Control Area Research Articles

Experimental investigation of bidirectional series resonant DC-DC converter in different operating modes

This paper presents a study of bidirectional series resonant DC/DC converter. The main operating modes of the converter with phase-shift control technique are observed. An experimental survey with a laboratory model of such type of converter working over the resonant frequency is made. The functionality of the studied device operating in a wide area of loading is demonstrated with waveforms of the main parameters. The conducted measurements are used to build the experimental output characteristics of the converter. A similarity of the experimental results with the theoretical are denoted, and the ability to achieve current source characteristics for the whole range of loading is proven. The possibility of the studied converter for operation both in forward and reverse modes of energy flow is proved, which positions the device as an appropriate variant for implementation in the storage system control area.

Is badger culling associated with risk compensation behaviour among cattle farmers?

Risk compensation theory suggests that behaviours are modified in response to interventions that remove risks by substituting them with other risky behaviours to maintain a 'risk equilibrium'. Alternatively, risk reduction interventions may result in spill-over behaviours that seek to minimise risks further. This paper assessed evidence for these behavioural risk responses among farmers in response to badger culling that seeks to remove the risk of bovine tuberculosis in cattle. Data from the UK's randomised badger culling trial were re-analysed, comparing farmers' cattle movement practices in proactive and reactive culling areasand control areas. Analysis compared cattle movementsduring and after the trial using zero-inflated negative binomial regression. The analysis found no strong evidence of risk compensation behaviours among farmers who experienced proactive culling. However, strong evidence for a reduction in cattle movements in reactive culling areas was found. The results indicate high levels of inertia within farming systems in relation to cattle purchasing. Data do not account for the risk of cattle purchases and reflect previous policy regimens. Evidence from recent badger culling interventions should be analysed. Proactive badger culling was not associated with risk compensation behaviours, while reactive badger culling was associated with decreased risk taking among farmers.

Sodium signal intensity of CSF using 1H-guided 23Na-MRI as a potential noninvasive biomarker in Alzheimer's disease.

Alzheimer's disease (AD) is characterized by cognitive decline and mnestic deficits. The pathophysiology of AD is not fully understood, which renders the development of accurate tools for early diagnosis and effective therapies exceedingly difficult. In this study, we investigated the use of 23Na-MRI to measure the relative sodium signal intensities (rSSIs) in CSF in patients with AD and healthy controls. We prospectively recruited 11 patients with biomarker-diagnosed early-stage AD, as well as 12 cognitively healthy age-matched controls. All participants underwent 23Na-MRI to measure rSSI. Statistical analyses were performed to compare CSF sodium signal intensities between groups and to evaluate the specificity and sensitivity of the rSSI in the diagnosis of AD. RSSIs in CSF were significantly higher in AD patients (mean=68.6%±7.7%) compared to healthy controls (mean=56.9%±5.5%) (p<.001). There was also a significant negative correlation between rSSI in CSF and hippocampus and amygdala volumes (r=-.54 and -.49, p<.05) as well as a positive correlation with total CSF volumes (r=.81, p<.05). Receiver operating characteristic analysis showed high diagnostic accuracy for rSSI in discriminating between AD patients and healthy controls (area under the curve=.94). Our study provides evidence that rSSI in CSF is increased in AD patients in comparison to healthy controls. rSSI may serve as a potential marker for early detection and monitoring of disease progression. Larger, longitudinal studies are needed to confirm our findings and to investigate the association between rSSI in CSF and the severity of cognitive impairment.

Small-scale hydrological patterns in a Siberian permafrost ecosystem affected by drainage

Abstract. Climate warming and associated accelerated permafrost thaw in the Arctic lead to a shift in landscape patterns, hydrologic conditions, and release of carbon. In this context, the lateral transport of carbon and shifts therein following thaw remain poorly understood. Crucial hydrologic factors affecting the lateral distribution of carbon include the depth of the saturated zone above the permafrost table with respect to changes in water table and thaw depth and the connectivity of water-saturated zones. Landscape conditions are expected to change in the future due to rising temperatures and polygonal or flat floodplain Arctic tundra areas in various states of degradation; hydrologic conditions will also change. This study is focused on an experimental site near Chersky, northeast Siberia, where a drainage ditch was constructed in 2004 to simulate landscape degradation features that result in drier soil conditions and channeled water flow. We compared water levels and thaw depths in the drained area (dry soil conditions) with those in an adjacent control area (wet soil conditions). We also identified the sources of water at the site via stable water isotope analysis. We found substantial spatiotemporal changes in the water conditions at the drained site: (i) lower water tables resulting in drier soil conditions, (ii) quicker water flow through drier areas, (iii) larger saturation zones in wetter areas, and (iv) a higher proportion of permafrost meltwater in the liquid phase towards the end of the growing season. These findings suggest decreased lateral connectivity throughout the drained area. Shifts in hydraulic connectivity in combination with a shift in vegetation abundance and water sources may impact carbon sources and sinks as well as transport pathways. Identifying lateral transport patterns in areas with degrading permafrost is therefore crucial.

POSITIVE SCRATCH COLLAPSE TEST IN ANTERIOR CUTANEOUS NERVE ENTRAPMENT SYNDROME (ACNES): EVIDENCE FOR A PERIPHERAL NEUROPATHY?

Abstract Background Chronic abdominal pain is occasionally caused by an abdominal wall entity such as Anterior Cutaneous Nerve Entrapment Syndrome (ACNES). This syndrome is thought to occur due to entrapped intercostal nerve branches (Th7-12) within the rectus abdominis muscles. This clinical diagnosis is based on subjective clues in patient history and physical examination. In contrast, in carpal tunnel syndrome an additional diagnostic test is used, which is referred to as the scratch collapse test (SCT). The SCT has shown positive results not only in other peripheral entrapment neuropathies involving the ulnar, peroneal, and long thoracic nerve, but also in three recently described ACNES patients. We investigated whether the SCT is of diagnostic use in patients suspected of having ACNES. Method A prospective, case-control study was performed among patients with ACNES (n = 20) and two control groups without ACNES (acute abdomen n = 20; healthy n = 20), all were consecutively included. ACNES was diagnosed based on previously published criteria. The SCT test was executed at the painful abdominal area in both patient groups and at a corresponding area in healthy controls. Predictive values, sensitivity, and specificity were calculated. Videos of tests were evaluated by blinded observers. Results SCT was judged positive in 19 of 20 ACNES patients, but not in any of the 40 controls. A 95% sensitivity (CI:75–99) and 100% specificity (CI: 83–100) were calculated. Conclusion This study provides strong evidence that ACNES should be considered as an entrapment neuropathy, while a positive SCT should be considered as a major diagnostic criterion.

A New Assessment of High Punctual Solar Trackers Effects on Poultry Welfare in Agrivoltaïc Open-Air Runs

Open-air poultry farming is currently developing with the increasing society demand for livestock farming better considering animal welfare. Outside animal comfort and open-air runs exploration could be enhanced by shelters such as trees or photovoltaic (PV) structure. The aim of this study is to confirm previous results to evaluate (i) the microclimates generated under high punctual PV trackers, (ii) the effect on laying hens comfort, (iii) the use of panels shadow area by hens. In three experimental sites, microclimates were studied and laying hens were counted in a control area, under such PV tracker and under a tree. Results showed that PV trackers, as big trees, lowered summer soil and air temperatures, radiation and lightness, decreased the occurrences of stress situations for hens, and that more hens were counted under trackers than in a control area. These results may help for optimizing such agrivoltaïc system and the hens welfare by improving the open-air run design with PV structures and vegetation.

