Species divergence in valleys: the phylogeny of Phrynocephalus forsythii complex and description of a new species.

Background: Geographic isolation caused by high-altitude valleys promotes the formation of geographic segregation of species, leading to species differentiation. The subgenus Oreosaura contains viviparous species from the Tibetan Plateau and the vicinity of the Tarim Basin, which can be divided into three species complexes according to their geographical distribution: Phrynocephalus vlangalii, Phrynocephalus theobaldi, and Phrynocephalus forsythii. However, molecular data for the P. forsythii complex are limited and the diversity of this species complex has been greatly underestimated. Therefore, this study aimed to explore the species diversity of Oreosaura and species differentiation within the P. forsythii complex. Methods: We analysed the species diversity of Oreosaura by combining previous data, constructed a phylogenetic tree of the subgenus based on cytochrome c oxidase subunit I and 16S sequences, and estimated the divergence time. Results: The results suggest significant genetic differences between the Tarim Basin populations and adjacent mountain valley populations of the P. forsythii complex and that the combination of deep valley landscapes in the high mountains and ice-age events have contributed to the differentiation of the viviparous toad-headed agama lizard, which is a key factor in the phylogenetics of the P. forsythii complex. Furthermore, we identified a population collected from Wuqia County, Xinjiang, as a new species, Phrynocephalus kangsuensis sp. nov. The results will provide data for phylogenetic studies following the P. forsythii complex and help demonstrate that valleys promote the formation of Phrynocephalus species.

On the elephant trails: habitat suitability and connectivity for Asian elephants in eastern Indian landscape.

Identifying suitable habitats and conserving corridors are crucial to the long-term conservation of large and conflict-prone animals. Being a flagship species, survival of Asian elephants is threatened by human-induced mortality and habitat modification. We aimed to assess the habitat suitability and connectivity of the Asian elephant Elephas maximus Linnaeus, 1758 habitat in the state of Odisha in eastern India. We followed the ensemble of spatial prediction models using species presence data and five environmental variables. We used least-cost path and circuit theory approaches to identify the spatial connectivity between core habitats for Asian elephants. The results revealed that normalized difference vegetation index (NDVI; variable importance 42%) and terrain ruggedness (19%) are the most influential variables for predicting habitat suitability of species within the study area. Our habitat suitability map estimated 14.6% of Odisha's geographical area (c. 22,442 km2) as highly suitable and 13.3% (c. 20,464 km2) as moderate highly suitable. We identified 58 potential linkages to maintain the habitat connectivity across study area. Furthermore, we identified pinch points, bottlenecks, and high centrality links between core habitats. Our study offers management implications for long-term landscape conservation for Asian elephants in Odisha and highlights priority zones that can help maintain spatial links between elephant habitats.

Environmental impact of hybrid (reusable/single-use) ports versus single-use equivalents in robotic surgery.

Given the rise in robotic surgery, and parallel movement towards net zero carbon, sustainable healthcare systems, it is important that the environmental impact of robotic approaches is minimised. The majority of greenhouse gas emissions associated with robotic surgery have previously been associated with single-use items. Whilst switching from single-use products to hybrid equivalents (predominantly reusable, with a small single-use component) has previously been found to reduce the environmental impact of a range of products used for laparoscopic surgery, the generalisability of this to robotic surgery has not previously been demonstrated. In this life cycle assessment, use of hybrid 5 mm ports compatible with emerging robotic systems (143 g CO2e) was found to reduce the carbon footprint by 83% compared with using single-use equivalents (816 g CO2e), accompanied by reductions in fifteen out of eighteen midpoint environmental impact categories. For endpoint categories, there was an 81% reduction in impact on human health and species loss, and 82% reductions in resource depletion associated with using hybrid robotic 5 mm ports. Whilst the carbon footprint of 5 mm hybrid ports compatible with emerging robotic equipment was 70% higher than previous estimates of ports appropriate for conventional laparoscopic approaches, the six-fold reductions seen with hybrids in this analysis point to the generalisability of the finding that reusable or hybrid products have a lower carbon footprint when compared with single-use equivalents. Surgeons, procurement teams, and policy makers should encourage innovation towards clinically safe and effective robotic instruments with maximal reusable components.

