between ambient temperature and OA/RA admission using a distributed lag nonlinear model (DLNM). The effect modifications by gender and age were also examined. Results Sudden temperature decrease was significantly associated with RA admission (25th percentile of temperature versus 50th percentile of temperature), with the acute and largest effect at current days lag (RR: 1.063, 95%CI: 1.010–1.118). However, no association between temperature and OA admission was observed. When conducting subgroup analyses by individual characteristics, we found that females and patients aged 41–65 years were more vulnerable to temperature decrease than males, patients aged 0–40 and ≧ 66 years, respectively. Conclusions This study suggested that sudden temperature decrease was a risk factor for increase RA admission. Females and patients aged 41–65 years were particularly vulnerable to the effect of temperature decrease.

scholarly journals The modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo, China

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Rui Zhang ◽  
Yujie Meng ◽  
Hejia Song ◽  
Ran Niu ◽  
Yu Wang ◽  
...  
Keyword(s):  
Air Pollution ◽  
High Temperature ◽  
Air Pollutants ◽  
Meteorological Data ◽  
Effect Of Temperature ◽  
Distributed Lag ◽  
Modification Effect ◽  
Incidence Risk ◽  
The Impact ◽  
The Relationship

Abstract Background Although exposure to air pollution has been linked to many health issues, few studies have quantified the modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo, China. Methods The data of daily incidence of influenza and the relevant meteorological data and air pollution data in Ningbo from 2014 to 2017 were retrieved. Low, medium and high temperature layers were stratified by the daily mean temperature with 25th and 75th percentiles. The potential modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo was investigated through analyzing the effects of air pollutants stratified by temperature stratum using distributed lag non-linear model (DLNM). Stratified analysis by sex and age were also conducted. Results Overall, a 10 μg/m3 increment of O3, PM2.5, PM10 and NO2 could increase the incidence risk of influenza with the cumulative relative risk of 1.028 (95% CI 1.007, 1.050), 1.061 (95% CI 1.004, 1.122), 1.043 (95% CI 1.003, 1.085), and 1.118 (95% CI 1.028, 1.216), respectively. Male and aged 7–17 years were more sensitive to air pollutants. Through the temperature stratification analysis, we found that temperature could modify the impacts of air pollution on daily incidence of influenza with high temperature exacerbating the impact of air pollutants. At high temperature layer, male and the groups aged 0–6 years and 18–64 years were more sensitive to air pollution. Conclusion Temperature modified the relationship between air pollution and daily incidence of influenza and high temperature would exacerbate the effects of air pollutants in Ningbo.

scholarly journals It’s the Weather: Quantifying the Impact of Weather on Retail Sales

2021 ◽  
Author(s):  
Natalie Rose ◽  
Les Dolega
Keyword(s):  
Weather Condition ◽  
Weather Conditions ◽  
Influential Factor ◽  
Retail Sector ◽  
Retail Sales ◽  
Weather Impact ◽  
High Street ◽  
Sector Decision ◽  
The Impact ◽  
The Relationship

AbstractThe weather is considered as an influential factor on consumer purchasing behaviours and plays a significant role in many aspects of retail sector decision making. As a result, better understanding of the magnitude and nature of the influence of variable UK weather conditions can be beneficial to many retailers and other stakeholders. This study addresses the dearth of research in this area by quantifying the relationship between different weather conditions and trading outcomes. By employing comprehensive daily sales data for a major high street retailer with over 2000 stores across England and adopting a random forest methodology, the study quantifies the influence of various weather conditions on daily retail sales. Results indicate that weather impact is greatest in the summer and spring months and that wind is consistently found to be the most influential weather condition. The top five most weather-dependent categories cover a range of different product types, with health foods emerging as the most susceptible to the weather. Also, sales from out-of-town stores show a far more complex relationship with the weather than those from traditional high street stores with the regions London and the South East experiencing the greatest levels of influence. Various implications of these findings for retail stakeholders are discussed and the scope for further research outlined.

Farmers’ Capacity and Rice Productivity in Climate Change Adaptation in Central Lampung Regency, Indonesia

2021 ◽  
Vol 11 (4) ◽  
pp. 346-353
Author(s):  
Indah Listiana ◽  
Indah Nurmayasari ◽  
Rinaldi Bursan ◽  
Muher Sukmayanto ◽  
Helvi Yanfika ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Change Adaptation ◽  
Agricultural Sector ◽  
Rank Correlation ◽  
Performance Level ◽  
Crop Failure ◽  
Rice Productivity ◽  
Spearman Rank Correlation Analysis ◽  
The Impact ◽  
The Relationship

