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The number of China’s elite scientists who have been trained abroad is falling

Association between dietary phytochemical index, inflammation and oxidative stress with sleep duration and sleep quality in Iranian adults

Spectroscopic and machine learning approaches for clinical subtyping in systemic sclerosis

Performance optimization of solar-energized electric vehicles using coupled inductor Relift boost converter

Feasibility of cow-dung groundnut-shell composite as a decentralized renewable fuel for clean cooking

Quantum phase classification via partial tomography-based quantum hypothesis testing

Abstract Quantum phase classification is a fundamental problem in quantum many-body physics, traditionally approached using order parameters or quantum machine learning techniques such as quantum convolutional neural networks (QCNNs). However, these methods often require extensive prior knowledge of the system or large numbers of quantum state copies for reliable classification. In this work, we propose a classification algorithm based on the quantum Neyman–Pearson test, which is theoretically optimal for distinguishing between two quantum states. While directly constructing the quantum Neyman–Pearson test for many-body systems via full state tomography is intractable due to the exponential growth of the Hilbert space, we introduce a partitioning strategy that applies hypothesis tests to subsystems rather than the entire state, effectively reducing the required number of quantum state copies while maintaining classification accuracy. We validate our approach through numerical simulations, demonstrating its advantages over conventional methods, including the order parameter-based classifier, the QCNN, and the recently developed classical machine learning algorithm enhanced with quantum data. Our results show that the proposed method achieves lower classification error probabilities with fewer required quantum state copies compared to all of these baselines, while also reducing the training cost relative to the QCNN and the classical machine learning algorithm enhanced with quantum data, and further decreasing the classical computational time in comparison with the latter. We additionally demonstrate scalability of our method in numerical experiments up to systems with 81 qubits. These findings highlight the potential of quantum hypothesis testing as a powerful tool for quantum phase classification, particularly in experimental settings where quantum measurements are combined with classical post-processing.

The hypoxic tight-skin mouse model of Group 3 pulmonary hypertension

Self-care behaviors among Iranian adults with non-alcoholic fatty liver disease based on the health belief model and structural equation modeling

Research on the damage mechanism and reservoir protection drilling fluid system of Jurassic reservoir in Zhenbei oilfield

Circular economy: water quality assessment for irrigation purposes in a constructed-wetland scenario

Abstract Water is an essential natural resource that sustains life and ecosystems. However, the increasing pressure on freshwater reserves due to climate change, rapid population growth, and industrialization is exacerbating the issue of water scarcity. In this context, wastewater reuse has emerged as a vital strategy to address water shortage. Also, it supports the United Nations Sustainable Development Goals and aligns with the principles of the circular economy. In this context, phytoremediation appears to be a viable solution that employs plant species to purify water, thereby contributing to water reuse. So, this study focuses on evaluating the feasibility of using treated wastewater from a constructed wetland for irrigation purposes. The investigation involved establishing a comprehensive monitoring plan, including sampling and analytical processes, followed by in situ and laboratory analyses of the collected water samples. The results indicate that the treated wastewater met the quality standards set by National and European legislation for irrigation purposes. Some parameters, such as chemical oxygen demand, total suspended solids, and turbidity, demonstrate high removal efficiencies, with maximum removal efficiencies exceeding 97%. The anions and potentially toxic elements showed very low values, being within the standards for water reuse for irrigation, except ammonium (NH 4 + ), which did not comply with the standards in any of the campaigns. The SAR, with a value of less than 2, was below the maximum recommended value (MRV) of 8. Overall, the findings support the use of treated wastewater from constructed wetlands for irrigation, which offers an effective solution for water reuse and contributes to environmental sustainability.