Agreement between a web collaborative dataset and an administrative dataset to assess the retail food environment in Mexico.

BACKGROUND: Latin American countries are often limited in the availability of food outlet data. There is a need to use online search engines that allow the identification of food outlets and assess their agreement with field observations. We aimed to assess the agreement in the density of food outlets provided by a web collaborative data (Google) against the density obtained from an administrative registry. We also determined whether the agreement differed by type of food outlet and by area-level socioeconomic deprivation. METHODS: In this cross-sectional study, we analyzed 1,693 census tracts from the municipalities of Hermosillo, Leon, Oaxaca de Juarez, and Tlalpan. The Google service was used to develop a tool for the automatic acquisition of food outlet data. To assess agreement, we compared food outlet densities obtained with Google against those registered in the National Statistical Directory of Economic Units (DENUE). Continuous densities were assessed using Bland-Altman plots and concordance correlation coefficient (CCC), while agreement across tertiles of density was estimated using weighted kappa. RESULTS: The CCC indicated a strong correlation between Google and DENUE in the overall sample (0.75); by food outlet, most of the correlations were from negligible (0.08) to moderate (0.58). The CCC showed a weaker correlation as deprivation increased. Weighted kappa indicated substantial agreement between Google and DENUE across all census tracts (0.64). By type of food outlet, the weighted kappa showed substantial agreement for restaurants (0.69) and specialty food stores (0.68); the agreement was moderate for convenience stores/small food retail stores (0.49) and fair for candy/ice cream stores (0.30). Weighted kappa indicated substantial agreement in low-deprivation areas (0.63); in very high-deprivation areas, the agreement was moderate (0.42). CONCLUSIONS: Google could be useful in assessing fixed food outlet densities as a categorical indicator, especially for some establishments, like specialty food stores and restaurants. The data could also be informative of the availability of fixed food outlets, particularly in less deprived areas.

Effect of pH on the ozonolysis degradation of p-nitrophenol in aquatic environment and the synergistic effect of hydroxy radical.

Density functional theory (DFT) was employed to elucidate the mechanisms for ozonolysis reaction of p-nitrophenol (PNP) and its anion form aPNP. Thermodynamic data, coupled with Average Local Ionization Energies (ALIE) analysis, reveal that the ortho-positions of the OH/O- groups are the most favorable reaction sites. Moreover, rate constant calculations demonstrate that the O3 attack on the C2-C3 bond is the predominant process in the reaction between neutral PNP and O3. For the aPNP + O3 reaction, the most favorable pathways involve O3 attacking the C1-C2 and C6-C1 bonds. The rate constant for PNP ozonolysis positively correlates with pH, ranging from 5.47 × 108 to 2.86 × 109 M-1 s-1 in the natural aquatic environment. In addition, the formation of hydroxyl radicals in the ozonation process of PNP and the mechanisms of its synergistic reaction of PNP with ozone were investigated. Furthermore, the ozonation and hydroxylation processes involving the intermediate OH-derivatives were both thermodynamically and kinetic analyzed, which illustrate that OH radicals could promote the elimination of PNP. Finally, the toxic of PNP and the main products for fish, daphnia, green algae and rat were assessed. The findings reveal that certain intermediates possess greater toxicity than the original reactant. Consequently, the potential health risks these compounds pose to organisms warrant serious consideration.

Automatic identification of incidents involving potential serious injuries and fatalities (PSIF).

