A cement factory nearby communities raise pollution concerns. This study assessed air pollution levels for respirable particulate matter (PM2.5 and PM10) and heavy metals (lead, chromium, nickel, cadmium, zinc and cop...A cement factory nearby communities raise pollution concerns. This study assessed air pollution levels for respirable particulate matter (PM2.5 and PM10) and heavy metals (lead, chromium, nickel, cadmium, zinc and copper) adjacent to a cement factory in Ewekoro and neighbouring communities (Papalantoro, Lapeleko and Itori) in Ogun State, Nigeria. Respirable particulate matter (PM2.5 and PM10) and heavy metals were measured using an ARA N-FRM cassette sampler. Each location sampled was monitored for eight continuous hours daily for 12 days. The PM2.5, PM10 and heavy metals results were compared with different standards, including those of the World Health Organization (WHO), Nigeria’s National Environmental Standard and Regulation Enforcement Agency (NESREA) and Canadian Ambient Air Quality Standards (CAAQS). The PM levels fell within 11 - 19 μg/m3 of the air management level of CAAQS, which signifies continuous actions are needed to improve air quality in the areas monitored but below the NESREA standard. The mean Cd, Cr and Ni concentrations in the cement factory area and the impacted neighbourhoods are higher than the WHO/EU permissible limits, while Zn and Cu were below the WHO/EU permissible limit. A risk assessment hazard quotient (HQ) for Cr was above the WHO/EU safe level (=1) in adults and children throµgh ingestion, inhalation and dermal contact at all the monitoring sites. The HQ for Ni and Cd was higher than the safe level in the cement factory area and Papalantoro, while Zn was at safe levels.展开更多
After an intensive few years of development,ACG Kinna Automatic and ACG Nystrom–members of TMAS,the Swedish textile machinery association–have delivered the first microfactory for the production of fully finished fi...After an intensive few years of development,ACG Kinna Automatic and ACG Nystrom–members of TMAS,the Swedish textile machinery association–have delivered the first microfactory for the production of fully finished filter bags to a major international filtration industry customer,in cooperation with JUKI Central Europe.展开更多
Objective:This study aimed to examine the causal model of eating behaviors among pregnant women working in industrial factories.Methods:This cross-sectional study was conducted on 210 participants,attending 4 healthca...Objective:This study aimed to examine the causal model of eating behaviors among pregnant women working in industrial factories.Methods:This cross-sectional study was conducted on 210 participants,attending 4 healthcare centers,at a tertiary care hospital in Chonburi province,Thailand.Data were collected using 7 questionnaires:demographic form,eating behavior questionnaire,perceived benefits of the healthy eating questionnaire,perceived barriers to the healthy eating questionnaire,perceived self-efficacy questionnaire,social support questionnaire,and accessibility to healthy foods questionnaire.Descriptive statistics and path analysis were used for data analysis.Results:The participants had relatively high mean scores for eating behaviors.The final model fitted well with the dataχ^(2)=12.86,df=10,P=0.23;χ^(2)/df=1.29;comparative fit index(CFI)=0.98;goodness-of-fit index(GFI)=0.98;adjusted goodness-of-fit index(AGFI)=0.95;root mean square error of approximation(RMSEA)=0.04.Four factors-perceived benefits(β=0.13,P<0.05),perceived self-efficacy in healthy eating(β=0.22,P<0.001),pregnancy planning(β=0.28,P<0.001),and accessibility to healthy foods in the factory(β=0.12,P<0.05)-positively affected eating behavior,while only perceived barriers to healthy eating had a negative effect on eating behavior(β=−0.24,P<0.001).All the above factors explained 27.2%of the variance in eating behaviors.Conclusions:Nurses or healthcare providers can apply these findings to create an eating behavior modification program,focusing on pregnancy planning,behavior-specific variables,and interpersonal and situational influence,to promote the nutritional status of pregnant women working in industrial factories.展开更多
Recently,to build a smart factory,research has been conducted to perform fault diagnosis and defect detection based on vibration and noise signals generated when a mechanical system is driven using deep-learning techn...Recently,to build a smart factory,research has been conducted to perform fault diagnosis and defect detection based on vibration and noise signals generated when a mechanical system is driven using deep-learning technology,a field of artificial intelligence.Most of the related studies apply various audio-feature extraction techniques to one-dimensional raw data to extract sound-specific features and then classify the sound by using the derived spectral image as a training dataset.However,compared to numerical raw data,learning based on image data has the disadvantage that creating a training dataset is very time-consuming.Therefore,we devised a two-step data preprocessing method that efficiently detects machine anomalies in numerical raw data.In the first preprocessing process,sound signal information is analyzed to extract features,and in the second preprocessing process,data filtering is performed by applying the proposed algorithm.An efficient dataset was built formodel learning through a total of two steps of data preprocessing.In addition,both showed excellent performance in the training accuracy of the model that entered each dataset,but it can be seen that the time required to build the dataset was 203 s compared to 39 s,which is about 5.2 times than when building the image dataset.展开更多
Experimentation has come a long in helping researchers achieve breakthroughs in their different scientific areas and engineering happens to be one of those areas with the most impact from experimental advancement. The...Experimentation has come a long in helping researchers achieve breakthroughs in their different scientific areas and engineering happens to be one of those areas with the most impact from experimental advancement. The need for valid experimental results free from biases and confounding conclusions has prompted the development of new experimental techniques that takes consideration of all applicable factor and combinations in providing answers on a research topic, and the Factorial Experimental design credited to Sir Ronald Fisher is one technique yielding highly valid results. This paper uses the factorial design of experiments to research the flexural impact of polyvinyl acetate fiber and layered concrete in construction. The experiment considered two levels of fiber contents and two levels of layers, and prepared samples with all combinations of the variable factors. The samples were tested after 7 days from casting for flexural strength and an advance statistical analysis was performed on the flexural responses of the samples using R-program. The results from the analyses revealed the significance of the variables to the flexural strength of the samples, as well as their interactions. The experiment concluded that based on the number of layers and fiber content used for the experiment, casting concrete in layers does have a significant negative effect on the flexural strength of concrete, and the failure pattern of concrete members under flexural load in evidently influenced by the material composition of the concrete, and that it can be evidently influenced by casting the concrete in layers.展开更多
From August 17 to 23,2023,the Yellow River Tourism Overseas Promotion Season 2023 launched the"Gansu Overseas Promotion Week"to present the Gansu Cultural Tourism Promotional Video,Gansu Intangible Cultural ...From August 17 to 23,2023,the Yellow River Tourism Overseas Promotion Season 2023 launched the"Gansu Overseas Promotion Week"to present the Gansu Cultural Tourism Promotional Video,Gansu Intangible Cultural Heritage Short Video and the"Symphony Silk Road and Satisfactory Gansu"-Gansu in Chinese Folk Music series of short videos to the global public.展开更多
文摘A cement factory nearby communities raise pollution concerns. This study assessed air pollution levels for respirable particulate matter (PM2.5 and PM10) and heavy metals (lead, chromium, nickel, cadmium, zinc and copper) adjacent to a cement factory in Ewekoro and neighbouring communities (Papalantoro, Lapeleko and Itori) in Ogun State, Nigeria. Respirable particulate matter (PM2.5 and PM10) and heavy metals were measured using an ARA N-FRM cassette sampler. Each location sampled was monitored for eight continuous hours daily for 12 days. The PM2.5, PM10 and heavy metals results were compared with different standards, including those of the World Health Organization (WHO), Nigeria’s National Environmental Standard and Regulation Enforcement Agency (NESREA) and Canadian Ambient Air Quality Standards (CAAQS). The PM levels fell within 11 - 19 μg/m3 of the air management level of CAAQS, which signifies continuous actions are needed to improve air quality in the areas monitored but below the NESREA standard. The mean Cd, Cr and Ni concentrations in the cement factory area and the impacted neighbourhoods are higher than the WHO/EU permissible limits, while Zn and Cu were below the WHO/EU permissible limit. A risk assessment hazard quotient (HQ) for Cr was above the WHO/EU safe level (=1) in adults and children throµgh ingestion, inhalation and dermal contact at all the monitoring sites. The HQ for Ni and Cd was higher than the safe level in the cement factory area and Papalantoro, while Zn was at safe levels.
文摘After an intensive few years of development,ACG Kinna Automatic and ACG Nystrom–members of TMAS,the Swedish textile machinery association–have delivered the first microfactory for the production of fully finished filter bags to a major international filtration industry customer,in cooperation with JUKI Central Europe.