A novel polyhydroxyalkanoate-storing bacterium Thauera carbonocopians sp. nov. isolated from a sequencing batch reactor fed with volatile fatty acids

Scenario-dependent northward shifts in wintering centroids of Anatidae in South Korea

Composition and antioxidant activity of Abies marocana essential oil

Abstract Belonging to the Pinaceae family Abies marocana is a native tree from calcareous mountains of Jebala in northern Morocco. This endemic species is distributed over Mont Tazaout and Talassemtane in the province of Chefchaouen. The present study explores for the first time the phytochemical composition, physicochemical properties, total phenolic content (TPC) and molecular docking simulations to evaluate antioxidant activity of Mont Tazaout Abies marocana essential oil (AMEO). AMEO was extracted using steam distillation, with a yield of 0.24%. A total of 49 compounds were identified using gas-chromatography coupled with mass spectrometry (GC/MS) method. Monoterpene hydrocarbons (88.55%) being the dominant class, and the main components of the tested oil were limonene (38.46%), α- Pinene (21.16%), β -Pinene (12.92%) and camphene (11.23%). Physicochemical properties of AMEO were determined, including density (0.888 ± 0.020) g/cm 3 , refractive index (1.470 ± 0.010), and optical rotation (-40.52 ± 0.04)˚. Furthermore, the total phenolic content (TPC) of the essential oil was found to be (5.07 ± 0.49) mg GAE/g EO. AMEO shows an IC 50 = (136.28 ± 7.8) mg/mL and IC 50 = (1.47 ± 0.04) mg/mL in the DPPH and FRAP assays, respectively. Molecular docking used to investigate the mechanism of interaction between the constituents of AMEO and target proteins associated with antioxidant activity. After analyzing the docking results related to the docking of the seven studied compounds ( S -limonene, R -limonene, camphene, (+)- α -pinene, (-)- α -pinene, (+)- β -pinene and (-)- β -pinene), compounds R -limonene and S -limonene emerged as the most promising antioxidants. This is due to their favorable binding profiles with both NAD(P)H oxidase and nitric oxide synthase targets. These findings highlight the potential bioactive properties of AMEO, suggesting its relevance for further exploration in pharmaceutical, cosmetic and medicinal food reformulation.

Experimental and numerical analysis on cold forging of commercially pure aluminum

Abstract Near net shape forging represents a manufacturing philosophy aimed at achieving components that closely approximate their final geometries in the as-forged state. Unlike a specific forging process, it emphasizes minimizing post-forging machining and material waste while enhancing efficiency and cost-effectiveness. The present work focuses on the preform design of commercially pure aluminium for closed-die forging conditions by analyzing its flow in the die cavity using Deform 3D software. The simulations have been conducted using DEFORM 3D V11.2 software to determine the optimal shape and size of the preform, thereby minimizing costly and inefficient shop floor iterations. The fully defined finite element model includes tetrahedral elements, refined contact region mesh, Lagrangian incremental solver, Coulomb friction formulation, and a calibrated nonlinear hardening law. Three preform geometries of equal volume were evaluated to determine the most suitable design for forming a 40 mm sphere. Experiments validated numerical predictions using a closed-die forging setup. Results show strong agreement in material flow, die filling, and energy trends, though quantitative deviations in forging energy (12.8%), ovality (1.9% simulation vs. 3.6% experimental), die-filling completeness (97.4% simulation vs. 95.1% experiment), and volume conservation (< 1% error in both cases) arose due to friction and strain hardening effects. The findings highlight the effectiveness of simulation in refining the forging process, offering practical insights for manufacturing complex components with improved quality and efficiency.

Correction: Dual-enzyme activated theranostic nanoparticles for image-guided glioblastoma therapy

Digital image analysis-based predictors of effective permanent make-up removal with laser and chemical remover

Traumatic brain injury among patients presenting from prison: a cohort study

Abstract Over two million people are incarcerated in the United States, where they experience increased illness, injury, and barriers to medical care. Traumatic brain injury (TBI) in the incarcerated population remains underexamined, including prevalence, treatment patterns, and outcomes. We analyzed the 2021–2022 National Trauma Data Bank to identify adult patients (≥ 18 years) with TBI as defined by ICD-10 codes, and incarcerated patients were identified by injury location codes. Propensity score matching (2:1 on age, sex, and race; then with the addition of Glasgow Coma Score and Injury Severity Score) was performed to balance baseline characteristics. