The impact of cleaner energy sources, advanced technology firms, and economic expansion on ecological footprints is critical in sustainable development.

The environmental degradation accompanying economic growth, despite the potential mitigating effects of technological advancements and cleaner energy sources. This study examines the critical impact of cleaner energy sources, advanced technology firms, and economic expansion on ecological footprints within the context of sustainable development, focusing on the period between 2010 and 2022. By comparing the E7 (emerging seven) and G7 (Group of Seven) economies, the research aims to delineate how these factors collectively influence environmental sustainability in both developing and developed nations. Utilizing a robust panel estimation technique, the study systematically explores the relationship between the adoption of renewable energy technologies, the growth of high-tech industries, and macroeconomic expansion, alongside their respective effects on the ecological footprint, a key indicator of environmental impact. Our statistical analysis reveals significant differences between the E7 and G7 countries. For the G7, investments in cleaner energy and technology sectors have shown a more pronounced effect in reducing ecological footprints, attributed to higher efficiency standards and greater public awareness. In contrast, the E7 countries exhibit a delayed response, owing to varying stages of economic development and technological adoption, although promising trends are emerging. Notably, the G7 demonstrates a more pronounced inclination towards financial imperialism (0.043), while the E7 is significantly influenced by green energy sources (0.258). Policy implications drawn from the findings suggest that targeted investments in green technologies and renewable energy sources, coupled with robust policies supporting economic expansion in a sustainable manner, are crucial for both groups of countries. For the E7, accelerating technology transfer and adopting stricter environmental regulations are key, while the G7 should focus on innovation and the continuous improvement of energy efficiency standards. This dual approach is essential for mitigating the environmental impacts of economic growth and steering the global economy towards a more sustainable trajectory.

Spillover impacts of financial development and globalization on environmental quality in ASEAN countries.

In the globalization era, the economic policy of a specific country might be influenced by the development of neighboring countries. Thus, this study aims to probe the direct and spillover effects of financial development, economic growth, and globalization on environmental sustainability in ASEAN countries during the period of 1992-2021. By applying three spatial regression models, the results are summarized: (1) There are positive spillover effects of financial development in neighboring countries on ecological footprint in a particular country; (2) Economic growth has a positive impact on ecological deficits in both the host country and neighboring countries in the short-run; (3) The expansion of globalization in neighboring countries has a negative spillover effect on the ecological footprint in a particular country and vice versa. Based on these findings, the study recommends that when a country formulates its economic policies, it is necessary to calculate the impact of that policy on neighboring countries and vice versa. Encouraging economic growth and expanding the money supply ought to go hand in hand with fostering greater integration. This integration is essential to counterbalance the potential adverse effects of these macroeconomic variables on environmental quality and ecological balance.

Environmental footprints of the data center service sector in Sweden.

The global data center (DC) sector has expanded rapidly during the last decades, due to the rising demand for digital services. In the Nordic region, Sweden has emerged as a global hub, attracting leading technology companies like Amazon, Facebook, Microsoft, and Google. Server halls of DCs are energy intensive buildings, which puts pressure on local water resources and contributes to global greenhouse gas emissions. This study aims to, firstly, quantify the environmental impact of DCs, based on energy usage, water consumption, and greenhouse gas (GHG) emissions. Secondly, it develops a planning tool by employing a multi-criteria approach to optimally locate new DCs and to assess the site suitability of existing ones in Sweden. Data of various performance indicators (geographical data on renewable energy accessibility, free cooling conditions, excess heat receivers, and resilience to water shortages) of DCs was collected through different means, e.g., questionnaire surveys, permit applications, company websites, and other open online data repositories. ArcGIS Pro was employed for spatial analysis, and 68 DCs with a site suitability index (SSI) ≤ 45 % were identified as less ideally located. The principal findings are centered on Sweden, and thereby primarily benefit stakeholders engaged in decision-making for evaluating existing or strategic planning of new DCs by incorporating a comprehensive environmental perspective. Given the rapidly changing climate, strategically siting DCs will become crucial for minimizing the sector's environmental impact.

