Area Sampling Frames （ASFs） are the basis of many statistical programs around the world. To improve the accuracy, objectivity and efficiency of crop survey estimates, an automated stratification method based on geos...Area Sampling Frames （ASFs） are the basis of many statistical programs around the world. To improve the accuracy, objectivity and efficiency of crop survey estimates, an automated stratification method based on geospatial crop planting frequency and cultivation data is proposed. This paper investigates using 2008-2013 geospatial corn, soybean and wheat planting frequency data layers to create three corresponding single crop specific and one multi-crop specific South Dakota （SD） U.S. ASF stratifications. Corn, soybeans and wheat are three major crops in South Dakota. The crop specific ASF stratifications are developed based on crop frequency statistics derived at the primary sampling unit （PSU） level based on the Crop Frequency Data Layers. The SD corn, soybean and wheat mean planting frequency strata of the single crop stratifications are substratified by percent cultivation based on the 2013 Cultivation Layer. The three newly derived ASF stratifications provide more crop specific information when compared to the current National Agricultural Statistics Service （NASS） ASF based on percent cultivation alone. Further, a multi-crop stratification is developed based on the individual corn, soybean and wheat planting frequency data layers. It is observed that all four crop frequency based ASF stratifications consistently predict corn, soybean and wheat planting patterns well as verified by the 2014 Farm Service Agency （FSA） Common Land Unit （CLU） and 578 administrative data. This demonstrates that the new stratifications based on crop planting frequency and cultivation are crop type independent and applicable to all major crops. Further, these results indicate that the new crop specific ASF stratifications have great potential to improve ASF accuracy, efficiency and crop estimates.展开更多
Agricultural geospatial information is critical for agricultural policy formulation and decision making, land use monitoring, agricultural sustainability, crop acreage and yield estimation, disaster assessment, bioene...Agricultural geospatial information is critical for agricultural policy formulation and decision making, land use monitoring, agricultural sustainability, crop acreage and yield estimation, disaster assessment, bioenergy crop inventory, food security policy, environmental assessment, carbon accounting, and other research topics that are of vital importance to agricul- ture and economy. Remote sensing technology enables us to collect, process, and analyze remotely sensed data and to retrieve, synthesize, visualize valuable geospatial information for agriculture uses. Specifically, remote sensing technology empowers capability for large scale field level or regional assessment and monitoring of crop land cover,展开更多
Phosphorus (P) risk indices are commonly used in the USA to estimate the field-scale risk of agricultural P runoff. Because the Ohio P Risk Index is increasingly being used to judge farmer performance, it is important...Phosphorus (P) risk indices are commonly used in the USA to estimate the field-scale risk of agricultural P runoff. Because the Ohio P Risk Index is increasingly being used to judge farmer performance, it is important to evaluate weighting/scoring of all P Index parameters to ensure Ohio farmers are credited for practices that reduce P runoff risk and not unduly penalized for things not demonstrably related to runoff risk. A sensitivity analysis provides information as to how sensitive the P Index score is to changes in inputs. The objectives were to determine 1) which inputs are most highly associated with P Index scores and 2) the relative impact of each input variable on resultant P Index scores. The current approach uses simulations across 6134 Ohio point locations and five crop management scenarios (CMSs), representing increasing soil disturbance. The CMSs range from all no-till, which is being promoted in Ohio, rotational tillage, which is a common practice in Ohio to full tillage to represent an extreme practice. Results showed that P Index scores were best explained by soil test P (31.9%) followed by connectivity to water (29.7%), soil erosion (13.4%), fertilizer application amount (11.3%), runoff class (9.5%), fertilizer application method (2.2%), and finally filter strip (2.0%). Ohio P Index simulations across CMSs one through five showed that >40% scored <15 points (low) while <1.5% scored >45 points (very high). Given Ohio water quality problems, the Ohio P Index needs to be stricter. The current approach is useful for Ohio P Index evaluations and revision decisions by spatially illustrating the impact of potential changes regionally and state-wide.展开更多