Safety incidents have always been a crucial risk in work spaces, especially industrial sites. In the last few decades, significant efforts have been dedicated to incident control measures to reduce the rate of safety incidents. Despite all these efforts, the rate of decline in serious injuries and fatalities (SIFs) has been considerably lower than the rate of decline for non-critical incidents. This observation has led to a change of risk reduction paradigm for safety incidents. Under the new paradigm, more focus has been allocated to reducing the rate of critical/SIF incidents, as opposed to reducing the count of all incidents. One of the challenges in reducing the number of SIF incidents is the proper identification of the risk prior to materialization. One of the reasons for risk identification being a challenge is that companies usually only focus on incidents where SIF did occur reactively, and incidents that did not cause SIF but had the potential to do so go unnoticed. Identifying these potentially significant incidents, referred to as potential serious injuries and fatalities (PSIF), would enable companies to work on identifying critical risk and taking steps to prevent them preemptively. However, flagging PSIF incidents requires all incident reports to be analyzed individually by experts and hence significant investment, which is often not affordable, especially for small and medium sized companies. This study is aimed at addressing this problem through machine learning powered automation. We propose a novel approach based on binary classification for the identification of such incidents involving PSIF (potential serious injuries and fatalities). This is the first work towards automatic risk identification from incident reports. Our approach combines a pre-trained transformer model with XGBoost. We utilize advanced natural language processing techniques to encode an incident record comprising heterogeneous fields into a vector representation fed to XGBoost for classification. Moreover, given the scarcity of manually labeled incident records available for training, we leverage weak labeling to augment the label coverage of the training data. We utilize the F2 metric for hyperparameter tuning using Tree-structured Parzen Estimator to prioritize the detection of PSIF records over the avoidance of non-PSIF records being mis-classified as PSIF. The proposed methods outperform several baselines from other studies on a significantly large test dataset.

[Resources and utilization of medicinal plants in countries and regions involved in "the Belt and Road" Initiative].

The protection, development, and utilization of medicinal plant resources are important cornerstones of maintaining human health. However, due to factors such as the reduction of high-quality land resources, deterioration of ecological environments, and excessive and disorderly resource development, medicinal plant resources are becoming scarce, and some of them are insufficiently supplied. With the proposal of "the Belt and Road" Initiative, the cooperation between China and "the Belt and Road" partners(the countries and regions involved in "the Belt and Road" Initiative)is increasingly close, which provides a new opportunity for carrying out trade of medicinal plant resources and alleviating the problem of imbalance and relative inadequacy of medicinal plant resources in countries. This study first determined the distribution and species information of plant resources in countries and regions involved in "the Belt and Road" Initiative by investigating the database of plant distribution and that of medicinal plant resources. Then, according to the published data from the International Union for Conservation of Nature(IUCN) and the Convention on International Trade in Endangered Species of Wild Fauna and Flora(CITES), this study identified the rare and endangered medicinal plants and the medicinal plants under trade control in countries and regions involved in "the Belt and Road" Initiative and finally sorted out the list of potential medicinal plant resources in countries and regions involved in "the Belt and Road" Initiative that can be used by China. This data resource can not only be used for the overall protection of important endangered species but also scientifically guide the development and utilization of medicinal resources, providing guidance and a theoretical basis for the sustainable development of medicinal plant resources in countries and regions involved in "the Belt and Road" Initiative.

Exploring the impact of autumn color and bare tree landscapes in virtual environments on human well-being and therapeutic effects across different sensory modalities.

In recent years, there has been a growing awareness of the potential health benefits of the natural environment for human well-being. Given the fast-paced nature of contemporary lifestyles, research into the use of virtual environments as a means to provide various seasonal landscapes has gained increasing importance. OBJECTIVE: The aim of this study is to investigate the impact of different sensory modes on the preferences and therapeutic effects of virtual autumn landscapes on university campuses. METHODS: In this study, 320 participants, with an average age of 21.11 years (±1.21 years), were exposed to virtual environments featuring autumn color landscapes and bare tree landscapes using visual, auditory, and combined conditions. A control group was included for comparison. Differences in participants' physiological indicators (EEG, heart rate) and psychological measures (POMS, PANAS, SVS, ROS) were analyzed, with the use of the Holm correction (P < 0.05). RESULTS: (1) Autumn virtual landscapes with color had a superior therapeutic effect. (2) There were significant differences in the therapeutic effects of different sensory modes within the same season's landscape categories, suggesting that incorporating additional sensory dimensions may enhance therapeutic outcomes. CONCLUSION: Based on the study's findings, we recommend that when designing therapeutic environments, attention should be given to seasonal variations and the integration of various sensory modes to optimize therapeutic results.

