Planetary health risks in urban agriculture

Urban agriculture is gaining recognition for its potential contributions to environmental resilience and climate change adaptation,providing advantages such as urban greening,reduced heat island effects,and decreased air pollution.Moreover,it indirectly supports communities during weather events and natural disasters,ensuring food security and fostering community cohesion.However,concerns about planetary health risks persist in highly urbanized and climate-affected areas.Employing electronic databases such as Web of Science and PubMed and adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines,we identified 55 relevant papers to comprehend the planetary health risks associated with urban agriculture,The literature review identified five distinct health risks related to urban agriculture:(1)trace metal risks in urban farms;(2)health risks associated with wastewater irrigation;(3)zoonotic risks;(4)other health risks;and(5)social and economic risks.The study highlights that urban agriculture,while emphasizing environmental benefits,particularly raises concerns about trace metal bioaccumulation in soil and vegetables,posing health risks for populations.Other well studied risks included wastewater irrigation and backyard livestock farming.The main limitations in the available literature were in studying infectious diseases and antibiotic resistance associated with urban agriculture.

Features of long-term health monitored strains of a bridge with wavelet analysis

This paper analyses the five years’ monitored strains collected from a long-term health monitoring system installed on a bridge with wavelet transform.In the analysis,the monitored strains are pre-processed,features of the monitored data are summarized briefly.The influences of the base functions on the results of wavelet analysis are studied simultaneously.The results show that the db wavelet is a good mother wavelet function in the analysis,and the order N should be larger than 20,but less than 46 in decomposing the monitored strains of the bridge.According to the strain variation features of concrete bridge,the proper decomposition level is 4 in the wavelet multi-resolution analysis.With the present method,the strains caused by random loads and daily sunlight can be accurately extracted from the monitored strains.The decomposed components of the monitored strains show that the amplitudes of the strains caused by random loads,daily sunlight,and annual temperature effect,are about 5 με,25 με,and 50 με respectively.The structural response under random load is smaller than the other parts.

Bibliometrics study on the Journal of American College Health： 1994-2014

Objective： To help readers around the world comprehensively understand the development of the journal and evolution of cooperation study, we employed a bibliometrics analysis for the Journal of American College Health. Methods： One-thousand-one-hundred-forty-three articles published in this journal from 1994 were analyzed using the bibliometrics and visualization software CiteSpace. Results： The annual number of published articles and cited studies increased. The published studies by RP Keeling and H Wechsler were at the forefront. ＂College student＂ and ＂alcohol＂ were prevalent key- words. University of Wisconsin and Harvard University were the institutional leaders of contributions. Conclusions： This journal provides an important platform for sharing research achievements and promoting cooperation in this field. The level of articles published is continually improving. A research cooperative network promoted by famous scholars and institutions is developing. However, crossregional and international cooperation is relatively limited.

Morphological Identification of the Main Fungi Associated with Sesame in Burkina Faso

Several fungal species are responsible for diseases that damage sesame crop and cause production losses. These seed-borne fungi cause serious damage by reducing seed germination. To identify the fungi associated with sesame seeds in Burkina Faso, 72 sesame seed samples were collected from 24 localities in the main production areas (Sudanian zone, Sudano-Sahelian zone, Sahelian zone). These samples were submitted for seed health analysis using the blotting paper incubation method. The results obtained revealed that the seed samples were contaminated by various fungi, the main ones being: Fusarium spp. Link: Fr. infecting 97.22% of the samples, Macrophomina phaseolina (Tassi) Goid. (90.28%), Alternaria sesamicola E. Kawamura (83.33%), Curvularia lunata (Wakker) Boedijn (76.39%), Cercospora sesami A. Zimmerm. (73.61%), Phoma sorghina Boerema, Dorenbosch, & Van Kesteren (73.61%), Aspergillus flavus Link: Fr. (69.44%), Cladosporium sphaerospermum Penz. (56.94%), Rhizopus sp. Ehrenb. (40.28%) and A. niger Tiegh. (36.11%). In each seed sample, 0.25% to 94% of the seeds host one or more fungal species. Regarding the climatic zones, the results revealed that A. sesamicola and A. flavus were more represented in the Sudanian zone than in the Sudano-Sahelian and Sahelian zones;while P. sorghina, and C. sphaerospermum were more encountered in the Sahelian zone than in the other two zones. This study showed that the majority of sesame seeds produced and used by farmers in Burkina Faso host one or more species of fungi at high levels.

Damage detection with image processing: a comparative study

Large structures,such as bridges,highways,etc.,need to be inspected to evaluate their actual physical and functional condition,to predict future conditions,and to help decision makers allocating maintenance and rehabilitation resources.The assessment of civil infrastructure condition is carried out through information obtained by inspection and/or monitoring operations.Traditional techniques in structural health monitoring(SHM)involve visual inspection related to inspection standards that can be time-consuming data collection,expensive,labor intensive,and dangerous.To address these limitations,machine vision-based inspection procedures have increasingly been investigated within the research community.In this context,this paper proposes and compares four different computer vision procedures to identify damage by image processing:Otsu method thresholding,Markov random fields segmentation,RGB color detection technique,and K-means clustering algorithm.The first method is based on segmentation by thresholding that returns a binary image from a grayscale image.The Markov random fields technique uses a probabilistic approach to assign labels to model the spatial dependencies in image pixels.The RGB technique uses color detection to evaluate the defect extensions.Finally,K-means algorithm is based on Euclidean distance for clustering of the images.The benefits and limitations of each technique are discussed,and the challenges of using the techniques are highlighted.To show the effectiveness of the described techniques in damage detection of civil infrastructures,a case study is presented.Results show that various types of corrosion and cracks can be detected by image processing techniques making the proposed techniques a suitable tool for the prediction of the damage evolution in civil infrastructures.