<strong>Purpose:</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"> This study sought to review the characteristics, strengths, weak...<strong>Purpose:</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"> This study sought to review the characteristics, strengths, weaknesses variants, applications areas and data types applied on the various </span><span><span style="font-family:Verdana;">Dimension Reduction techniques. </span><b><span style="font-family:Verdana;">Methodology: </span></b><span style="font-family:Verdana;">The most commonly used databases employed to search for the papers were ScienceDirect, Scopus, Google Scholar, IEEE Xplore and Mendeley. An integrative review was used for the study where </span></span></span><span style="font-family:Verdana;">341</span><span style="font-family:;" "=""><span style="font-family:Verdana;"> papers were reviewed. </span><b><span style="font-family:Verdana;">Results:</span></b><span style="font-family:Verdana;"> The linear techniques considered were Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Singular Value Decomposition (SVD), Latent Semantic Analysis (LSA), Locality Preserving Projections (LPP), Independent Component Analysis (ICA) and Project Pursuit (PP). The non-linear techniques which were developed to work with applications that ha</span></span><span style="font-family:Verdana;">ve</span><span style="font-family:Verdana;"> complex non-linear structures considered were Kernel Principal Component Analysis (KPC</span><span style="font-family:Verdana;">A), Multi</span><span style="font-family:Verdana;">-</span><span style="font-family:;" "=""><span style="font-family:Verdana;">dimensional Scaling (MDS), Isomap, Locally Linear Embedding (LLE), Self-Organizing Map (SOM), Latent Vector Quantization (LVQ), t-Stochastic </span><span style="font-family:Verdana;">neighbor embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP). DR techniques can further be categorized into supervised, unsupervised and more recently semi-supervised learning methods. The supervised versions are the LDA and LVQ. All the other techniques are unsupervised. Supervised variants of PCA, LPP, KPCA and MDS have </span><span style="font-family:Verdana;">been developed. Supervised and semi-supervised variants of PP and t-SNE have also been developed and a semi supervised version of the LDA has been developed. </span><b><span style="font-family:Verdana;">Conclusion:</span></b><span style="font-family:Verdana;"> The various application areas, strengths, weaknesses and variants of the DR techniques were explored. The different data types that have been applied on the various DR techniques were also explored.</span></span>展开更多
We present a unified approach to describing and linking several methods for representing categorical data in a contingency table. These methods include: correspondence analysis, Hellinger distance analysis, the log-ra...We present a unified approach to describing and linking several methods for representing categorical data in a contingency table. These methods include: correspondence analysis, Hellinger distance analysis, the log-ratio alternative, which is appropriate for compositional data, and the non-symmetrical correspondence analysis. We also present two solutions working with cummulative frequencies.展开更多
Habitual fish consumption is associated with numerous health benefits;however, in Australia fish intake remains low. The aim of this study was to compare the effect of specific or general fish consumption recommendati...Habitual fish consumption is associated with numerous health benefits;however, in Australia fish intake remains low. The aim of this study was to compare the effect of specific or general fish consumption recommendations on fish intake behavior over the duration of a 12-month clinical trial. Participants were randomized into a control group (general dietary advice), and two intervention groups (received dietetic advice to consume 180 g fish/wk), with one intervention group receiving LC omega-3 PUFA supplements. Dietary data was available for n = 117 at baseline, n = 85 at 3 months and n = 63 at 12 months. Total, fatty and lean fish intake (g/day) was calculated, and the change in fish intake between and within groups over the duration of the study was measured. Total fish consumption did not differ significantly between groups or within groups, however fatty fish intake was significantly greater in the intervention groups at three months (p = 0.004). The proportion of study participants complying with fish intake recommendations was also highest at the three month time point for both intervention groups. Overall, compliance to fish intake recommendations was highest at the three month time point and appeared to be influenced by dietetic intervention. Provision of fish may increase compliance in future studies, however if research is to be translated to practice, behavioral approaches are required to increase fish intake in the long term.展开更多