Spatial and temporal differences and convergence analysis of multidimensional relative poverty in ethnic areas.

Reducing multidimensional relative poverty is one of the important issues in the current global poverty governance field. This article takes 12 ethnic regions in China as the research object and constructs a multidimensional relative poverty measurement system. The calculated multidimensional relative poverty index is decomposed according to provinces, cities, dimensions, and indicators. Then, the Dagum Gini coefficient and convergence analysis are used to analyze spatiotemporal heterogeneity and convergence characteristics. The results show that the multi-dimensional relative poverty situation of various provinces in ethnic minority areas has improved from 2012 to 2021, among which Tibet province is the most serious and Shaanxi is the best. According to the analysis of convergence, it was observed that there is no σ-convergence of multidimensional relative poverty in ethnic areas in general, and there is absolute ß-convergence in general and in the southwest and northwest regions, and there is no absolute ß-convergence in the northeast region. Based on this, policy recommendations for reducing multidimensional relative poverty are proposed at the end of the article. Compared with previous studies, this article focuses on ethnic regions that are easily overlooked. Starting from the dimensions of economy, social development, and ecological environment, the poverty measurement system has been enriched.

Using Computer Vision to Annotate Video-Recoded Direct Observation of Physical Behavior.

Direct observation is a ground-truth measure for physical behavior, but the high cost limits widespread use. The purpose of this study was to develop and test machine learning methods to recognize aspects of physical behavior and location from videos of human movement: Adults (N = 26, aged 18-59 y) were recorded in their natural environment for two, 2- to 3-h sessions. Trained research assistants annotated videos using commercially available software including the following taxonomies: (1) sedentary versus non-sedentary (two classes); (2) activity type (four classes: sedentary, walking, running, and mixed movement); and (3) activity intensity (four classes: sedentary, light, moderate, and vigorous). Four machine learning approaches were trained and evaluated for each taxonomy. Models were trained on 80% of the videos, validated on 10%, and final accuracy is reported on the remaining 10% of the videos not used in training. Overall accuracy was as follows: 87.4% for Taxonomy 1, 63.1% for Taxonomy 2, and 68.6% for Taxonomy 3. This study shows it is possible to use computer vision to annotate aspects of physical behavior, speeding up the time and reducing labor required for direct observation. Future research should test these machine learning models on larger, independent datasets and take advantage of analysis of video fragments, rather than individual still images.

Fresh bell peppers consumed in cities: Unveiling the environmental impact of urban and rural food supply systems.

Agriculture and its supply chain pose significant environmental threats. This study employs Life Cycle Assessment (LCA) to explore the environmental impact of fresh bell pepper production and distribution, comparing Urban and Peri-Urban Agriculture (UPA) with Rural Long-Distance Food Supply Systems (RLDFS). Four UPA scenarios (hydroponics, soil-based greenhouse, open-field conventional, and organic) and two RLDFS scenarios (soil-based greenhouse and open-field conventional) are evaluated using SimaPro, incorporating inputs from UPA practitioners and rural farmers. Results reveal an energy demand range of 0.011 to 5.5 kWh/kg eq., with urban greenhouses exhibiting the lowest consumption and hydroponics the highest due to lighting, ventilation, and irrigation. Hydroponics exhibits a global warming potential of 7.24 kg of CO2 eq·kg-1, with energy demand contributing over 95 %, surpassing other scenarios by 7-25 times, necessitating reduction for sustainability. RLDFS's environmental impact is dominated by transportation (over 70 %), meanwhile other UPA systems are influenced by irrigation, infrastructure, and fertilizers. Despite challenges, UPA-hydroponics proves to be 1.7 to 4.3 times more land-use-efficient than other scenarios, emphasizing its potential. The study highlights the need to address electricity usage in UPA-hydroponics for carbon footprint reduction. Despite challenges, hydroponics could contribute to sustainable food security, and RLDFS does not significantly lag in environmental performance compared to UPA other than Ozone layer depletion criteria attributed to fossil fuel usage in transportation. These insights offer valuable guidance for urban development and policy formulation, promoting sustainable agricultural practices and supporting policies for agronomic and supply chain sustainability.