Climate change is an extreme natural change condition due to global warming that cannot be avoided, and will have a broad impact on various aspects of life, including the agricultural sector. The impact of climate change that occurs in the agricultural sector, namely flood and drought that cause plants to crop failure , is becoming greater, causing significant reduction in agricultural production, especially rice, requiring that farmers have the ability to adapt to climate change. The purposes of this study are to analyze the relationship between the performance level of agricultural extension workers and the capacity level of farmers in regard to climate change adaptation, and to analyze the relationship between the level of farmer capacity in climate change adaptation and rice productivity. The research was conducted in Central Lampung Regency in 2019 using a total of 100 rice farmers. The data analysis method used is Spearman rank correlation analysis. The results show that the performance level of agricultural instructors is significantly related to the level of knowledge capacity, attitude, and skills of farmers in climate change adaptation. Knowledge capacity, attitude, and skills of farmers in climate change adaptation are significantly related to rice productivity.

scholarly journals Reading the Mind in the Eyes Test: Relationship with Neurocognition and Facial Emotion Recognition in Non-Clinical Youths

2020 ◽  
Vol 17 (8) ◽  
pp. 835-839
Author(s):  
Eunchong Seo ◽  
Se Jun Koo ◽  
Ye Jin Kim ◽  
Jee Eun Min ◽  
Hye Yoon Park ◽  
...  
Keyword(s):  
Emotion Recognition ◽  
Bootstrap Method ◽  
Mental Illnesses ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Raven's Standard Progressive Matrices ◽  
The Mind ◽  
The Impact ◽  
The Relationship ◽  
Reasoning By Analogy

Objective The Reading the Mind in the Eyes Test (RMET) is a common measure of the Theory of Mind. Previous studies found a correlation between RMET performance and neurocognition, especially reasoning by analogy; however, the nature of this relationship remains unclear. Additionally, neurocognition was shown to play a significant role in facial emotion recognition. This study is planned to examine the nature of relationship between neurocognition and RMET performance, as well as the mediating role of facial emotion recognition.Methods One hundred fifty non-clinical youths performed the RMET. Reasoning by analogy was tested by Raven’s Standard Progressive Matrices (SPM) and facial emotion recognition was assessed by the Korean Facial Expressions of Emotion (KOFEE) test. The percentile bootstrap method was used to calculate the parameters of the mediating effects of facial emotion recognition on the relationship between SPM and RMET scores.Results SPM scores and KOFEE scores were both statistically significant predictors of RMET scores. KOFEE scores were found to partially mediate the impact of SPM scores on RMET scores.Conclusion These findings suggested that facial emotion recognition partially mediated the relationship between reasoning by analogy and social cognition. This study highlights the need for further research for individuals with serious mental illnesses.

scholarly journals Modeling Infection of Strawberry Flowers by Botrytis cinerea Using Field Data

2000 ◽  
Vol 90 (12) ◽  
pp. 1367-1374 ◽  
Author(s):  
Xiangming Xu ◽  
David C. Harris ◽  
Angela M. Berrie
Keyword(s):  
Vapor Pressure ◽  
Botrytis Cinerea ◽  
Vapor Pressure Deficit ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Gray Mold ◽  
Weather Variables ◽  
Infection Models ◽  
The Relationship ◽  
Field Plots

The incidence of strawberry flower infection by Botrytis cinerea was monitored in unsprayed field plots in three successive years together with meteorological data and numbers of conidia in the air. There were large differences in conidia numbers and weather conditions in the 3 years. Three sets of models were derived to relate inoculum and weather conditions to the incidence of flower infection; by inoculum only, by weather variables only, and by both inoculum and weather variables. All the models fitted the observed incidence satisfactorily. High inoculum led to more infection. Models using weather variables only gave more accurate predictions than models using inoculum only. Models using both weather variables and inoculum gave the best predictions, but the improvement over the models based on weather variables only was small. The relationship between incidence of flower infection and inoculum and weather variables was generally consistent between years. Of the weather variables examined, daytime vapor pressure deficit and nighttime temperature had the greatest effect in determining daily incidence of flower infection. Infection was favored by low day vapor pressure deficit and high night temperature. The accuracy and consistency of the weather-based models suggest they could be explored to assist in management of gray mold.

scholarly journals Powdery mildew infection dependent on weather factors in vineyards near Keszthely in 2008

2010 ◽  
Vol 16 (2) ◽  
Author(s):  
P. Taksony ◽  
E. Tarczal ◽  
K. Maráczi ◽  
I. J. Holb ◽  
L. Kocsis
Keyword(s):  
High Temperature ◽  
Powdery Mildew ◽  
Vitis Vinifera ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Vitis Vinifera L ◽  
Weather Factors ◽  
Vegetative Period ◽  
Favorable Conditions ◽  
Powdery Mildew Infection