Quantifying land impacts of wind energy: a regional-scale assessment in Finland

AbstractLarge-scale deployment of wind energy raises ecological concerns about land use changes. Here, we conducted a quantitative assessment of land impacts of 42 wind farms (513 turbines) from Ostrobothnia, Finland. Located on the Baltic Sea coast, Ostrobothnia is a strategic region for national wind energy targets. Our main objectives were (1) to calculate landscape metrics (e.g., habitat composition, loss and fragmentation) within wind farm project areas, (2) compare the amount of building-related deforestation between project areas and simulation-based control areas and (3) compute the overlap between project areas and regional land use plans. According to CORINE Land Cover datasets, the predominant habitats within project areas were forests (371.7 km2; 81%) and transitional forests (52.7 km2; 11%). The remaining 8% were agricultural areas (17.6 km2; 4%), waters (12.5 km2; 3%) and artificial surfaces (2.9 km2; 1%). Wind farm infrastructure corresponded to 1.4-6.0% of project areas and caused similar degrees of habitat fragmentation. Deforestation levels in project areas were higher (~ 6 times on average) than in control areas, and the micro-siting of turbines did not avoid mature forests by favouring e.g., transitional forests (which are ecologically less valuable). We found some spatial incongruence between project areas and regional land use plans, with 78 turbines falling outside the established boundaries. Our results highlight the need for careful ecological considerations in wind energy spatial planning in Finland (and countries with similar landscapes and land uses) to limit forest loss and its detrimental impacts on forest-dependent species, but also on carbon storage and sequestration.

Exploring the thermal shielding performance by coupling phase change material to liquid cooling plate

To enhance the thermal shielding performance of high-temperature heat source target, an evolved cold shield system coupling phase change material (PCM) and liquid cooling plate with serpentine flow channel is developed. The thermal shielding effectiveness of the proposed system is illustrated by comparing the duration maintained at a lower temperature on the cold surface, and the temperature uniformity of the cold surface is analyzed to describe the role of PCM in the thermal shielding performance. The influences of the operating parameters of the liquid cooling plate and PCM physical parameters on the thermal shielding performance of the heat source targets are investigated. The results indicate that coupling PCM to a liquid cooling plate can effectively improve the thermal shielding performance. Increasing the heat power of the heat source target from 190 W to 231 W will lessen the advantage time from 3090 s to 1980 s for the coupled system. The advantage time is shortened by 1500 s as increasing the liquid volume flow rate from 0.26 L/min to 1.30 L/min. Lifting the starting temperature of the coolant from 15 °C to 25 °C prolongs the advantage time from 2130 s to 3090 s. The advantage time is improved by 660 s as increasing the PCM phase transition temperature from 26 °C to 30 °C, and increasing the PCM covering thickness from 8 mm to 10 mm extends the advantage time from 1830 s to 3090 s. Meanwhile, the temperature equalization of the cold surface for the coupled system is better than the single liquid cooling. These results indicate that the proposed coupled system has potential applications in improving thermal shielding performance as well as heat flow control, thermal insulation, and other areas of heat regulation.

Prediction of electrical properties of GAAFET based on integrated learning model

As device feature sizes continue to decrease and fin field effect transistors reach their physical limits, gate all around field effect transistors (GAAFETs) have emerged with larger gate control areas and stackable characteristics for better suppression of second-order effects such as short-channel effects due to their gate encircling characteristics. Traditional methods for studying the electrical characteristics of devices are mostly based on the technology computer-aided design. Still, it is not conducive to developing new devices due to its time-consuming and inefficient drawbacks. Deep learning (DL) and machine learning (ML) have been well-used in recent years in many fields. In this paper, we propose an integrated learning model that integrates the advantages of DL and ML to solve many problems in traditional methods. This integrated learning model predicts the direct current characteristics, capacitance characteristics, and electrical parameters of GAAFET better than those predicted by DL or ML methods alone, with a linear regression factor (R 2) greater than 0.99 and very small root mean square error. The proposed integrated learning model achieves fast and accurate prediction of GAAFET electrical characteristics, which provides a new idea for device and circuit simulation and characteristics prediction in microelectronics.

An Edge Computing System with AMD Xilinx FPGA AI Customer Platform for Advanced Driver Assistance System.