Quantification of the dark fungal taxon Cryptomycota using qPCR.

Fungi are present in a wide variety of natural environments, and in the last years, various studies have shown that they are quite abundant in aquatic ecosystems. In addition, a whole new highly diverse phylum, the Cryptomycota, was discovered. Nevertheless, research on aquatic fungi and a detailed evaluation of their functions and distribution are still sparse. One of the main reasons is a limitation in reliable identification and quantification methods. To bridge part of the research gap, this study aims to implement a quantitative PCR method to detect and quantify the newly discovered phylum. We developed and validated a Cryptomycota-specific qPCR primer pair targeting the 5.8S region that detects the majority of Cryptomycota, but Microsporidia. The resulting amplicon is 102 bp long. We used different environmental samples to evaluate the primer pair, various fungal sequences as negative control and positive control sequences. Obtained amplicons were sequenced using Illumina, and the obtained ASVs were all classified as Cryptomycota. The qPCR method works reliably and specifically for the quantification of Cryptomycota in environmental samples.

Building adjustment capacity to cope with running water in cultured grass carp through flow stimulation conditions.

The adaptability of cultured fish to complex flow conditions is crucial for their survival after being released into the wild. Running water in natural environments poses significant challenges for the proliferation and release of cultured fish. This study aimed to investigate the effects of flow stimulation on the adjustment capacity of cultured fish to cope with running water. The target fish were cultured grass carp. An annular flume was used to conduct tests on training and control groups. The results demonstrated an enhancement in the adjustment capacity of cultured fish following appropriate flow stimulation training. (1) The trained fish exhibited a heightened preference for low-velocity areas. (2) The trained fish displayed the ability to select a route characterized by low energy consumption, predominantly following the periphery of the low-velocity area. This suggested that an appropriate flow velocity could improve the sensitivity of training fish to water flow information, and their adjustment capacity to cope with running water improved to a certain extent. A higher adjustment capacity allowed them to process flow rate information rapidly and identify a migration strategy with lower energy consumption. This study provides a useful reference for enhancing the survival rate of grass carp through stock enhancement initiatives and contributes to the sustainability of freshwater ecosystems.

Prophage maintenance is determined by environment-dependent selective sweeps rather than mutational availability.

Prophages, viral sequences integrated into bacterial genomes, can be beneficial and costly. Despite the risk of prophage activation and subsequent bacterial death, active prophages are present in most bacterial genomes. However, our understanding of the selective forces that maintain prophages in bacterial populations is limited. Combining experimental evolution with stochastic modeling, we show that prophage maintenance and loss are primarily determined by environmental conditions that alter the net fitness effect of a prophage on its bacterial host. When prophages are too costly, they are rapidly lost through environment-specific sequences of selective sweeps. Conflicting selection pressures that select against the prophage but for a prophage-encoded accessory gene can maintain prophages. The dynamics of prophage maintenance additionally depend on the sociality of this accessory gene. Prophage-encoded genes that exclusively benefit the lysogen maintain prophages at higher frequencies compared with genes that benefit the entire population. That is because the latter can protect phage-free "cheaters," reducing the benefit of maintaining the prophage. Our simulations suggest that environmental variation plays a larger role than mutation rates in determining prophage maintenance. These findings highlight the complexity of selection pressures that act on mobile genetic elements and challenge our understanding of the role of environmental factors relative to random chance events in shaping the evolutionary trajectory of bacterial populations. By shedding light on the key factors that shape microbial populations in the face of environmental changes, our study significantly advances our understanding of the complex dynamics of microbial evolution and diversification.