An Australian food composition database, AUSNUT1999, does not include long chain omega-3 polyunsaturated fatty acid （LC omega-3 PUFA） data. Measurement of the fatty acid content of diets initially analysed using AUS...An Australian food composition database, AUSNUT1999, does not include long chain omega-3 polyunsaturated fatty acid （LC omega-3 PUFA） data. Measurement of the fatty acid content of diets initially analysed using AUSNUT1999 requires conversion to AUSNUT2007, an updated database inclusive of LC omega-3 PUFA. The aim of this study was to convert clinical trial dietary data from AUSNUT1999 to AUSNUT2007 and measure LC omega-3 PUFA intake. Clinical trial diet history （DH） data was converted from AUSNUTI999 to 2007 using a staged approach. Macronutrient intake from AUSNUTI999 and 2007 were calculated and compared via paired t-tests and Wilcoxon Signed Ranks tests. Mean dietary LC omega-3 PUFA intake and the percentage contribution of food groups to total LC omega-3 PUFA were then calculated. DHs were collected at baseline （n = 118）, three months （n = 86）, and 12 months （n = 64）. The accuracy of the conversion process improved with time, with no significant difference between most macronutrients at 12 months. Mean LC n-3 PUFA intake was 441.87 mg at baseline, 521.07 mg at 3 months, and 442.40 mg at 12 months, and was predominantly provided by fish and seafood, followed by meat products. This study allowed for the measurement of LC omega-3 intake, which was previously impossible using the AUSNUT 1999 database.展开更多
In many countries, traffic volumes and the number of drivers are rising faster than the availability of police officers whose routine duties include traffic law enforcement. Automated traffic enforcement, which produc...In many countries, traffic volumes and the number of drivers are rising faster than the availability of police officers whose routine duties include traffic law enforcement. Automated traffic enforcement, which produces photographic evidence of vehicles detected speeding or running red lights, can be used to supplement traditional enforcement. In the United States and Canada, a number of individuals and organizations have been very vocal in their opposition to automated traffic enforcement. They argue that automated enforcement programs are unnecessary for improving road safety, that they unfairly target relatively good drivers, and that they are motivated by revenue generation rather than safety. These arguments, however, often ignore the numerous peer-reviewed studies that have found real-world benefits in communities that use automated enforcement---cameras deter would-be violators, reduce crashes, and save lives. Solid, published research by a number of experts demonstrates that red light cameras save lives, and speed cameras substantially reduce speeding and speed-related crashes. Surveys of drivers and other road users indicate widespread support for automated enforcement. With regard to fairness, the objective of photo enforcement is to deter violations, not to surreptitiously catch violators. The more public the enforcement is, the better. If anything, automated enforcement programs improve fairness by reducing the potential for prejudicial enforcement. Finally, photo enforcement is intended to improve traffic safety by modifying the driver behaviors that lead to crashes, and it is reasonable to expect that people who break the law should pay for enforcing it. Ticket revenue should decline overtime as the cameras succeed in deterring would-be speeders and red light runners. This paper provides research-based responses to the critics＇ arguments as well as best practice guidelines for effective automated enforcement programs.展开更多
Increasing forage proportion(FP)in the diets of dairy cows would reduce competition for human edible foods and reduce feed costs,particularly in low-input systems.However,increasing FP reduces productivity and may inc...Increasing forage proportion(FP)in the diets of dairy cows would reduce competition for human edible foods and reduce feed costs,particularly in low-input systems.However,increasing FP reduces productivity and may increases methane(CH4)emission parameters.This work aimed to investigate the impact of FP and breed on feed efficiency and CH4 emission parameters.Data from 32 individual experiments conducted at the Agri-Food and Biosciences Institute between 1992 and 2010 were utilised in this study resulting in data from 796 Holstein-Friesian(HF),50 Norwegian Red(NR),46 JerseyHF(JHF)and 16 NRHF cows.Diets consisted of varying proportions of forage and concentrate dependent on the experimental protocols of each experiment.A linear mixed model was used to investigate the effect of low(LFP;10%to 30%),medium(MFP;30%to 59%),high(HFP;60%to 87%)and pure(FOR;100%)FP(dry matter[DM]basis)and breed on feed efficiency,and CH4 emission parameters and multivariate redundancy analysis identified associations between animal and dietary drivers on the same variables.Total dry matter intake(DMI)was higher for cows offered LFP(17.3 kg/d)and MFP(17.9 kg/d)compared to HFP(15.3 kg/d)and FOR(13.8 kg/d)(P<0.001).Milk yield(P<0.001),milk yield/DMI(P<0.001),energy corrected milk(ECM)/DMI(P<0.001)and milk energy/DMI(P<0.001)were higher for LFP and MFP compared to HFP and FOR.Methane/DMI was higher for HFP(24.3 g/kg)compared to MFP(22.4 g/kg)(P<0.001).Methane/milk yield(P<0.001)or CH4/ECM(P<0.001)was higher for HFP(22.5 or 21.6 g/kg)and FOR(27.0 or 25.8 g/kg)compared to MFP(19.1 or 17.9 g/kg).There were no differences between LFP and MFP or between HFP and FOR for milk yield,milk yield/DMI,ECM/DMI,milk energy/DMI,CH4/milk yield and CH4/ECM(P>0.05).Differences existed between breeds for residual feed intake(P=0.040),milk yield/DMI(P=0.041)and CH4/DMI(P=0.048)with multivariate redundancy analysis demonstrating negative correlations with efficiency and positive correlations with CH4/DMI and CH4/milk yield.Feeding concentrates at 70%to 90%of DMI(LFP group)would not result in any further benefits for productivity,feed efficiency or CH4 yield and intensity when compared to feeding 41%to 70%concentrates of DMI(MFP group).There may be opportunity to improve profitability for lower intensity farms with less concentrate input.展开更多
Background:Malaria remains a significant public health concern in Ghana,with varying risk levels across different geographical areas.Malaria affects millions of people each year and imposes a substantial burden on the...Background:Malaria remains a significant public health concern in Ghana,with varying risk levels across different geographical areas.Malaria affects millions of people each year and imposes a substantial burden on the health care system and population.Accurate risk estimation and mapping are crucial for effectively allocating resources and implementing targeted interventions to identify regions with disease hotspots.This study aimed to identify regions exhibiting elevated malaria risk so that public health interventions can be implemented,and to identify malaria risk predictors that can be controlled as part of public health interventions for malaria control.Methods:The data on laboratory-confirmed malaria cases from 2015 to 2021 were obtained from the Ghana Health Service and Ghana Statistical Service.We studied the spatial and spatiotemporal patterns of the relative risk of malaria using Bayesian spatial and spatiotemporal models.The malaria risk for each region was mapped to visually identify regions with malaria hotspots.Clustering and heterogeneity of disease risks were established using correlated and uncorrelated structures via the conditional autoregressive and Gaussian models,respectively.Parameter estimates from the marginal posterior distribution were estimated within the Integrated Nested Laplace Approximation using the R software.Results:The spatial model indicated an increased risk of malaria in the North East,Bono East,Ahafo,Central,Upper West,Brong Ahafo,Ashanti,and Eastern regions.The spatiotemporal model results highlighted an elevated malaria risk in the North East,Upper West,Upper East,Savannah,Bono East,Central,Bono,and Ahafo regions.Both spatial and spatiotemporal models identified the North East,Upper West,Bono East,Central,and Ahafo Regions as hotspots for malaria risk.Substantial variations in risk were evident across regions(H=104.9,P<0.001).Although climatic and economic factors influenced malaria infection,statistical significance was not established.Conclusions:Malaria risk was clustered and varied among regions in Ghana.There are many regions in Ghana that are hotspots for malaria risk,and climate and economic factors have no significant influence on malaria risk.This study could provide information on malaria transmission patterns in Ghana,and contribute to enhance the effectiveness of malaria control strategies.展开更多
文摘Area Sampling Frames （ASFs） are the basis of many statistical programs around the world. To improve the accuracy, objectivity and efficiency of crop survey estimates, an automated stratification method based on geospatial crop planting frequency and cultivation data is proposed. This paper investigates using 2008-2013 geospatial corn, soybean and wheat planting frequency data layers to create three corresponding single crop specific and one multi-crop specific South Dakota （SD） U.S. ASF stratifications. Corn, soybeans and wheat are three major crops in South Dakota. The crop specific ASF stratifications are developed based on crop frequency statistics derived at the primary sampling unit （PSU） level based on the Crop Frequency Data Layers. The SD corn, soybean and wheat mean planting frequency strata of the single crop stratifications are substratified by percent cultivation based on the 2013 Cultivation Layer. The three newly derived ASF stratifications provide more crop specific information when compared to the current National Agricultural Statistics Service （NASS） ASF based on percent cultivation alone. Further, a multi-crop stratification is developed based on the individual corn, soybean and wheat planting frequency data layers. It is observed that all four crop frequency based ASF stratifications consistently predict corn, soybean and wheat planting patterns well as verified by the 2014 Farm Service Agency （FSA） Common Land Unit （CLU） and 578 administrative data. This demonstrates that the new stratifications based on crop planting frequency and cultivation are crop type independent and applicable to all major crops. Further, these results indicate that the new crop specific ASF stratifications have great potential to improve ASF accuracy, efficiency and crop estimates.
文摘Agricultural geospatial information is critical for agricultural policy formulation and decision making, land use monitoring, agricultural sustainability, crop acreage and yield estimation, disaster assessment, bioenergy crop inventory, food security policy, environmental assessment, carbon accounting, and other research topics that are of vital importance to agricul- ture and economy. Remote sensing technology enables us to collect, process, and analyze remotely sensed data and to retrieve, synthesize, visualize valuable geospatial information for agriculture uses. Specifically, remote sensing technology empowers capability for large scale field level or regional assessment and monitoring of crop land cover,
文摘Phosphorus (P) risk indices are commonly used in the USA to estimate the field-scale risk of agricultural P runoff. Because the Ohio P Risk Index is increasingly being used to judge farmer performance, it is important to evaluate weighting/scoring of all P Index parameters to ensure Ohio farmers are credited for practices that reduce P runoff risk and not unduly penalized for things not demonstrably related to runoff risk. A sensitivity analysis provides information as to how sensitive the P Index score is to changes in inputs. The objectives were to determine 1) which inputs are most highly associated with P Index scores and 2) the relative impact of each input variable on resultant P Index scores. The current approach uses simulations across 6134 Ohio point locations and five crop management scenarios (CMSs), representing increasing soil disturbance. The CMSs range from all no-till, which is being promoted in Ohio, rotational tillage, which is a common practice in Ohio to full tillage to represent an extreme practice. Results showed that P Index scores were best explained by soil test P (31.9%) followed by connectivity to water (29.7%), soil erosion (13.4%), fertilizer application amount (11.3%), runoff class (9.5%), fertilizer application method (2.2%), and finally filter strip (2.0%). Ohio P Index simulations across CMSs one through five showed that >40% scored <15 points (low) while <1.5% scored >45 points (very high). Given Ohio water quality problems, the Ohio P Index needs to be stricter. The current approach is useful for Ohio P Index evaluations and revision decisions by spatially illustrating the impact of potential changes regionally and state-wide.
文摘<strong>Purpose:</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"> This study sought to review the characteristics, strengths, weaknesses variants, applications areas and data types applied on the various </span><span><span style="font-family:Verdana;">Dimension Reduction techniques. </span><b><span style="font-family:Verdana;">Methodology: </span></b><span style="font-family:Verdana;">The most commonly used databases employed to search for the papers were ScienceDirect, Scopus, Google Scholar, IEEE Xplore and Mendeley. An integrative review was used for the study where </span></span></span><span style="font-family:Verdana;">341</span><span style="font-family:;" "=""><span style="font-family:Verdana;"> papers were reviewed. </span><b><span style="font-family:Verdana;">Results:</span></b><span style="font-family:Verdana;"> The linear techniques considered were Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Singular Value Decomposition (SVD), Latent Semantic Analysis (LSA), Locality Preserving Projections (LPP), Independent Component Analysis (ICA) and Project Pursuit (PP). The non-linear techniques which were developed to work with applications that ha</span></span><span style="font-family:Verdana;">ve</span><span style="font-family:Verdana;"> complex non-linear structures considered were Kernel Principal Component Analysis (KPC</span><span style="font-family:Verdana;">A), Multi</span><span style="font-family:Verdana;">-</span><span style="font-family:;" "=""><span style="font-family:Verdana;">dimensional Scaling (MDS), Isomap, Locally Linear Embedding (LLE), Self-Organizing Map (SOM), Latent Vector Quantization (LVQ), t-Stochastic </span><span style="font-family:Verdana;">neighbor embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP). DR techniques can further be categorized into supervised, unsupervised and more recently semi-supervised learning methods. The supervised versions are the LDA and LVQ. All the other techniques are unsupervised. Supervised variants of PCA, LPP, KPCA and MDS have </span><span style="font-family:Verdana;">been developed. Supervised and semi-supervised variants of PP and t-SNE have also been developed and a semi supervised version of the LDA has been developed. </span><b><span style="font-family:Verdana;">Conclusion:</span></b><span style="font-family:Verdana;"> The various application areas, strengths, weaknesses and variants of the DR techniques were explored. The different data types that have been applied on the various DR techniques were also explored.</span></span>
文摘We present a unified approach to describing and linking several methods for representing categorical data in a contingency table. These methods include: correspondence analysis, Hellinger distance analysis, the log-ratio alternative, which is appropriate for compositional data, and the non-symmetrical correspondence analysis. We also present two solutions working with cummulative frequencies.