The convergence of edge computing systems with Field-Programmable Gate Array (FPGA) technology has shown considerable promise in enhancing real-time applications across various domains. This paper presents an innovative edge computing system design specifically tailored for pavement defect detection within the Advanced Driver-Assistance Systems (ADASs) domain. The system seamlessly integrates the AMD Xilinx AI platform into a customized circuit configuration, capitalizing on its capabilities. Utilizing cameras as input sensors to capture road scenes, the system employs a Deep Learning Processing Unit (DPU) to execute the YOLOv3 model, enabling the identification of three distinct types of pavement defects with high accuracy and efficiency. Following defect detection, the system efficiently transmits detailed information about the type and location of detected defects via the Controller Area Network (CAN) interface. This integration of FPGA-based edge computing not only enhances the speed and accuracy of defect detection, but also facilitates real-time communication between the vehicle's onboard controller and external systems. Moreover, the successful integration of the proposed system transforms ADAS into a sophisticated edge computing device, empowering the vehicle's onboard controller to make informed decisions in real time. These decisions are aimed at enhancing the overall driving experience by improving safety and performance metrics. The synergy between edge computing and FPGA technology not only advances ADAS capabilities, but also paves the way for future innovations in automotive safety and assistance systems.

Culicoides Midge Abundance across Years: Modeling Inter-Annual Variation for an Avian Feeder and a Candidate Vector of Hemorrhagic Diseases in Farmed Wildlife

(1) Background: Epizootic hemorrhagic disease virus (EHDV) and bluetongue virus (BTV) are orbiviruses that cause hemorrhagic disease (HD) with significant economic and population health impacts on domestic livestock and wildlife. In the United States, white-tailed deer (Odocoileus virginianus) are particularly susceptible to these viruses and are a frequent blood meal host for various species of Culicoides biting midges (Diptera: Ceratopogonidae) that transmit orbiviruses. The species of Culicoides that transmit EHDV and BTV vary between regions, and larval habitats can differ widely between vector species. Understanding how midges are distributed across landscapes can inform HD virus transmission risk on a local scale, allowing for improved animal management plans to avoid suspected high-risk areas or target these areas for insecticide control. (2) Methods: We used occupancy modeling to estimate the abundance of gravid (egg-laden) and parous (most likely to transmit the virus) females of two putative vector species, C. stellifer and C. venustus, and one species, C. haematopotus, that was not considered a putative vector. We developed a universal model to determine habitat preferences, then mapped a predicted weekly midge abundance during the HD transmission seasons in 2015 (July–October) and 2016 (May–October) in Florida. (3) Results: We found differences in habitat preferences and spatial distribution between the parous and gravid states for C. haematopotus and C. stellifer. Gravid midges preferred areas close to water on the border of well and poorly drained soil. They also preferred mixed bottomland hardwood habitats, whereas parous midges appeared less selective of habitat. (4) Conclusions: If C. stellifer is confirmed as an EHDV vector in this region, the distinct spatial and abundance patterns between species and physiological states suggest that the HD risk is non-random across the study area.

Validation of the Cognitive Assessment Instrument for Obsessions and Compulsions (CAIOC-13) in an Indian Sample

Background: Brief self-report measures of cognition are advantageous for flagging significant cognitive dysfunction without extensive neuropsychological assessments. The Cognitive Assessment Instrument for Obsessions and Compulsions (CAIOC-13) is a recently developed self-report that assesses everyday cognitive dysfunction in obsessive-compulsive disorder (OCD), for example, difficulties with reading, slowness, and decision-making. This study was undertaken to validate the CAIOC-13 in an Indian sample of OCD. Material and Methods: 75 subjects with OCD and 81 non-clinical controls completed CAIOC-13, Perceived Deficits Questionnaire (PDQ), and Dysfunctional Attitude Scale-Short Form (DAS-SF1). Convergent and divergent validity with PDQ and DAS-SF1 were established with Pearson’s correlation; the Receiver Operating Characteristic (ROC) curve was used to analyze discriminant validity; and factorial structure was evaluated using the principal component analysis (PCA). Results: CAIOC-13 scores showed a strong significant correlation ( r = 0.56; p &lt; .001) with PDQ and a moderate correlation with DAS-SF1 scores ( r = 0.33; p = .003). CAIOC-13 could accurately discriminate between OCD and controls (area under curve = 0.92). PCA revealed strong loading on a single component. Conclusion: CAIOC-13 is a valid tool for briefly assessing OCD-related cognitive dysfunction in Indian samples. Future studies may examine the correlation of CAIOC-13 with standardized neuropsychological assessments.