Study on the differences and influencing factors of spatial distribution of population aging at township scale: a case study of township research units in Anshun City, China.

An aging population is one of the main features of China's current population structure, and it is a key area that needs attention to achieve high-quality population development. Because of its unique geographical environment, economic conditions, and sociocultural background, the study of population aging in the karst region of southwest China is particularly important. However, there is a lack of research exploring the regional differentiation of population aging and its influencing factors in the karst regions of southwest China. In light of this, we chose Anshun City, located in Guizhou Province's southwest area, as the case study area. We used the Lorenz curve and spatial autocorrelation to study the differences in the spatial distribution pattern of population aging and introduced multi-scale geographical weighted regression to explore its influencing factors. The results show that Anshun City's older people population proportion (OPP) is generally high with more than 7% of the older people there, making it part of an aging society. The OPP appeared high in the east and low in the west in spatial distribution; the older people population density (OPD) revealed a gradually increasing trend from south to north. At the township scale, both the OPP and the OPD showed significant spatial positive correlation, and the spatial agglomeration characteristics were obvious. OPD and OPP have a positive spatial correlation at the global level, and townships with similar OPP or OPD were spatially adjacent. The spatial distribution characteristics of population aging are the consequence of complex contributions such as natural, social, economic, and karst factors. Further, the spatial distribution pattern of aging is determined by a variety of influencing factors, which have different directions and intensities. Therefore, it is necessary to formulate and implement corresponding policies and strategies to deal with the aging problem in the future.

Species-resolved, single-cell respiration rates reveal dominance of sulfate reduction in a deep continental subsurface ecosystem.

Rates of microbial processes are fundamental to understanding the significance of microbial impacts on environmental chemical cycling. However, it is often difficult to quantify rates or to link processes to specific taxa or individual cells, especially in environments where there are few cultured representatives with known physiology. Here, we describe the use of the redox-enzyme-sensitive molecular probe RedoxSensor™ Green to measure rates of anaerobic electron transfer physiology (i.e., sulfate reduction and methanogenesis) in individual cells and link those measurements to genomic sequencing of the same single cells. We used this method to investigate microbial activity in hot, anoxic, low-biomass (~103 cells mL-1) groundwater of the Death Valley Regional Flow System, California. Combining this method with electron donor amendment experiments and metatranscriptomics confirmed that the abundant spore formers including Candidatus Desulforudis audaxviator were actively reducing sulfate in this environment, most likely with acetate and hydrogen as electron donors. Using this approach, we measured environmental sulfate reduction rates at 0.14 to 26.9 fmol cell-1 h-1. Scaled to volume, this equates to a bulk environmental rate of ~103 pmol sulfate L-1 d-1, similar to potential rates determined with radiotracer methods. Despite methane in the system, there was no evidence for active microbial methanogenesis at the time of sampling. Overall, this method is a powerful tool for estimating species-resolved, single-cell rates of anaerobic metabolism in low-biomass environments while simultaneously linking genomes to phenomes at the single-cell level. We reveal active elemental cycling conducted by several species, with a large portion attributable to Ca. Desulforudis audaxviator.

Assessing environmental sustainability by combining product service systems and life cycle perspective: A case study of hydroponic urban farming models in India.

Hydroponics technology offers an environmentally sustainable alternative to conventional farming for urban food needs. It attracts technologists, non-farmers, retailers, restaurants, and consumers. However, the environmental impact of hydroponics-based urban farming models is yet to be quantified. This study assesses the environmental impact of hydroponics-based urban farming models and makes suggestions to improve their adoption. The methodology involves the use of the Product-Service Systems perspective to categorise the hydroponics-based urban farming models and the Life Cycle Assessment (LCA) method to quantify their environmental impact from a cradle-to-gate perspective. The analysis focuses on the lettuce crop in the state of Tamil Nadu, India. The results from the study suggest that that greenhouse farming (BM1) is more environmentally sustainable than indoor farming (BM2), Cabinet selling and remote monitoring (BM3), and conventional farming. It outperforms other models in terms of GHG emissions, Human Toxicity, and fossil fuels per unit of product, with BM3 having high environmental impacts.