Early childhood caries, climate change and the sustainable development goal 13: a scoping review.

BACKGROUND: Sustainable development goal 13 centres on calls for urgent action to combat climate change and its impacts. The aim of this scoping review was to map the published literature for existing evidence on the association between the Sustainable Development Goal (SDG) 13 and early childhood caries (ECC). METHODS: The scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. In August 2023, a search was conducted in PubMed, Web of Science, and Scopus using search terms related to SDG13 and ECC. Only English language publications were extracted. There was no restriction on the type of publications included in the study. A summary of studies that met the inclusion criteria was conducted highlighting the countries where the studies were conducted, the study designs employed, the journals (dental/non-dental) in which the studies were published, and the findings. In addition, the SDG13 indicators to which the study findings were linked was reported. RESULTS: The initial search yielded 113 potential publications. After removing 57 duplicated papers, 56 publications underwent title and abstract screening, and two studies went through full paper review. Four additional papers were identified from websites and searching the references of the included studies. Two of the six retrieved articles were from India, and one was China, Japan, the United States, and the United Kingdom respectively. One paper was based on an intervention simulation study, two reported findings from archeologic populations and three papers that were commentaries/opinions. In addition, four studies were linked to SDG 13.1 and they suggested an increased risk for caries with climate change. Two studies were linked to SDG 13.2 and they suggested that the practice of pediatric dentistry contributes negatively to environmental degradation. One study provided evidence on caries prevention management strategies in children that can reduce environmental degradation. CONCLUSION: The evidence on the links between SDG13 and ECC suggests that climate change may increase the risk for caries, and the management of ECC may increase environmental degradation. However, there are caries prevention strategies that can reduce the negative impact of ECC management on the environment. Context specific and inter-disciplinary research is needed to generate evidence for mitigating the negative bidirectional relationships between SDG13 and ECC.

The importance of assessing the ghosting phenomenon in dynamic footprints when estimating stature - Forensic implications.

In cases where multiple footprints are found at a crime scene, it is unusual that all are static, and some are likely dynamic. Depending on how the footprint was made, we distinguish between dynamic and static footprints. A distinguishing feature that has only recently been associated with dynamic footprints is the fact that dynamic footprints differ from static footprints by the presence of additional markings around the back of the heel and the tops of the toe prints, the so-called ghosting phenomenon. The present study aims to analyse the ghosting phenomenon on dynamic footprints - its occurrence in relation to sex, laterality, and different areas of footprints as well as length features. Additionally, it aims to investigate the assessment of the ghosting phenomenon on dynamic footprints when estimating stature for biological profiling in the forensic field. The study sample comprised of 170 young adults aged 18 - 30 years of both biological sexes. Stature was measured and dynamic footprints were obtained where the ghosting phenomenon was analysed together with length measurements of the same footprint with and without ghosting. In the first and second toes of footprints, the ghosting phenomenon occurred most frequently in both sexes and in the sex-mixed group. Sex differences were not significant in ghosting occurrence on right and left footprints (p > 0.05), except for the area of the left fifth toe (p = 0.045). All the footprints' lengths with ghosting were significantly higher (p < 0.001) than those without ghosting. Statures calculated from footprint length measurements with ghosting predicted stature more accurately than statures calculated from the same footprint length measurements without ghosting. In the case of finding dynamic footprints at crime scenes, it is necessary to correctly identify and evaluate ghosting of the footprint. This comparison can be helpful in interpreting how ghosting should be taken into account when estimating a person's stature.

Urban cemeteries: The forgotten but powerful cooling islands.

Urban parks play a key role in UHI mitigation. However, the role of other prominent types of urban green infrastructure has not been comprehensively studied. Thus, the main objective of this study was to evaluate the role of cemeteries and allotments as cooling islands compared to the well-studied park areas. We assessed the LST of cemeteries, allotments and parks based on Landsat 8 TM images across the five largest German cities during summertime. Random forest regressions explain the LST spatial variability of the different urban green spaces (UGS) with spectral indices (NDVI, NDMI, NDBaI) as well as with tree characteristics (tree type, tree age, trunk circumferences, trunk height or canopy density). As a result, allotments were identified as the hottest UGS with the city means varying between 23.1 and 26.9 °C, since they contain a relatively high proportion of sealed surfaces. The LST spatial variability of allotment gardens was best explained by the NDVI indicating that fields with a higher percentage of flowering shrubs and trees reveal lower LST values than those covered by annual crops. Interestingly, cemeteries were characterized as the coolest UGS, with city means between 20.4 and 24.7 °C. Despite their high proportion of sealed surfaces, they are dominated by old trees resulting in intensive transpiration processes. Parks show heterogeneous LST patterns which could not be systematically explained by spectral indices due to the variability of park functionality and shape. Compared to parks, the tree-covered areas of cemeteries have a higher cooling potential since cemeteries as cultural heritage sites are well-protected allowing old tree growth with intensive transpiration. These findings underline the relevance of cemeteries as cooling islands and deepen the understanding of the role of tree characteristics in the cooling process.

Distinguishing the contributions of different smelting emissions to the spatial risk footprints of toxic elements in soil using PMF, Bayesian isotope mixing models, and distance-based regression.

Toxic element pollution of soils emanating from smelting operations is an escalating global concern due to its severe impact on ecosystems and human health. In this study, soil samples were collected and analyzed to quantify the risk contributions and delineate the spatial risk footprints from smelting emissions for 8 toxic elements. A comprehensive health risk contribution and delineation framework was utilized, consisting of Positive matrix factorization (PMF), spatial interpolation, an advanced Bayesian isotope mixing model via Mixing Stable Isotope Analysis in R (MixSIAR), and distance-based regression. The results showed that the mean concentrations of As, Cd, Cu, Hg, Pb, and Zn exceeded the background levels, indicating substantial contamination. Three sources were identified using the PMF model and confirmed by spatial interpolation and MixSIAR, with contributions ranked as follows: industrial wastewater discharge and slag runoff from the smelter site (48.9 %) > natural geogenic inputs from soil parent materials (26.7 %) > atmospheric deposition of dust particles from smelting operations (24.5 %). Among the identified sources, smelter runoff posed the most significant risk, accounting for 97.9 % of the non-carcinogenic risk (NCR) and 59.9 % of the carcinogenic risk (CR). Runoff also drove NCR and CR exceedances at 7.8 % and 4.7 % of sites near the smelter, respectively. However, atmospheric deposition from smelting emissions affected soils across a larger 0.8 km radius. Although it posed lower risks, contributing just 1.1 % to NCR and 22.6 % to CR due to the limited elevation of toxic elements, deposition reached more distant soils. Spatial interpolation and distance-based regression delineated high NCR and CR exposure hotspots within 1.4 km for runoff and 0.8 km for deposition, with exponentially diminishing risks at further distances. These findings highlight the need for pathway-specific interventions that prioritize localized wastewater containment and drainage controls near the smelter while implementing broader regional air pollution mitigation measures.

Strength characterization and sustainability assessment of coal bottom ash concrete.

Coal bottom ash (CBA) which is waste and environment contaminant has been used in grinded and raw form as replacement of Portland cement (PC) and natural fine aggregates (NFA) in concrete. The combined effect of grinding period (GP) (2-10 h), grinded CBA (GCBA) (10-30%), and raw CBA (0-50%) on strength and microstructural characteristics was investigated and optimized along with its sustainability assessment. An enhancement in strength parameters with an increase in GP and replacement of PC and NFA with GCBA and CBA respectively was observed. The microstructural techniques like XRD, SEM, EDS, and FTIR also correlate with the aforementioned behavior. Mathematical models for strength parameters are well fitted and in good agreement with experimental and predicted values. Multi-objective optimization suggested 6.38 h grinding, 24.21% GCBA, and 32.96% CBA as the optimum values. CBA-based optimized mix resulted in 19.79% and 22.6% lower carbon footprints and eco-cost than the control mix.