Spatial and Temporal Distribution Characteristics of Ozone Concentration and Health Benefit Assessment in the Beijing-Tianjin-Hebei Region from 2015 to 2020

To evaluate the spatial and temporal distribution characteristics of ambient ozone (O3) in the Beijing-Tianjin-Hebei (BTH) Region, the land use regression (LUR) model and random forest (RF) model were used to simulate the ambient O3 concentration from 2015 to 2020. Meanwhile, all-cause, cardiovascular, and respiratory mortalities as well as economic losses attributed to O3 were also estimated. The results showed that upward trends with fluctuation were observed for ambient O3 concentration, mortalities, and economic losses attributable to O3 exposure in the BTH Region from 2015 to 2020. The areas with high O3 concentration and great changes were concentrated in the central and southwestern regions, whereas the concentration in the northern region was low, and the change degree was small. The spatial distribution of the mortalities was also consistent with the spatial distribution of O3 concentration. From 2015 to 2020, the economic losses regarding all-cause mortality and cardiovascular mortality increased in 13 cities of the BTH Region, whereas the economic losses of respiratory mortality decreased in 4 cities in the BTH Region. The results indicated that the priority areas for O3 control were not uniform. Specifically, Beijing, Tianjin, Hengshui, and Xingtai were vital areas for O3 pollution control in the BTH Region. Differentiated control measures should be adopted based on the characteristics of these target areas to decline O3 concentration and reduce health impacts and economic losses associated with O3 exposure.

CICIoV2024: Advancing realistic IDS approaches against DoS and spoofing attack in IoV CAN bus

Considering the complexity of network traffic in IoV operations, methods that can identify complex patterns become useful. Machine learning fosters several techniques to enhance the detection, prevention, and mitigation of cyberattacks. However, important features are not addressed in the current state-of-the-art security datasets for IoV. For example, in the case of intra-vehicle communications, it is critical to consider the interaction among multiple Electronic Control Units (ECUs). Also, mimicking a realistic IoV environment is not simple since establishing a test environment requires considerable financial investment. Hence, there is a need for a testbed composed of several real ECUs in an IoV environment comprising network traffic. Thereupon, the main goal of this research is to propose a realistic benchmark dataset to foster the development of new cybersecurity solutions for IoV operations. To accomplish this, five attacks were executed against the fully intact inner structure of a 2019 Ford car, complete with all ECUs. However, the vehicle was immobile and incapable of causing any potential harm or injuries. Hence, all attacks were carried out on the vehicle without endangering the car’s driver or passengers. These attacks are classified as spoofing and Denial-of-Service (Dos) and were carried out through the Controller Area Network (CAN) protocol. This effort establishes a baseline complementary to existing contributions and supports researchers in proposing new IoV solutions to strengthen overall security using different techniques (e.g., Machine Learning — ML). The CICIoV2024 dataset has been published on CIC’s dataset page.

Interactions between Lateral Hypothalamic Orexin and Dorsal Raphe Circuitry in Energy Balance.

Orexin/hypocretin terminals innervate the dorsal raphe nucleus (DRN), which projects to motor control areas important for spontaneous physical activity (SPA) and energy expenditure (EE). Orexin receptors are expressed in the DRN, and obesity-resistant (OR) rats show higher expression of these receptors in the DRN and elevated SPA/EE. We hypothesized that orexin-A in the DRN enhances SPA/EE and that DRN-GABA modulates the effect of orexin-A on SPA/EE. We manipulated orexin tone in the DRN either through direct injection of orexin-A or through the chemogenetic activation of lateral-hypothalamic (LH) orexin neurons. In the orexin neuron activation experiment, fifteen minutes prior to the chemogenetic activation of orexin neurons, the mice received either the GABA-agonist muscimol or antagonist bicuculline injected into the DRN, and SPA/EE was monitored for 24 h. In a separate experiment, orexin-A was injected into the DRN to study the direct effect of DRN orexin on SPA/EE. We found that the activation of orexin neurons elevates SPA/EE, and manipulation of GABA in the DRN does not alter the SPA response to orexin neuron activation. Similarly, intra-DRN orexin-A enhanced SPA and EE in the mice. These results suggest that orexin-A in the DRN facilitates negative energy balance by increasing physical activity-induced EE, and that modulation of DRN orexin-A is a potential strategy to promote SPA and EE.