文摘Habitual fish consumption is associated with numerous health benefits;however, in Australia fish intake remains low. The aim of this study was to compare the effect of specific or general fish consumption recommendations on fish intake behavior over the duration of a 12-month clinical trial. Participants were randomized into a control group (general dietary advice), and two intervention groups (received dietetic advice to consume 180 g fish/wk), with one intervention group receiving LC omega-3 PUFA supplements. Dietary data was available for n = 117 at baseline, n = 85 at 3 months and n = 63 at 12 months. Total, fatty and lean fish intake (g/day) was calculated, and the change in fish intake between and within groups over the duration of the study was measured. Total fish consumption did not differ significantly between groups or within groups, however fatty fish intake was significantly greater in the intervention groups at three months (p = 0.004). The proportion of study participants complying with fish intake recommendations was also highest at the three month time point for both intervention groups. Overall, compliance to fish intake recommendations was highest at the three month time point and appeared to be influenced by dietetic intervention. Provision of fish may increase compliance in future studies, however if research is to be translated to practice, behavioral approaches are required to increase fish intake in the long term.
文摘An Australian food composition database, AUSNUT1999, does not include long chain omega-3 polyunsaturated fatty acid （LC omega-3 PUFA） data. Measurement of the fatty acid content of diets initially analysed using AUSNUT1999 requires conversion to AUSNUT2007, an updated database inclusive of LC omega-3 PUFA. The aim of this study was to convert clinical trial dietary data from AUSNUT1999 to AUSNUT2007 and measure LC omega-3 PUFA intake. Clinical trial diet history （DH） data was converted from AUSNUTI999 to 2007 using a staged approach. Macronutrient intake from AUSNUTI999 and 2007 were calculated and compared via paired t-tests and Wilcoxon Signed Ranks tests. Mean dietary LC omega-3 PUFA intake and the percentage contribution of food groups to total LC omega-3 PUFA were then calculated. DHs were collected at baseline （n = 118）, three months （n = 86）, and 12 months （n = 64）. The accuracy of the conversion process improved with time, with no significant difference between most macronutrients at 12 months. Mean LC n-3 PUFA intake was 441.87 mg at baseline, 521.07 mg at 3 months, and 442.40 mg at 12 months, and was predominantly provided by fish and seafood, followed by meat products. This study allowed for the measurement of LC omega-3 intake, which was previously impossible using the AUSNUT 1999 database.
文摘In many countries, traffic volumes and the number of drivers are rising faster than the availability of police officers whose routine duties include traffic law enforcement. Automated traffic enforcement, which produces photographic evidence of vehicles detected speeding or running red lights, can be used to supplement traditional enforcement. In the United States and Canada, a number of individuals and organizations have been very vocal in their opposition to automated traffic enforcement. They argue that automated enforcement programs are unnecessary for improving road safety, that they unfairly target relatively good drivers, and that they are motivated by revenue generation rather than safety. These arguments, however, often ignore the numerous peer-reviewed studies that have found real-world benefits in communities that use automated enforcement---cameras deter would-be violators, reduce crashes, and save lives. Solid, published research by a number of experts demonstrates that red light cameras save lives, and speed cameras substantially reduce speeding and speed-related crashes. Surveys of drivers and other road users indicate widespread support for automated enforcement. With regard to fairness, the objective of photo enforcement is to deter violations, not to surreptitiously catch violators. The more public the enforcement is, the better. If anything, automated enforcement programs improve fairness by reducing the potential for prejudicial enforcement. Finally, photo enforcement is intended to improve traffic safety by modifying the driver behaviors that lead to crashes, and it is reasonable to expect that people who break the law should pay for enforcing it. Ticket revenue should decline overtime as the cameras succeed in deterring would-be speeders and red light runners. This paper provides research-based responses to the critics＇ arguments as well as best practice guidelines for effective automated enforcement programs.
基金Financial support for this work has been provided by(1)European Union's Seventh Framework Programme for research,technological development,and demonstration under grant agreement no.266367(SOLIDS e Sustainable Organic and Low Input Dairy Systems),and(2)the Biotechnology and Biological Sciences Research Council(BBSRC)[grant number BB/T008776/1]as part of the Doctoral Training Partnership FoodBioSystems:biological processes across the Agri-Food system from pre-farm to postefork.Special thanks to the staff of the Dairy and Energy Metabolism Units(Agri-Food and Biosciences Institute,Hillsborough,Co.Down,UK)for collection of data and care of animals.
