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Driven by the urgent demand of the steel industry for utilizing low-grade, high-crystal-water iron ores, this study focuses on the thermal decrepitation problem in Guisha limonite pellet preparation caused by goethite dehydroxylation. Different from previous studies that mainly focused on single factors or single performance indicators, this work establishes a multi-factor experimental framework that simultaneously considers bentonite dosage, preheating temperature, and pellet size. This framework enables the strength-decrepitation trade-off of Guisha limonite pellets to be evaluated quantitatively rather than empirically. This work systematically investigated bentonite addition (0.8-1.6 wt%), preheating temperature (600-800 °C), and pellet diameter (9-13 mm). These factors were evaluated in terms of thermal cracking mass ratio and compressive strength. Their interactive effects on thermal cracking behavior and mechanical properties were quantitatively revealed. A target-oriented dual-window process control strategy was then proposed. The results show that thermal cracking intensifies with increasing preheating temperature and decreases with increasing bentonite content; compressive strength peaks at 1.2 wt% bentonite (approx. 1456 N). On this basis, a Min-Max normalization and weighted scoring method was adopted. A quantitative decision-making model was established for strength-prioritized and safety-prioritized objectives. The model identified two optimal process control windows at 1.2 wt% and 1.4 wt% bentonite. An optimized thermal regime-preheating at 700 °C, roasting at 1250 °C, and slow furnace cooling-was established. This regime provides directly referable process parameters. It also offers a decision-making framework for pellet production of similar ores.

Pulmonary embolism (PE) is a blood clot traveling to the lungs and is associated with substantial morbidity and mortality. Therefore, rapid diagnoses and treatments are essential. Chest computed tomographic pulmonary angiogram (CTPA) is the gold standard for PE diagnoses. Deep learning can enhance the radiologists’workflow by identifying PE using CTPA, which helps to prioritize important cases and hasten the diagnoses for at-risk patients. In this study, we propose a two-phase multitask learning method that can recognize the presence of PE and its properties such as the position, whether acute or chronic, and the corresponding right-to-left ventricle diameter (RV/LV) ratio, thereby reducing false-negative diagnoses. Trained on the RSNA-STR Pulmonary Embolism CT Dataset, our model demonstrates promising PE detection performances on the hold-out test set with the window-level AUROC achieving 0.93 and the sensitivity being 0.86 with a specificity of 0.85, which is competitive with the radiologists’sensitivities ranging from 0.67 to 0.87 with specificities of 0.89–0.99. In addition, our model provides interpretability through attention weight heatmaps and gradient-weighted class activation mapping (Grad-CAM). Our proposed deep learning model could predict PE existence and other properties of existing cases, which could be applied to practical assistance for PE diagnosis.

PurposeIn the booming electric vehicle market, the demand for refined cobalt is showing a blowout growth. China is the largest cobalt-refiner and cobalt-importer in the world. However, the life cycle inventory and potential environmental impact from cobalt refining in China have not been clearly illustrated. This paper builds a comprehensive inventory to support the data needs of downstream users of cobalt sulfate. A “cradle-to-gate” life cycle assessment was conducted to provide theoretical support to stakeholders.MethodsA life cycle assessment was performed based on ISO 14040 to evaluate the potential environmental impact and recognize the key processes. The system boundary of this study contains four stages of cobalt sulfate production: mining, beneficiation, primary extraction, and refining. Except for the experimental data used in the primary extraction stage, all relevant data are actual operating data. The normalization value was calculated based on the latest released global emission and extraction data.Results and discussionNormalization results show that the potential impacts of cobalt refining were mainly concentrated in the fossil depletion and freshwater ecotoxicity categories. The beneficiation stage and the refining stage account for 72% and 26% of the total normalization value, respectively. The beneficiation stage needs to consume a lot of chemicals and energy to increase the cobalt content, due to the low grade of cobalt ore in China. Compared with cobalt concentrate, the use of cobalt-containing waste (e.g., cobalt waste from EV batteries) can ease endpoint impact by up to 73%. With the application of the target electricity structure in 2050, the potential impact of China’s cobalt sulfate production on global warming, fossil depletion, and particulates formation can be reduced by 24%, 22%, and 26%, respectively.ConclusionFindings indicate that the chemical inputs and electricity consumption are primary sources of potential environmental impact in China’s cobalt sulfate production. Promoting the development of urban mines can reduce excessive consumption of chemicals and energy in the beneficiation stage. The environmental benefits of transforming the electricity structure and using more renewable energy to reduce dependence on coal-based power in the cobalt refining industry were revealed.

