scholarly journals APPLICATION OF THE BAYESIAN TRUST NETWORK AND MULTINOMIAL LOGISTIC REGRESSION TO PREDICT THE DEGREE OF CONTAMINATION OF AGRICULTURAL LAND

2021 ◽  
pp. 10-17
Author(s):  
В.К. Каличкин ◽  
К.Ю. Максимович ◽  
В.А. Шпак ◽  
Р.Р. Галимов ◽  
А.Л. Пакуль
Keyword(s):  
Logistic Regression ◽  
Agricultural Land ◽  
Multinomial Logistic Regression ◽  
High Reliability ◽  
Anthropogenic Factors ◽  
Degree Of Contamination ◽  
Trust Network ◽  
Air Temperatures ◽  
Statistical Sample

Исследованы возможности применения Байесовской сети доверия (БСД) и мультиномиальной логистической регрессии (МНЛР) для прогнозирования степени засоренности земель сельскохозяйственного назначения. Рассчитана вероятность превышения экономического порога вредоносности (ЭПВ) при участии обеих моделей. Выполнено моделирование влияния природных и антропогенных факторов с использованием БСД, а также осуществлен прогноз превышения ЭПВ по категориям с помощью МНЛР. Для обучения моделей использованы данные длительного многофакторного полевого опыта Кемеровского НИИСХ – филиала СФНЦА РАН. Учитывая особенности статистической выборки, определены основные предикторы моделей, влияющие на засоренность земель. Выбранными предикторами были агротехнические приемы (системы обработки почвы, предшественники) и агрометеорологические ресурсы (суммы активных температур воздуха, осадки). Объясненная часть дисперсии по мере Нэйджелкерка, составляет 80,9 %, что говорит о высоких прогностических возможностях применения МНЛР. Прогнозные результаты обеих моделей совпали в 79 % случаев, что указывает на достижение высоких показателей меры близости прогнозов по БСД и МНЛР. Обе модели показали достаточно высокую достоверность при верификации на эмпирических данных за прошлые годы и могут быть использованы в качестве инструмента для прогноза. Следующим этапом работы станет совместное использование БСД и МЛНР, которое может способствовать усилению достоинств обоих подходов и устранению недостатков отдельных из них. The possibilities of using the Bayesian Network of Trust (BSD) and multinomial logistic regression (MNLR) to predict the degree of contamination of agricultural land are investigated. The probability of exceeding the economic threshold of harmfulness (ETH) with the participation of both models is calculated. Modeling of the influence of natural and anthropogenic factors using BSD was carried out, and the forecast of the excess of ETH by category was carried out using MNLR. To train the models, data from a long–term multifactorial field experience of the Kemerovo Research Institute of Agricultural Sciences - branch of the SFSCA RAS were used. Taking into account the features of the statistical sample, the main predictors of the models affecting land contamination are determined. The selected predictors were agrotechnical techniques (tillage systems, precursors) and agrometeorological resources (sums of active air temperatures, precipitation). The explained part of the variance with the Nagelkerk measure is 80.9%, which indicates high prognostic possibilities of using MNLR. The forecast results of both models coincided in 79% of cases, which indicates the achievement of high indicators of the measure of proximity of forecasts for BSD and MNLR. Both models have shown sufficiently high reliability when verified on empirical data from previous years and can be used as a tool for forecasting. The next stage of the work will be the joint use of BSD and MDR, which can contribute to strengthening the advantages of both approaches and eliminating the shortcomings of some of them.

A long-term evaluation of Facebook for recruitment and retention in the ENDIA type 1 diabetes pregnancy-birth cohort study (Preprint)

2021 ◽  
Author(s):  
Kelly J McGorm ◽  
James David Brown ◽  
Rebecca Louise Thomson ◽  
Helena Oakey ◽  
Belinda Moore ◽  
...  
Keyword(s):  
Social Media ◽  
Type 1 Diabetes ◽  
Logistic Regression ◽  
Birth Cohort ◽  
Multinomial Logistic Regression ◽  
Sociodemographic Characteristics ◽  
Recruitment And Retention