Hydrocarbons in Formicidae: influence of chemical footprints on ant behavioral strategies.

When an insect walks, it leaves chemical cues that derive from the arolium, a tarsal structure. These cues may contain important information about other species that occur in their community and can then mediate interactions of competition, predation, and information about resources with ants from their own colony. The compounds of these cues are released into the substrate in the form of chemical footprints. There are still few species studied, and little is known about the behavior of ants regarding these signals and how they use them in their interactions. Therefore, the aim of this study was to assess the behavioral strategy of different ant species when confronted with chemical footprints left by other ants, as well as identify their compounds and their relationship with the cuticular hydrocarbon profile. The experiments were performed using a Y-maze, where in one of the arms, there were chemical footprints of their own species or of other species, and the other Y arm was footprint-free. The chemical compounds of footprints and cuticle were analyzed by gas chromatography-mass spectrometry. The results show that foragers of all species detect and respond to the presence of chemical cues in the form of footprints left by other ants. Foragers of all species followed footprints of individuals of the same species both nestmates and non-nestmates; however, Neoponera villosa avoided the footprints of Cephalotes borgmeieri, and C. borgmeieri avoided the footprints of the other two species. The chemical compositions of the cuticle and footprints are related to each other and are specific to each species.

Identifying dementia from cognitive footprints in hospital records among Chinese older adults: a machine-learning study.

Background: By combining theory-driven and data-driven methods, this study aimed to develop dementia predictive algorithms among Chinese older adults guided by the cognitive footprint theory. Methods: Electronic medical records from the Clinical Data Analysis and Reporting System in Hong Kong were employed. We included patients with dementia diagnosed at 65+ between 2010 and 2018, and 1:1 matched dementia-free controls. We identified 51 features, comprising exposures to established modifiable factors and other factors before and after 65 years old. The performances of four machine learning models, including LASSO, Multilayer perceptron (MLP), XGBoost, and LightGBM, were compared with logistic regression models, for all patients and subgroups by age. Findings: A total of 159,920 individuals (40.5% male; mean age [SD]: 83.97 [7.38]) were included. Compared with the model included established modifiable factors only (area under the curve [AUC] 0.689, 95% CI [0.684, 0.694]), the predictive accuracy substantially improved for models with all factors (0.774, [0.770, 0.778]). Machine learning and logistic regression models performed similarly, with AUC ranged between 0.773 (0.768, 0.777) for LASSO and 0.780 (0.776, 0.784) for MLP. Antipsychotics, education, antidepressants, head injury, and stroke were identified as the most important predictors in the total sample. Age-specific models identified different important features, with cardiovascular and infectious diseases becoming prominent in older ages. Interpretation: The models showed satisfactory performances in identifying dementia. These algorithms can be used in clinical practice to assist decision making and allow timely interventions cost-effectively. Funding: The Research Grants Council of Hong Kong under the Early Career Scheme 27110519.

Monitoring jellyfish outbreaks along Israel's Mediterranean coast using digital footprints.