Integrating health, nutrition, and environmental impacts of foods: a life cycle impact assessment and modelling analysis of foods in Canada.

BACKGROUND: Given the urgency of transitioning towards sustainable nutrition, dietary shifts that provide co-benefits to human health and the environment are imperative. There is currently no database of the environmental impacts of foods that reflects Canada's unique geographical and agri-climatic context and regional inputs and emissions. To determine sustainable diets, harmonising nutritional considerations with environmental impacts is also essential for an equitable comparison of foods. We aimed to develop a Canadian Food Life Cycle Inventory database and a multidimensional index to enable a joint assessment of the health and environmental impacts of foods in Canada. METHODS: The Canadian Food Life Cycle Inventory database uses life cycle assessment methodology to evaluate environmental impacts. The datasets mirror Canada's food consumption patterns, averaging the spectrum of agricultural practices weighted by domestic production and import shares. The database is structured according to the nomenclature and categorisation of the Canadian Nutrient File. Environmental sustainability is assessed using a cradle-to-grave approach, including indicators such as greenhouse gas emissions, eutrophication, particulate matter, freshwater usage, land use, non-renewable energy consumption, and food loss and waste. Environmental impacts are quantified through an environmental impact score (EIS) assigned to each impact category for a given food. The EIS-nutrition (EIS-N) integrates the evaluation of nutritional quality with environmental impacts using Nutri-Score, a validated food nutrient-profiling tool. The EIS-N is modelled as a ratio of the EIS to the Nutri-Score values. FINDINGS: Preliminary results show the greatest environmental impacts for animal-based foods, particularly beef, in agreement with current literature. Foods with greater nutritional quality also generally show greater environmental sustainability, with some exceptions for particular impact categories. INTERPRETATION: The database and index have potential to serve as powerful tools to support researchers, policy makers, and consumers, harnessing big data to drive efficient food and climate solutions for systems transformation. FUNDING: Province of Ontario and University of Toronto, CIHR SMART Healthy Cities Training Platform, and University of Toronto's Temerty Faculty of Medicine.

Research on smart city public health detection system and improvement technology based on intelligent multi-objective.

Introduction: With the increase of urban population density, urban sanitation becomes more severe; urban sanitation has important influence on public health. Therefore, in order to realize the detection of public health in smart cities, the research will use cutting-edge scientific and technological methods to improve urban environmental health, so as to promote the realization of public health achievements. This study introduces public health detection and optimizationtechnologies for smart cities. Methods: Firstly, a data detection system for urban public health environment was established using sensors and intelligent multi-objective technology to evaluate the water quality, air quality, and noise level of the city. Then, an intelligent garbage management system based on Tensor-flow was constructed to achieve efficient garbage collection and treatment. Finally, an intelligent traffic management system was developed to monitor and regulate urban traffic flow. Results: The results of the simulation experiment demonstrated that the life data detection system was operationally stable, with a high success rate of 98%. Furthermore, its accuracy in detecting residents' living environment data was above 95%, the maximum relative error was only 0.0465, making it a reliable and efficient tool. The waste recycling system achieved a minimum accuracy of 83.6%, the highest accuracy rate was 95.3%, making it capable of sorting and recycling urban waste effectively. Additionally, the smart traffic management system led to a 20% reduction in traffic congestion rates, 20 tonnes less tailpipe emissions and an improvement in public health and well-being. Discussion: In summary, the plan proposed in this study aims to create a more comfortable, safe, and healthy urban public health environment, while providing theoretical support for environmental health management in smart cities.