文摘Increasing forage proportion(FP)in the diets of dairy cows would reduce competition for human edible foods and reduce feed costs,particularly in low-input systems.However,increasing FP reduces productivity and may increases methane(CH4)emission parameters.This work aimed to investigate the impact of FP and breed on feed efficiency and CH4 emission parameters.Data from 32 individual experiments conducted at the Agri-Food and Biosciences Institute between 1992 and 2010 were utilised in this study resulting in data from 796 Holstein-Friesian(HF),50 Norwegian Red(NR),46 JerseyHF(JHF)and 16 NRHF cows.Diets consisted of varying proportions of forage and concentrate dependent on the experimental protocols of each experiment.A linear mixed model was used to investigate the effect of low(LFP;10%to 30%),medium(MFP;30%to 59%),high(HFP;60%to 87%)and pure(FOR;100%)FP(dry matter[DM]basis)and breed on feed efficiency,and CH4 emission parameters and multivariate redundancy analysis identified associations between animal and dietary drivers on the same variables.Total dry matter intake(DMI)was higher for cows offered LFP(17.3 kg/d)and MFP(17.9 kg/d)compared to HFP(15.3 kg/d)and FOR(13.8 kg/d)(P<0.001).Milk yield(P<0.001),milk yield/DMI(P<0.001),energy corrected milk(ECM)/DMI(P<0.001)and milk energy/DMI(P<0.001)were higher for LFP and MFP compared to HFP and FOR.Methane/DMI was higher for HFP(24.3 g/kg)compared to MFP(22.4 g/kg)(P<0.001).Methane/milk yield(P<0.001)or CH4/ECM(P<0.001)was higher for HFP(22.5 or 21.6 g/kg)and FOR(27.0 or 25.8 g/kg)compared to MFP(19.1 or 17.9 g/kg).There were no differences between LFP and MFP or between HFP and FOR for milk yield,milk yield/DMI,ECM/DMI,milk energy/DMI,CH4/milk yield and CH4/ECM(P>0.05).Differences existed between breeds for residual feed intake(P=0.040),milk yield/DMI(P=0.041)and CH4/DMI(P=0.048)with multivariate redundancy analysis demonstrating negative correlations with efficiency and positive correlations with CH4/DMI and CH4/milk yield.Feeding concentrates at 70%to 90%of DMI(LFP group)would not result in any further benefits for productivity,feed efficiency or CH4 yield and intensity when compared to feeding 41%to 70%concentrates of DMI(MFP group).There may be opportunity to improve profitability for lower intensity farms with less concentrate input.
文摘Background:Malaria remains a significant public health concern in Ghana,with varying risk levels across different geographical areas.Malaria affects millions of people each year and imposes a substantial burden on the health care system and population.Accurate risk estimation and mapping are crucial for effectively allocating resources and implementing targeted interventions to identify regions with disease hotspots.This study aimed to identify regions exhibiting elevated malaria risk so that public health interventions can be implemented,and to identify malaria risk predictors that can be controlled as part of public health interventions for malaria control.Methods:The data on laboratory-confirmed malaria cases from 2015 to 2021 were obtained from the Ghana Health Service and Ghana Statistical Service.We studied the spatial and spatiotemporal patterns of the relative risk of malaria using Bayesian spatial and spatiotemporal models.The malaria risk for each region was mapped to visually identify regions with malaria hotspots.Clustering and heterogeneity of disease risks were established using correlated and uncorrelated structures via the conditional autoregressive and Gaussian models,respectively.Parameter estimates from the marginal posterior distribution were estimated within the Integrated Nested Laplace Approximation using the R software.Results:The spatial model indicated an increased risk of malaria in the North East,Bono East,Ahafo,Central,Upper West,Brong Ahafo,Ashanti,and Eastern regions.The spatiotemporal model results highlighted an elevated malaria risk in the North East,Upper West,Upper East,Savannah,Bono East,Central,Bono,and Ahafo regions.Both spatial and spatiotemporal models identified the North East,Upper West,Bono East,Central,and Ahafo Regions as hotspots for malaria risk.Substantial variations in risk were evident across regions(H=104.9,P<0.001).Although climatic and economic factors influenced malaria infection,statistical significance was not established.Conclusions:Malaria risk was clustered and varied among regions in Ghana.There are many regions in Ghana that are hotspots for malaria risk,and climate and economic factors have no significant influence on malaria risk.This study could provide information on malaria transmission patterns in Ghana,and contribute to enhance the effectiveness of malaria control strategies.