Could wastewater analysis be a useful tool for China?——A review

Analysing wastewater samples is an innovative approach that overcomes many limitations of traditional surveys to identify and measure a range of chemicals that were consumed by or exposed to people living in a sewer catchment area. First conceptualised in 2001, much progress has been made to make wastewater analysis（WWA） a reliable and robust tool for measuring chemical consumption and/or exposure. At the moment, the most popular application of WWA, sometimes referred as sewage epidemiology, is to monitor the consumption of illicit drugs in communities around the globe, including China. The approach has been largely adopted by law enforcement agencies as a device to monitor the temporal and geographical patterns of drug consumption. In the future, the methodology can be extended to other chemicals including biomarkers of population health（e.g. environmental or oxidative stress biomarkers, lifestyle indicators or medications that are taken by different demographic groups） and pollutants that people are exposed to（e.g. polycyclic aromatic hydrocarbons,perfluorinated chemicals, and toxic pesticides）. The extension of WWA to a huge range of chemicals may give rise to a field called sewage chemical-information mining（SCIM） with unexplored potentials. China has many densely populated cities with thousands of sewage treatment plants which are favourable for applying WWA/SCIM in order to help relevant authorities gather information about illicit drug consumption and population health status. However, there are some prerequisites and uncertainties of the methodology that should be addressed for SCIM to reach its full potential in China.

A novel testability model for health management of heading attitude system

Prognostics and health management （PHM） is very important to guarantee the reliability and safety of aerospace systems, and sensing and test are the precondition of PHM. Integrating design for testability into early design stage of system early design stage is deemed as a fundamental way to improve PHM performance, and testability model is the base of testability analysis and design. This paper discusses a hierarchical model-based approach to testability modeling and analysis for heading attitude system health management. Quantified directed graph, of which the nodes represent components and tests and the directed edges represent fault propagation paths, is used to describe fault-test dependency, and quantitative testability information is assigned to nodes and directed edges. The fault dependencies between nodes can be obtained by functional fault analysis methodology that captures the physical architecture and material flows such as energy, heat, data, and so on. By incorporating physics of failure models into component, the dynamic process of a failing or degrading component can be projected onto system behavior, i.e., system symptoms. Then, the analysis of extended failure modes, mechanisms and effects is utilized to construct fault evolution-test dependency. Using this integrated model, the designers and system analysts can assess the test suite＇s fault detectability, fault isolability and fault predictability. And heading attitude system application results show that the proposed model can support testability analysis and design for PHM very well.

Performability analysis of avionics system with multilayer HM/FM using stochastic Petri nets

The integrated modular avionics （IMA） architecture is an open standard in avionics industry, in which the number of functionalities implemented by software is greater than ever before. In the IMA architecture, the reliability of the avionics system is highly affected by the software applications. In order to enhance the fault tolerance feature with regard to software application failures, many industrial standards propose a layered health monitoring/fault management （HM/FM） scheme to periodically check the health status of software application processes and recover the malfunctioning software process whenever an error is located. In this paper, we make an analytical study of the HM/FM system for avionics application software. We use the stochastic Petri nets （SPN） to build a formal model of each component and present a method to combine the components together to form a complete system model with respect to three interlayer query strategies. We further investigate the effectiveness of these strategies in an illustrative system.

Determination of symptoms associated with hiesho among young females using hie rating surveys

Objective： Hie （cold sensation） is one of the most well-known health complaints in Japan and elsewhere in East Asia. Those who suffer from severe hie are considered to have hiesho （cold disorder）. This study was conducted to determine symptoms associated with hie in young females using a survey consisting of the hie scale and hie diary. Methods： Two hundred and seventy-one participants were included for the analysis. Survey forms were distributed to the participants. Diagnosis of hiesho was determined by using the hie scale. A discriminant score of over -0.38 was considered hiesho. The Short Form-8 Health Survey Standard Version （SF-8） was used to measure health-related quality of life （QOL）. The participants were also asked to respond to the questionnaire evaluating 14 physical and emotional symptoms, utilizing a six-level Likert scale item. Results： The 1st factor （hie factor） was correlated with hie （r= 0.546）, dry mouth （r= 0.332）, lower- extremity edema （r = 0.450）, headrushes （r=0.470）, shoulder stiffness （r = 0.311 ）, headrushes with chills （r = 0.726）, and fatigue （r= 0.359）. Cronbach＇s α of the 1st factor was 0.748, which indicated reliability between the items. When hie factor was the dependent variable, standardized partial regression coefficient was β=-0.387 for physical component score （P 〈 0.001） and β=-0.243 for mental component score （P 〈 0.001 ）. Conclusion： This study indicated that hiesho symptoms among young female adults were associated with bodily pain and general health perceptions of the SF-8 QOL survey.