BACKGROUND Recruitment and retention of research participants is challenging. Social media, particularly Facebook, has emerged as a tool for connecting with participants due to its high uptake in the community. The Environmental Determinants of Islet Autoimmunity (ENDIA) study is an Australia-wide prospective pregnancy-birth cohort following children who have a first-degree relative with type 1 diabetes (ACTRN1261300794707). A dedicated Facebook page was established for the ENDIA study in 2013 with the aim to enhance recruitment and support participant retention. OBJECTIVE The purpose of this investigation was to evaluate the long-term impact of Facebook as a recruitment and retention tool. The hypotheses were that (1) Facebook was an important source of referral to the ENDIA study, (2) the sociodemographic characteristics of participants recruited by Facebook would be different from those of participants recruited by other means (i.e., ‘conventional recruits’), and (3) recruitment by Facebook would be associated with long-term retention. We also evaluated the most effective types of Facebook content based on post engagement. METHODS Recruitment of 1511 ENDIA participants was completed in December 2019. Characteristics of participants recruited through Facebook were compared to conventional recruits using linear, logistic, and multinomial logistic regression models. A logistic regression model was used to determine the risk of study withdrawal. Data pertaining to 794 Facebook posts over 7.5 years from June 2013 until December 2020 were extracted using the Facebook ‘Insights’ function for thematic analysis. RESULTS Facebook was the third largest source of referral to the ENDIA study (300/1511; 19.9%) behind in-person clinics (500/1511, 33.1%) and healthcare professional referrals (347/1511, 23.0%). The ENDIA Facebook page had 2337 followers at the close of recruitment. Approximately 20% of these could be identified as participating parents. Facebook recruits were more frequently Australian-born (P<.001) enrolling postnatally (P=.01) and withdrew from the study at a significantly lower rate compared to conventional recruits (4.7% vs 12.3%; P<.001) after a median of follow-up of 3.3 years. CONCLUSIONS Facebook was a valuable recruitment tool for the ENDIA study and participants recruited through Facebook were three times less likely to withdraw during long-term follow-up. The sociodemographic characteristics of Facebook recruits were different to conventional recruits, but perhaps in unintended ways. Facebook content featuring stories and images of participants received the highest engagement despite the fact that most Facebook followers were not enrolled in the study. These findings should inform social media strategies for future cohort studies involving pregnant women and young families, and for type 1 diabetes risk studies. CLINICALTRIAL Australia New Zealand Clinical Trials Registry: ACTRN1261300794707 INTERNATIONAL REGISTERED REPORT RR2-https://doi.org/10.1186/1471-2431-13-124

scholarly journals Long-Term Effects of Anthropogenic Factors on Nonpoint Source Pollution in the Upper Reaches of the Yangtze River

2019 ◽  
Vol 11 (8) ◽  
pp. 2246 ◽  
Author(s):  
Xiaowen Ding ◽  
Lin Liu
Keyword(s):  
Point Source ◽  
Pollution Control ◽  
Yangtze River ◽  
Agricultural Land ◽  
Anthropogenic Factors ◽  
The Yangtze River ◽  
Long Term Effects ◽  
Point Source Pollution ◽  
Non Point Source Pollution

With the continuous enhancement of point source pollution control, non-point source (NPS) pollution has become an important factor in the deterioration of surface water quality. Meanwhile, due to the soaring global population, long-term effects of anthropogenic factors on non-point source pollution in large river basins have increasingly attracted worldwide attention. The Yangtze river is the largest river basin of China, and protecting its ecological environment has great significance on protecting the lifeline of the entire Yangtze river. In this study, the improved output coefficient and nutrient losses empirical model were used to conduct space–time simulations of non-point source pollution in the upper reaches of the Yangtze river (URYR) based on GIS during 1960–2003. This method reveals the anthropogenic effects of non-point source pollution in the upper reaches of the Yangtze river. The results indicate that the impacts of anthropogenic factors on dissolved pollutants increased significantly, while those on sediment and adsorbed pollutants increased first and then decreased during the simulation year. Agricultural land use and atmospheric deposition, as well as rural life, were the main sources of dissolved pollutants. In addition, dry land and paddy fields were the major sources of sediment and adsorbed pollutants. For the load intensities, the long-term effects of anthropogenic factors on dissolved pollutants increased rapidly, and those on the load intensity of sediment and adsorbed pollutants increased first and then decreased. Therefore, the study would propose some corresponding environmental management measures to strengthen environmental protection and non-point source pollution control in the upper reaches of the Yangtze river.

scholarly journals Social participation and the combination of future needs for long-term care and mortality among older Japanese people: a prospective cohort study from the Aichi Gerontological Evaluation Study (AGES)