CAN Interface Insights for Electric Vehicle Battery Recycling

Road transportation is a significant worldwide contributor to greenhouse gases, and electrifying the driveline of road vehicles is essential in overcoming the evident challenge of climate change. A sustainable transition to electric vehicles requires efficient and safe methods for recycling and repurposing used electric vehicle batteries. While various testing methods have been explored for assessing battery state of health and state of risk for recycling and reuse, a research gap exists concerning using data from integrated battery monitoring systems in the recycling process of electric vehicle batteries. This study addresses the research gap by presenting an approach to extract data from the monitoring system integrated into the battery using the automotive standard controller area network interface. In addition, methods to use this interface to ensure the optimal state of charge of the batteries for storage are presented. The benefits, challenges, and limitations set by the proprietary nature of the data to assess the state of risk and health of electric vehicle batteries for recycling and repurposing are presented, discussed, and evaluated. Finally, the influence of battery regulations and the battery passport proposal on electric vehicle battery recycling and repurposing are discussed to provide future perspectives.

Modelling the magnetic-mechanical coupled viscoelastic behaviour of transversely isotropic soft magnetorheological elastomers

Soft magnetorheological elastomers (s-MRE) is a kind of smart material mainly fabricated by embedding soft magnetic particles into an elastomer matrix. It can be categorized as isotropic and transversely isotropic, depending on the arrangement of internal magnetic particles. In isotropic s-MRE, magnetic particles are randomly distributed, while transversely isotropic s-MRE forms chain structures for the magnetic particles. Compared with isotropic s-MRE, transversely isotropic s-MRE exhibits more significant magnetically-enhanced mechanical properties, making it highly applicable in the vibration control area. While past theoretical work has mainly focused on the magneto-mechanical coupling behaviour of isotropic s-MRE, less attention has been given to modelling the magneto-mechanical coupling behaviour of transversely isotropic s-MRE. Specifically, understanding the impact of different particle chain-magnetic field spatial locations on the magnetization and magnetic-enhanced viscoelastic behaviour of transversely isotropic s-MRE remains an open topic. To address this research gap, we characterize the quasi-static, viscoelastic and magnetization performance of transversely isotropic s-MRE under different particle chain-magnetic field spatial locations. Subsequently, we develop a novel constitutive model for transversely isotropic s-MRE, integrating magneto-hyperelasticity, magneto-viscoelasticity and magnetization. We then implement the magneto-mechanical coupled model for transversely isotropic s-MRE at a finite element level. Following model calibration and validation, we conduct a case study to demonstrate the model’s ability to predict the magneto-mechanical coupling performance of a transversely isotropic s-MRE-based laminated isolator. This model is a valuable tool for predicting the magneto-mechanical performance of transversely isotropic s-MRE-based smart devices, thereby facilitating the design and advancement of transversely isotropic s-MRE in vibration control.

Quantifying Heavy Metal Accumulation in Soil and Vegetation Surrounding Industrial Areas: A Comprehensive Environmental Toxicology Study