Idiopathic inflammatory myopathies (IIMs) are a heterogeneous group of autoimmune diseases with various subtypes, myositis-specific antibodies, and affect multiple systems. The treatment of IIMs remains challenging, especially for refractory myositis. In addition to steroids and traditional immunosuppressants, rituximab (RTX), a B cell-depleting monoclonal antibody, is emerging as an alternative treatment for refractory myositis. However, the therapeutic response to RTX remains controversial. This meta-analysis aimed to systematically evaluate the efficacy and safety of RTX in patients with IIMs, excluding sporadic inclusion body myositis. PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, and WanFang Data were searched for relevant studies. The overall effective rate, complete response rate, and partial response rate were calculated to assess the efficacy of RTX. The incidences of adverse events, infection, severe adverse events, severe infection, and infusion reactions were collected to evaluate the safety of RTX. Subgroup analyses were performed using IIM subtypes, affected organs, continents, and countries. We also performed a sensitivity analysis to identify the sources of heterogeneity. A total of 26 studies were included in the quantitative analysis, which showed that 65% (95% confidence interval [CI]: 54%, 75%) of patients with IIMs responded to RTX, 45% (95% CI: 22%, 70%) of patients achieved a complete response, and 39% (95% CI: 26%, 53%) achieved a partial response. Subgroup analyses indicated that the overall efficacy rates in patients with refractory IIMs, dermatomyositis and polymyositis, as well as anti-synthetase syndrome were 62%, 68%, and 62%, respectively. The overall efficacy rates for muscle, lungs, and skin involvement were 59%, 65%, and 81%, respectively. In addition, studies conducted in Germany and the United States showed that patients with IIMs had an excellent response to RTX, with an effective rate of 90% and 77%, respectively. The incidence of severe adverse events and infections was 8% and 2%, respectively. RTX may be an effective and relatively safe treatment choice in patients with IIMs, especially for refractory cases. However, further verification randomized controlled trials is warranted.

In the face of external shocks from urbanization and the inherent needs of economic development, it is essential for urban and rural heritage to adapt timely to achieve sustainability in development. Employing Historic Urban Landscape (HUL) methodologies for change management holds significant implications for the sustainable preservation and utilization of heritage. This study used Dongxi Ancient Town as a case study, characterized by a distinct evolutionary trajectory and diverse layers of accumulation throughout its historical progression, making it an exemplary instance for change analysis. This paper analyzed the processes and outcomes of historic urban landscape changes through a layered historical approach. Combining historical data translation methods with ArcGIS spatial analysis, we documented and mapped the cultural and natural characteristics of Dongxi Ancient Town. The layered process of the town’s historical landscape was categorized into four stages: the primary formative period from the Western Han to the Ming dynasties, the rapid development during the Qing dynasty, the prosperous period of the Republic of China, and the transitional expansion period following the establishment of the People’s Republic of China. The study analyzed the morphological changes and values of the historical landscape throughout these periods. Based on the analysis results, we suggest three transformation management strategies for historical landscapes oriented towards economic development: (1) converting cultural heritage into cultural assets, (2) implementing moderate and controlled quantitative changes, and (3) enhancing operational feasibility through collaborative efforts among multiple stakeholders. These strategies aim to establish a sustainable model that balances heritage conservation with economic growth.

In biological and engineered systems, an inherent trade-off exists between the force and velocity that can be delivered by a muscle, spring, or combination of the two. However, one can amplify the maximum throwing power of an arm by storing the energy in a bow or sling shot with a latch mechanism for sudden release. Ilton et al. used modeling to explore the performance of motor-driven versus spring-latch systems in engineering and biology across size scales. They found a range of general principles that are common to animals, plants, fungi, and machines that use elastic structures to maximize kinetic energy. Science , this issue p. eaao1082 Combining motors, springs, and latches offers many routes to optimization of mechanical power in biological and engineered systems. Mechanical power limitations emerge from the physical trade-off between force and velocity. Many biological systems incorporate power-enhancing mechanisms enabling extraordinary accelerations at small sizes. We establish how power enhancement emerges through the dynamic coupling of motors, springs, and latches and reveal how each displays its own force-velocity behavior. We mathematically demonstrate a tunable performance space for spring-actuated movement that is applicable to biological and synthetic systems. Incorporating nonideal spring behavior and parameterizing latch dynamics allows the identification of critical transitions in mass and trade-offs in spring scaling, both of which offer explanations for long-observed scaling patterns in biological systems. This analysis defines the cascading challenges of power enhancement, explores their emergent effects in biological and engineered systems, and charts a pathway for higher-level analysis and synthesis of power-amplified systems.