With mounting global concerns about jellyfish outbreaks, monitoring their occurrence remains challenging. Tapping into the wealth of digital data that internet users share online, which includes reports of jellyfish sightings, may provide an alternative or complement to more conventional expert-based or citizen science monitoring. Here, we explore digital footprints as a data source to monitor jellyfish outbreaks along the Israeli Mediterranean coast. We compiled jellyfish sighting data for the period 2011-2022 from multiple platforms, including leading social media platforms, searches in the Google search engine, and Wikipedia page views. Employing time series analysis, cross-correlation, and various evaluation metrics for presence/absence data, we compared weekly data from three sources: digital footprints, citizen science, and traditional expert-based field monitoring. Consistent seasonal patterns emerge across datasets, with notable correlations, particularly in jellyfish abundance. The cross-correlation between digital footprint and citizen science data exceeds >0.7, with Twitter and Instagram showing the highest correlation. Citizen science data often precedes digital footprints by up to one week. Correlation with traditional, expert-based field monitoring is limited as a result of limited data availability. Digital footprints demonstrate substantial agreement with the other data sources regarding jellyfish presence/absence and major outbreaks, especially for data from Wikipedia, Twitter, and Instagram. Overall, we highlight digital footprint data as a reliable, cost-effective tool for passive monitoring of jellyfish outbreaks, which can aid characterization in data-scarce coastal regions, including retrospective assessment. Transferring and scaling up the proposed approach should consider data accessibility as well as platform relative popularity and usage in the regions under investigation.

Carbon-negative and high-rate nutrient recovery from municipal wastewater using mixotrophic Scenedesmus acuminatus.

The efficiency of mixotrophic microalgae in enhancing the recovery of waste nutrients has been well established; however, the recovery rate is crucial in meeting the needs of field applications. This study evaluated the impact of media characteristics on nutrient recovery under mixotrophic conditions. The mixotrophic N recovery rate with S. acuminatus in modified BG-11 reached 2.59 mg L-1h-1. A mixotrophic growth optimization strategy was applied to achieve a high-rate nutrient recovery from municipal wastewater treatment plant effluents. The contribution of waste chemical oxygen demand (COD) to nutrient recovery was assessed using secondary effluent (SE) under heterotrophy. The results highlighted a significant increase in total nitrogen (TN) and total phosphorus (TP) recovery rates when glucose was supplied, indicating the additional carbon requirements for efficient nutrient recovery. The TN and TP recovery rates under mixotrophic conditions with the addition of trace metals and high cell density were enhanced by 91.94% and 92.53%, respectively, resulting in recovery rates of 3.43 mg L-1h-1 and 0.30 mg L-1h-1. The same conditions were used for nutrient recovery from primary effluent (PE), and the results were more satisfactory as the TN and TP recovery rates reached 4.79 and 0.55 mg L-1h-1, respectively. Additionally, the study estimated the carbon footprints (C-footprints) and areal footprints of mixotrophy-based nitrogen recovery. The findings revealed carbon footprints and areal footprints of -15.93 ± 4.57 tCO2e t-1 N recovery and 0.53 ± 0.19 m3 m-2d-1 wastewater, respectively. This high-rate nutrient recovery, achieved under a carbon-negative (C-negative) budget through mixotrophy, presents a novel strategy for efficiently recovering resources from municipal wastewater, thus facilitating resource recycling and ensuring environmental sustainability.

Technical note: A volumetric method for measuring the longitudinal arch of human tracks and feet.

Fossil footprints (i.e., tracks) were believed to document arch anatomical evolution, although our recent work has shown that track arches record foot kinematics instead. Analyses of track arches can thereby inform the evolution of human locomotion, although quantifying this 3-D aspect of track morphology is difficult. Here, we present a volumetric method for measuring the arches of 3-D models of human tracks and feet, using both Autodesk Maya and Blender software. The method involves generation of a 3-D object that represents the space beneath the longitudinal arch, and measurement of that arch object's geometry and spatial orientation. We provide relevant tools and guidance for users to apply this technique to their own data. We present three case studies to demonstrate potential applications. These include, (1) measuring the arches of static and dynamic human feet, (2) comparing the arches of human tracks with the arches of the feet that made them, and (3) direct comparisons of human track and foot arch morphology throughout simulated track formation. The volumetric measurement tool proved robust for measuring 3-D models of human tracks and feet, in static and dynamic contexts. This tool enables researchers to quantitatively compare arches of fossil hominin tracks, in order to derive biomechanical interpretations from them, and/or offers a different approach for quantifying foot morphology in living humans.

New vegetable field converted from rice paddy increases net economic benefits at the expense of enhanced carbon and nitrogen footprints.