Background: Industrial activities release significant amounts of heavy metals into the environment, contaminating soil and vegetation. This pollution poses severe risks to ecosystems and human health, making it a crucial area of study. Objective: To quantify the accumulation of heavy metals in soil and vegetation surrounding industrial areas and assess the ecological risks associated with this contamination. Methods: The study involved quantitative analysis of soil and plant samples from industrial and control areas. Heavy metals analyzed included lead, cadmium, mercury, arsenic, chromium, and nickel. Methods included atomic absorption spectroscopy for metal quantification, bioaccumulation factor (BAF) calculation for plants, and ecological risk assessment using the ecological risk index (ERI). Results: Soil samples from industrial zones showed significantly higher concentrations of lead (175 mg/kg), cadmium (8 mg/kg), and chromium (90 mg/kg) compared to control areas (lead: 30 mg/kg, cadmium: 2 mg/kg, chromium: 20 mg/kg). Plant tissues from these areas also revealed elevated levels of lead (12 mg/kg), cadmium (2 mg/kg), and nickel (8 mg/kg), against lower concentrations in control samples (lead: 3 mg/kg, cadmium: 0.5 mg/kg, nickel: 2 mg/kg). The ecological risk index underscored a high risk in industrial zones (ERI = 85) compared to control areas (ERI = 30). Conclusion: The study highlights the critical contamination of soil and vegetation with heavy metals near industrial zones and the consequent ecological risks. These findings emphasize the need for immediate remediation strategies and stricter regulatory frameworks to mitigate the impacts of this pollution.

Nonlinear Effects of Land-Use Conflicts in Xinjiang: Critical Thresholds and Implications for Optimal Zoning

Land-use conflicts (LUCs) are pivotal in assessing human–land interaction, reflecting the intricate interplay between natural and anthropogenic drivers. However, existing studies often overlook nuanced non-linear responses and critical threshold recognition, focusing solely on linear correlations between isolated factors and LUCs. This study, situated in Xinjiang, China’s arid and semiarid region, introduces a novel analytical framework and threshold application model for LUCs. Integrating land-use and socioeconomic data, we quantified LUCs using Fragstats, correlation analysis, and restricted cubic spline (RCS) regression. Exploring non-linear dynamics between LUCs and 14 potential drivers, including natural and anthropogenic factors, we identified critical thresholds. LUC zones were delineated using a four-quadrant method, allowing tailored mitigation strategies. Our findings reveal Xinjiang’s distinct LUC spatial pattern, with intense conflicts surrounding mountainous areas and milder conflicts in basin regions, showing marked diminishment from 2000 to 2020. RCS effectively identifies LUC thresholds, indicating persisting severity pre- or post-specific thresholds. Xinjiang’s LUCs are categorized into key control areas, urgent regulation zones, elastic development territories, and moderate optimization regions, each with significant regional disparities. Tailored optimization suggestions mitigate linear analysis limitations, providing a fresh perspective on land zoning optimization. This research supports comprehensive land management and planning in Xinjiang, China.

Tracking bioaerosol exposure among municipal solid waste workers using hematological and inflammatory biomarkers

High levels of bioaerosols may exist in the air of municipal solid waste (MSW) management facilities, constituting a significant occupational hazard for workers. In this study, we investigated the potential association between exposure to bioaerosols and inflammatory biomarkers among municipal solid waste workers (MSWWs) at both the landfill site and the municipal solid waste transfer station (MSWTS), in comparison to a control group without exposure. Air sampling was conducted at six points around the landfill, two points at the MSWTS, and one point in a public park (as a control area) during the spring and summer of 2019. The results of our study revealed that airborne pathogens were highly prevalent at the sampling points, especially in the active zone and leachate collection pond. Aspergillus species were the predominant fungal species detected in this study, with the highest occurrence observed for Aspergillus flavus (83.3%), Aspergillus niger, and Aspergillus fumigatus (75.0%). Furthermore, Staphylococcus species accounted for over 75% of the total bacterial bioaerosols detected across all study areas. The blood test results of workers revealed a significant increase in platelets (PLT), immunoglobulin G (IgG), white blood cells (WBC), neutrophils, basophils, and high-sensitivity C-reactive protein (hs-CRP) compared to the control group. Conversely, platelet distribution width (PDW), mean platelet volume (MPV), and platelet-large cell ratio (P-LCR) in the exposed subjects exhibited a decreasing trend compared to the control group. These findings suggest a potential association between exposure to bioaerosols, particularly in the vicinity of open dumpsites, and elevated levels of hematologic and inflammatory markers in circulation. Furthermore, the influence of smoking status and confounding factors appears to be significant in both the control and exposure groups.