BMJ Open ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. e030500 ◽  
Author(s):  
Sei Takahashi ◽  
Toshiyuki Ojima ◽  
Katsunori Kondo ◽  
Sayaka Shimizu ◽  
Shunichi Fukuhara ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Cohort Study ◽  
Prospective Cohort Study ◽  
Social Participation ◽  
Prospective Cohort ◽  
Long Term Care ◽  
Multinomial Logistic Regression ◽  
Evaluation Study ◽  
Term Care

ObjectivesOur study aimed to examine the longitudinal association between social participation and both mortality and the need for long-term care (LTC) simultaneously.DesignA prospective cohort study with 9.4 years of follow-up.SettingSix Japanese municipalities.ParticipantsThe participants were 15 313 people who did not qualify to receive LTC insurance at a baseline based on the data from the Aichi Gerontological Evaluation Study (AGES, 2003–2013). They received a questionnaire to measure social participation and other potential confounders. Social participation was defined as participating in at least one organisation from eight categories.Primary and secondary outcome measuresThe primary outcomes were classified into three categories at the end of the 9.4 years observational period: living without the need for LTC, living with the need for LTC and death. We estimated the adjusted OR (AOR) using multinomial logistic regression analyses with adjustment for possible confounders.ResultsThe primary analysis included 9741 participants. Multinomial logistic regression analysis revealed that social participation was associated with a significantly lower risk of the need for LTC (AOR 0.82, 95% CI 0.69 to 0.97) or death (AOR 0.78, 95% CI 0.70 to 0.88).ConclusionsSocial participation may be associated with a decreased risk of the need for LTC and mortality among elderly patients.

ASSESSMENT OF FACTORS OF LANDSCAPE CHANGE IN MOSAIC TYPE LANDSCAPE: A CASE STUDY OF VIDZEME, LATVIA

2016 ◽  
Author(s):  
Ivo Vinogradovs ◽  
Oļģerts Nikodemus ◽  
Guntis Tabors ◽  
Imants Krūze ◽  
Didzis Elferts
Keyword(s):  
Land Use ◽  
Logistic Regression ◽  
Landscape Structure ◽  
Landscape Change ◽  
Agricultural Land ◽  
Driving Forces ◽  
Multinomial Logistic Regression ◽  
Rural Landscape ◽  
Physical Factors ◽  
Remotely Sensed Data

Landscape change has been extensively documented throughout rural Europe over the past decades. The dominating tendencies are intensification of agriculture and land marginalization. In territories of former USSR radical land use changes have shattered rural landscape structure throughout the 20th century, which in many cases have led to land marginalization in form of abandonment of agricultural lands and subsequent uncontrolled afforestation. This process is especially evident in mosaic type landscapes – landscapes of small intertwining structure of patches of agricultural land and forests. The paper presents the results of the study based on application of multinomial logistic regression and cross-analysis using binary logistic regression in R of important physical factors of landscape structure such as land quality, soil texture, slope, as well as land use patch size. Additionally certain human induced factors such as distance to closest paved road, cadastral plot size and availability of Single Area Payments are added for more accurate assessment of the driving forces of landscape change and possible vectors for supplementary studies. Data was gathered in intensive field surveys combined with analysis of high quality remotely sensed data. Results show strong interrelationship of several analyzed factors and thus calls for attention to further development of methodology.

scholarly journals Impact of ascending aortic, hemiarch and arch repair on early and long-term outcomes in patients with Stanford A acute aortic dissection

2018 ◽  
Vol 12 (12) ◽  
pp. 327-340 ◽  
Author(s):  
Julia Merkle ◽  
Anton Sabashnikov ◽  
Antje-Christin Deppe ◽  
Mohamed Zeriouh ◽  
Johanna Maier ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Aortic Dissection ◽  
Hospital Mortality ◽  
Subgroup Analysis ◽  
Acute Aortic Dissection ◽  
Multinomial Logistic Regression ◽  
Ascending Aorta ◽  
Term Survival ◽  
Surgery Group