Weather conditions are extremely influential on grapevine productivity and quality. High temperature and humidity makes favorable conditions for powdery mildew infection respectively. The meteorological data around Keszthely, Hungary show the vegetative period is dryer and warmer than it was closely hundred years ago. We examined the development of powdery mildew infection  on  two variet ies Vitis vinifera L. cv Italian Riesling and cv Merlot in relation with meteorological data. No primer infections were appeared in the vineyard. The year of 2008 was quite ideal for the accumulation of Erysiphe necator in the experimental vineyard. Although the dry summer can lower the infection, but if the high temperature is coupling with rainfall, the possibilities of powdery mildew infection is going to grow higher during the upcoming years.

scholarly journals Estimation of the impact of short-term fluctuations in inputs on temporally aggregated outputs of process-oriented models

2003 ◽  
Vol 5 (3) ◽  
pp. 169-180 ◽  
Author(s):  
Å. Forsman ◽  
C. Andersson ◽  
A. Grimvall ◽  
M. Hoffmann
Keyword(s):  
Root Zone ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Parametric Models ◽  
Time Lags ◽  
Least Squares Regression ◽  
Arable Soils ◽  
Time Step ◽  
Process Oriented ◽  
The Impact

Process-oriented models driven by highly resolved meteorological inputs and comprising a short internal time step are sometimes used to predict substance fluxes in air, soil and water over fairly long periods of time. To ascertain whether regression-based input–output analyses in such cases can provide adequate parametric models of the impact of daily and monthly fluctuations in inputs on annual outputs, we studied the SOIL/SOILN model of vertical transport of heat, water and nitrogen through arable soils. Annual leaching of nitrate from the root zone was regarded as the response variable, and regressors were selected from among the set of all linear combinations of daily or monthly values of five different meteorological inputs. We found that, although several of the underlying processes described by the SOIL/SOILN model are non-linear, both ordinary and partial least squares regression (OLS and PLS) identified the subsets of input variables with the strongest influence on the model output, and the dominating time lags between model inputs and outputs. Furthermore, highly resolved explanatory variables were a prerequisite for good performance of linear predictors of temporally aggregated outputs and, to discern the full dynamic behaviour of the model, it was necessary to analyse the response to artificially generated daily meteorological data representing a very large number of different weather conditions. PLS had one advantage over OLS: a smooth pattern in the regression coefficients facilitated physical interpretation of the derived impulse–response weights.

scholarly journals Exploring the Relationships between the Topological Characteristics of Subway Networks and Service Disruption Impact

2020 ◽  
Vol 12 (10) ◽  
pp. 3960 ◽  
Author(s):  
Zhiru Wang ◽  
Wubin Ma ◽  
Albert Chan
Keyword(s):  
Significant Relationship ◽  
Rank Correlation ◽  
Data Set ◽  
Service Interruption ◽  
Delay Duration ◽  
Topological Characteristics ◽  
Service Disruption ◽  
High Degree ◽  
The Impact ◽  
The Relationship

Although numerous studies have considered the topological characteristics and the impact of disruptions in subway systems, their results have not been verified by empirical data. To address this limitation, we used a data set containing 392 detailed records of disruptions to subway services in Beijing from 2011 to 2017. The Spearman rank correlation coefficient analysis results indicate that the delay duration exhibits no significant relationship with the topological characteristics, whereas the reverse is true for the relationship between the number of affected trains and the topological characteristics. The results also demonstrate that subway network expansion will not result in a paradox between convenience and vulnerability from an actual data perspective. Moreover, contrary to previous research results, no significant relationship was found to exist between service interruption impact and the transit and key bridge stations. However, a high degree of clustering, characterized by redundant tracks between neighbours, tends to provide protection against service disruption for stations. In terms of the spatial variation, the influence of the disruption is greater when the station is further from the centre of the line. These results can support sustainable design in subway network planning.

scholarly journals Impact of meteorological parameters on the Covid-19 incidence. The case of the city of Oran, Algeria.

2020 ◽  
Author(s):  
Farid RAHAL ◽  
Salima REZAK ◽  
Fatima Zohra BABA HAMED
Keyword(s):  
Meteorological Parameters ◽  
Rank Correlation ◽  
Weather Conditions ◽  
Spearman Rank Correlation ◽  
First Case ◽  
Maximum Temperatures ◽  
Autumn And Winter ◽  
The Impact ◽  
The City ◽  
Spearman Rank Correlation Test

Several studies have confirmed the impact of weather conditions on the evolution of the Covid-19 pandemic. We wanted to verify this phenomenon in the city of Oran in Algeria, which experienced its first case of Covid19 on March 19, 2020. The data studied are the new Covid19 cases, the average, minimum and maximum temperatures, as well as the relative humidity rate. A first analysis of the data with a Spearman rank correlation test did not yield significant results. Taking into account the average incubation period to adjust the data made it possible, during a second analysis, to show that the minimum temperature is significantly correlated with the new cases of Covid19 in Oran. This study can help establish prevention policies against Covid19, especially during fall in temperatures in autumn and winter.

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