China accounts for around 50 % of the global vegetable harvested area which is expected to increase continuously. Large cropland areas, including rice paddy, have been converted into vegetable cultivation to feed an increasingly affluent population and increase farmers' incomes. However, little information is available on the balance between economic benefits and environmental impacts upon rice paddy conversion into vegetable fields, especially during the initial conversion period. Herein, the life cycle assessment approach was applied to compare the differences in agricultural input costs, yield incomes, net economic benefits (NEB), carbon (C) and nitrogen (N) footprints and net ecosystem economic benefits (NEEB) between the double rice paddy (Rice) and newly vegetable field (Veg) converted from Rice based on a four-year field experiment. Results showed that yield incomes from Veg increased by 96-135 %, outweighing the increased agricultural input costs due to higher inputs of labor and pesticide, thus significantly increasing NEB by 80-137 %, as compared to Rice. Rice conversion into Veg largely increased C footprints by 2.3-10 folds and N footprints by 1.1-2.6 folds, consequently increasing the environmental damage costs (EDC) by 2.2 folds on average. The magnitudes of increases in C and N footprints and EDC due to conversion strongly declined over time. The NEEB, the trade-offs between NEB and EDC, decreased by 18 % in the first year, while increasing by 63 % in the second year and further to 135 % in the fourth year upon conversion. These results suggested that rice paddy conversion into vegetable cultivation could increase the NEB at the expense of enhanced EDC, particular during the initial conversion years. Overall, these findings highlight the importance of introducing interventions to mitigate C and N footprints from newly converted vegetable field, so as to maximize NEEB and realize the green and sustainable vegetable production.

Genome-wide mining of diversity and evolutionary signatures revealed selective hotspots in Indian Sahiwal cattle.

The Sahiwal cattle breed is the best indigenous dairy cattle breed, and it plays a pivotal role in the Indian dairy industry. This is due to its exceptional milk-producing potential, adaptability to local tropical conditions, and its resilience to ticks and diseases. The study aimed to identify selective sweeps and estimate intrapopulation genetic diversity parameters in Sahiwal cattle using ddRAD sequencing-based genotyping data from 82 individuals. After applying filtering criteria, 78,193 high-quality SNPs remained for further analysis. The population exhibited an average minor allele frequency of 0.221 ± 0.119. Genetic diversity metrics, including observed (0.597 ± 0.196) and expected heterozygosity (0.433 ± 0.096), nucleotide diversity (0.327 ± 0.114), the proportion of polymorphic SNPs (0.726), and allelic richness (1.323 ± 0.134), indicated ample genomic diversity within the breed. Furthermore, an effective population size of 74 was observed in the most recent generation. The overall mean linkage disequilibrium (r2) for pairwise SNPs was 0.269 ± 0.057. Moreover, a greater proportion of short Runs of Homozygosity (ROH) segments were observed suggesting that there may be low levels of recent inbreeding in this population. The genomic inbreeding coefficients, computed using different inbreeding estimates (FHOM, FUNI, FROH, and FGROM), ranged from -0.0289 to 0.0725. Subsequently, we found 146 regions undergoing selective sweeps using five distinct statistical tests: Tajima's D, CLR, |iHS|, |iHH12|, and ROH. These regions, located in non-overlapping 500 kb windows, were mapped and revealed various protein-coding genes associated with enhanced immune systems and disease resistance (IFNL3, IRF8, BLK), as well as production traits (NRXN1, PLCE1, GHR). Notably, we identified interleukin 2 (IL2) on Chr17: 35217075-35223276 as a gene linked to tick resistance and uncovered a cluster of genes (HSPA8, UBASH3B, ADAMTS18, CRTAM) associated with heat stress. These findings indicate the evolutionary impact of natural and artificial selection on the environmental adaptation of the Sahiwal cattle population.

Race and Gender Differences in Anterior Cruciate Ligament Femoral Footprint Location and Orientation: A 3D-MRI Study.

OBJECTIVE: The femoral tunnel position is crucial to anatomic single-bundle anterior cruciate ligament (ACL) reconstruction, but the ideal femoral footprint position are mostly based on small-sized cadaveric studies and elderly patients with a single ethnic background. This study aimed to identify potential race- or gender-specific differences in the ACL femoral footprint location and ACL orientation, determine the correlation between the ACL orientation and the femoral footprint location. METHODS: Magnetic resonance images (MRIs) of 90 Caucasian participants and 90 matched Chinese subjects were used for reconstruction of three-dimensional (3D) femur and tibial models. ACL footprints were sketched by several experienced orthopedic surgeons on the MRI photographs. The anatomical coordinate system was applied to reflect the ACL footprint location and orientation of scanned samples. The femoral ACL footprint locations were represented by their distance from the origin in the anteroposterior (A/P) and distal-proximal (D/P) directions. The orientation of the ACL was described with the sagittal, coronal and transverse deviation angles. The ACL orientation and femoral footprint position were compared by the two-sided t-test. Multiple regression analysis was used to study the correlation between the orientation and femoral footprint position. RESULTS: The average femur footprint A/P position was -6.6 ± 1.6 mm in the Chinese group and -5.1 ± 2.3 mm in the Caucasian group, (p < 0.001). The average femur footprint D/P position was -2.8 ± 2.4 mm in Chinese and - 3.9 ± 2.0 mm in Caucasians, (p = 0.001). The Chinese group had a mean difference of a 1.5 mm (6.1%) more posterior and 1.1 mm (5.3%) more proximal in the position from the flexion-extension axis (FEA). And the males have a sagittal plane elevation about 4-5° higher than females in both racial groups. Furthermore, for every 1% (0.40 mm) increase in A/P and D/P values, the sagittal angle decreased by about 0.12° and 0.24°, respectively; the coronal angle decreased by about 0.10° and 0.30°, respectively. For every 1% (0.40 mm) increase in D/P value, the transverse angle increased by about 0.14°. CONCLUSION: The significant race- and gender-specific differences in the femoral footprint and orientation of the ACL should be taken in consideration during anatomic single-bundle ACL reconstruction. Furthermore, the quantitative relationship between the ACL orientation and the footprint location might provide some reference for surgeons to develop a surgical strategy in ACL single-bundle reconstruction and revision.

Mitigating life-cycle environmental impacts and increasing net ecosystem economic benefits via optimized fertilization combined with lime in pomelo production in Southeast China.

Excessive fertilization is acknowledged as a significant driver of heightened environmental pollution and soil acidification in agricultural production. Combining fertilizer optimization with soil acidity amendment can effectively achieve sustainable crop production in China, especially in Southeast China. However, there is a lack of long-term studies assessing the environmental and economic sustainability of combining fertilizer optimization with soil acidity amendment strategies, especially in fruit production. A four-year field experiment was conducted to explore pomelo yield, fruit quality, and environmental and economic performance in three treatments, e.g., local farmer practices (FP), optimized NPK fertilizer application (OPT), and OPT with lime (OPT+L). The results showed that the OPT+L treatment exhibited the highest pomelo yield and fruit quality among the three treatments. The OPT treatment had the lowest net greenhouse gas (GHG) emissions among the three treatments, which were 90.1 % and 42.6 % lower than those in FP and OPT+L, respectively. It is essential to note that GHG emissions associated with lime production constitute 40.7 % of the total emissions from fertilizer production. The OPT+L treatment reduced reactive nitrogen (Nr) emissions and phosphorus (P) losses, compared to FP and OPT. Moreover, the OPT+L treatment increased the net ecosystem economic benefit by 220.3 % and 20.3 % compared with the FP and OPT treatments, respectively. Overall, the OPT and OPT+L treatments underscore the potential to achieve environmentally friendly and economically sustainable pomelo production. Our study provides science-based evidence to achieve better environmental and economic performance in pomelo production through optimized NPK fertilization and alleviating soil acidification by lime.