文摘Objective:This study aimed to examine the causal model of eating behaviors among pregnant women working in industrial factories.Methods:This cross-sectional study was conducted on 210 participants,attending 4 healthcare centers,at a tertiary care hospital in Chonburi province,Thailand.Data were collected using 7 questionnaires:demographic form,eating behavior questionnaire,perceived benefits of the healthy eating questionnaire,perceived barriers to the healthy eating questionnaire,perceived self-efficacy questionnaire,social support questionnaire,and accessibility to healthy foods questionnaire.Descriptive statistics and path analysis were used for data analysis.Results:The participants had relatively high mean scores for eating behaviors.The final model fitted well with the dataχ^(2)=12.86,df=10,P=0.23;χ^(2)/df=1.29;comparative fit index(CFI)=0.98;goodness-of-fit index(GFI)=0.98;adjusted goodness-of-fit index(AGFI)=0.95;root mean square error of approximation(RMSEA)=0.04.Four factors-perceived benefits(β=0.13,P<0.05),perceived self-efficacy in healthy eating(β=0.22,P<0.001),pregnancy planning(β=0.28,P<0.001),and accessibility to healthy foods in the factory(β=0.12,P<0.05)-positively affected eating behavior,while only perceived barriers to healthy eating had a negative effect on eating behavior(β=−0.24,P<0.001).All the above factors explained 27.2%of the variance in eating behaviors.Conclusions:Nurses or healthcare providers can apply these findings to create an eating behavior modification program,focusing on pregnancy planning,behavior-specific variables,and interpersonal and situational influence,to promote the nutritional status of pregnant women working in industrial factories.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea Government(MSIT)(No.2021R1C1C1013133)funded by BK21 FOUR(Fostering Outstanding Universities for Research)(No.5199990914048)supported by the Soonchunhyang University Research Fund.
文摘Recently,to build a smart factory,research has been conducted to perform fault diagnosis and defect detection based on vibration and noise signals generated when a mechanical system is driven using deep-learning technology,a field of artificial intelligence.Most of the related studies apply various audio-feature extraction techniques to one-dimensional raw data to extract sound-specific features and then classify the sound by using the derived spectral image as a training dataset.However,compared to numerical raw data,learning based on image data has the disadvantage that creating a training dataset is very time-consuming.Therefore,we devised a two-step data preprocessing method that efficiently detects machine anomalies in numerical raw data.In the first preprocessing process,sound signal information is analyzed to extract features,and in the second preprocessing process,data filtering is performed by applying the proposed algorithm.An efficient dataset was built formodel learning through a total of two steps of data preprocessing.In addition,both showed excellent performance in the training accuracy of the model that entered each dataset,but it can be seen that the time required to build the dataset was 203 s compared to 39 s,which is about 5.2 times than when building the image dataset.
文摘Experimentation has come a long in helping researchers achieve breakthroughs in their different scientific areas and engineering happens to be one of those areas with the most impact from experimental advancement. The need for valid experimental results free from biases and confounding conclusions has prompted the development of new experimental techniques that takes consideration of all applicable factor and combinations in providing answers on a research topic, and the Factorial Experimental design credited to Sir Ronald Fisher is one technique yielding highly valid results. This paper uses the factorial design of experiments to research the flexural impact of polyvinyl acetate fiber and layered concrete in construction. The experiment considered two levels of fiber contents and two levels of layers, and prepared samples with all combinations of the variable factors. The samples were tested after 7 days from casting for flexural strength and an advance statistical analysis was performed on the flexural responses of the samples using R-program. The results from the analyses revealed the significance of the variables to the flexural strength of the samples, as well as their interactions. The experiment concluded that based on the number of layers and fiber content used for the experiment, casting concrete in layers does have a significant negative effect on the flexural strength of concrete, and the failure pattern of concrete members under flexural load in evidently influenced by the material composition of the concrete, and that it can be evidently influenced by casting the concrete in layers.
文摘From August 17 to 23,2023,the Yellow River Tourism Overseas Promotion Season 2023 launched the"Gansu Overseas Promotion Week"to present the Gansu Cultural Tourism Promotional Video,Gansu Intangible Cultural Heritage Short Video and the"Symphony Silk Road and Satisfactory Gansu"-Gansu in Chinese Folk Music series of short videos to the global public.