Background: Stanford A acute aortic dissection (AAD) is a life-threatening emergency associated with major morbidity and mortality. The aim of this study was to compare outcomes of three different surgical approaches in patients with Stanford A AAD. Methods: From January 2006 to March 2015 a total of 240 consecutive patients with diagnosed Stanford A AAD underwent elective, isolated surgical aortic repair in our centre. Patients were divided into three groups according to the extent of surgical repair: isolated replacement of the ascending aorta, hemiarch replacement and total arch replacement. Patients were followed up for up to 9 years. After univariate analysis multinomial logistic regression was performed for subgroup analysis. Baseline characteristics and endpoints as well as long-term survival were analysed. Results: There were no statistically significant differences among the three groups in terms of demographics and preoperative baseline and clinical characteristics. Incidence of in-hospital stroke ( p = 0.034), need for reopening due to bleeding ( p = 0.031) and in-hospital mortality ( p = 0.017) increased significantly with the extent of the surgical approach. There was no statistical difference in terms of long-term survival ( p = 0.166) among the three groups. Applying multinomial logistic regression for subgroup analysis significantly higher odds for stroke ( p = 0.023), reopening for bleeding ( p = 0.010) and in-hospital mortality ( p = 0.009) for the arch surgery group in comparison to the ascending aorta surgery group as well as significantly higher odds for stroke ( p = 0.029) for the total arch surgery group in comparison to the hemiarch surgery group were identified. Conclusions: With Stanford A AAD the incidence of perioperative complications increased significantly with the extent of the surgical approach. Subgroup analysis and long-term follow up in patients undergoing isolated ascending or hemiarch surgery showed a lower incidence of cerebrovascular events compared with surgery for total arch replacement.

On the dynamics of distribution of the American White Butterfly, Hyphantria cunea Drury, 1973 (Lepidoptera, Arctiidae), in Ukraine regarding the annual minimal air temperatures

2018 ◽  
Vol 14 (1) ◽  
pp. 44-57
Author(s):  
S. N. Shumov
Keyword(s):  
Air Temperature ◽  
Annual Reports ◽  
Complete Elimination ◽  
Hyphantria Cunea ◽  
White American ◽  
Gis Technologies ◽  
Data Analyses ◽  
Air Temperatures ◽  
Negative Temperatures

The spatial analysis of distribution and quantity of Hyphantria cunea Drury, 1973 across Ukraine since 1952 till 2016 regarding the values of annual absolute temperatures of ground air is performed using the Gis-technologies. The long-term pest dissemination data (Annual reports…, 1951–1985; Surveys of the distribution of quarantine pests ..., 1986–2017) and meteorological information (Meteorological Yearbooks of air temperature the surface layer of the atmosphere in Ukraine for the period 1951-2016; Branch State of the Hydrometeorological Service at the Central Geophysical Observatory of the Ministry for Emergencies) were used in the present research. The values of boundary negative temperatures of winter diapause of Hyphantria cunea, that unable the development of species’ subsequent generation, are received. Data analyses suggests almost complete elimination of winter diapausing individuals of White American Butterfly (especially pupae) under the air temperature of −32°С. Because of arising questions on the time of action of absolute minimal air temperatures, it is necessary to ascertain the boundary negative temperatures of winter diapause for White American Butterfly. It is also necessary to perform the more detailed research of a corresponding biological material with application to the freezing technics, giving temperature up to −50°С, with the subsequent analysis of the received results by the punched-analysis.

Analysis of Long-term Changes of Days with 25℃ or Higher Air Temperatures in Jeju

2016 ◽  
Vol 7 (1) ◽  
pp. 31 ◽  
Author(s):  
Jae-Won Choi ◽  
Yumi Cha ◽  
Jeoung-Yun Kim ◽  
Cheol-Hong Park
Keyword(s):  
Air Temperatures ◽  
Long Term Changes

Public knowledge, perception and communication behavior surrounding COVID-19 in Malaysia

2020 ◽  
Author(s):  
Khayriyyah Mohd Hanafiah ◽  
Chang Da Wan
Keyword(s):  
Logistic Regression ◽  
Employment Status ◽  
Multinomial Logistic Regression ◽  
Movement Control ◽  
Education Level ◽  
Public Knowledge ◽  
Communication Behavior ◽  
Positive Communication ◽  
The Face ◽  
Control Order

The COVID-19 pandemic is the first to occur in an age of hyperconnectivity. This paper presents results from an online anonymous survey conducted in Malay, English, and Chinese, during the first week of the Movement Control Order in Malaysia (n=1075), which aimed to examine public knowledge, perception and communication behavior in the Malaysian society in the face of a sudden outbreak and social distancing measures. Although the level of public knowledge, risk perception and positive communication behavior surrounding COVID-19 was high, a majority of respondents reported receiving a lot of questionable information. Multinomial logistic regression further identified that responses to different items varied significantly across respondent survey language, gender, age, education level and employment status.

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