To address the challenges of low prediction accuracy and insufficient capture of temporal dynamic variations in new energy electricity demand, this paper proposes a chaos-optimized least squares support vector machine (LSSVM) neural network model for multi-temporal and spatial forecasting. First, leveraging an edge computing framework, data collected at the metering side are processed, and redundant time records are cleaned. By integrating chaos theory with Takens’ theorem, the refined data sequence undergoes phase space reconstruction, producing a new energy electricity demand dataset with spatial correlation features. In an innovative step, the spatial transformation results are used as input, combining long short-term memory (LSTM) networks and least squares support vector machines to construct a hybrid LSSVM neural network model for electricity demand forecasting. This enables accurate and dynamic multi-temporal and spatial prediction of new energy electricity demand. Experimental results show that the proposed method achieves an MAE of 0.355 kWh and a MAPE of 1.32% for short-term new energy electricity demand forecasting, while for mid-term forecasting, the MAE and MAPE reach 25.36 kWh and 2.15%, respectively. These results verify the robustness and accuracy of the proposed method in dynamic multi-temporal and spatial electricity demand prediction.

Objectives To characterize the clinical and myo-fascial histopathological features, along with long-term treatment outcomes of patients with eosinophilic fasciitis (EF). Methods We performed a retrospective analysis of the clinical, serological, myo-fascial pathological features, as well as the long-term follow-up outcomes of EF patients between January 2011 and August 2023 at our neuromuscular disorder (NMD) center. Results Seventeen patients were included, and a male predominance (12/17, 70.6%) was identified. The most common clinical manifestation was skin thickening (100%), always distal to the elbow and knee joints, occupied by limited joint mobility (12/17, 70.6%). The “prayer sign” was observed in 7 (41.2%) patients. Eosinophilia was identified in only 7 (41.2%) patients, including 6 in the blood and 3 in tissue. Anti-Ha antibody was confirmed in one patient (P17). Typical fascial edema with or without involvement of the adjacent subcutaneous tissues was exhibited on magnetic resonance imaging (MRI) in all 9 patients. The perifascicular pattern of MHC-I and/or MHC-II upregulation without MxA expression was identified in 56.3% (9/16) of the patients’ muscle specimens. Typical perifascicular atrophy was identified in 4 patients. Complete recovery was noted in 5 patients, including 4 patients treated with prednisone as monotherapy, and 1 patient treated with prednisone combined with D-penicillamine. Conclusions The “prayer sign” might be an important clinical feature of EF. Perifascicular upregulation of MHC-I and/or MHC-II but negative expression of MxA, with or without PFA, represents a unique pathological phenotype of EF. Most patients show favorable outcome following steroid monotherapy or in combination with immunosuppressants, underscoring the autoimmune pathogenic nature of this disease.

Meeting the Paris Agreement targets and the World Health Organization 2021 Air Quality Guidelines is crucial for avoiding air pollution-related health damage. Failing these targets worsens climate change, intensifying environmental threats to public health. Here, we adopt an integrated assessment modeling framework to evaluate timelines for the AQGs attainment under different mitigation scenarios worldwide. We find that achieving 1.5 °C goal could expedite guidelines by decades, dropping PM 2.5 to 5 μg m -3 and ozone to 30 parts per billion by volume by 2050, averting over a million mortalities and delivering major benefits in India, China, American, Europe, and Southeast Asia. Monetized health co-benefits would exceed mitigation costs, rising from 11 trillion to 22 trillion US dollars between 2050 and 2100. We show heightened climate ambition is both feasible and economical, offsetting global mitigation expenses via health benefits. Insufficient actions would exacerbate climate risks such as extreme weather, sea-level rise and economic loss. Realizing the 1.5 °C target could advance WHO Air Quality Guidelines compliance by decades, preventing over one million deaths and delivering significant benefits. The monetized health co-benefits will exceed mitigation costs in most regions.

AimsTo detect abnormal eye movements in Parkinson’s disease and explore its correlation with clinical characteristics and their value for diagnosis.MethodsWe recruited forty-nine Parkinson’s disease patients, including 35 early Parkinson’s disease patients (Hoehn-Yahr: 1 to 2 stage) and 14 advanced Parkinson’s disease patients (Hoehn-Yahr: 3 to 5 stage) and 23 healthy controls. Clinical manifestations in Parkinson’s disease patients were recorded. Oculomotor performances including fixation, gaze, saccade in horizontal and vertical direction, and smooth pursuit in horizontal and vertical direction were measured by video-oculography.ResultsWe found that five oculomotor parameters, namely square wave jerk frequency, latency of downward saccade, latency of upward saccade, accuracy of upward saccade, and gain of horizontal smooth pursuit were significantly different in Parkinson’s disease patients and controls. When combining all these five parameters, we got the diagnostic sensitivity of 78.3% and specificity of 95.2%. More deficits in upward saccade than in other directions were associated with disease duration and progression of Parkinson’s disease.ConclusionOur primary study suggests that oculomotor examination might serve as an aid in the clinical assessment of Parkinson’s disease patients and differentiating between early Parkinson’s disease and normal controls.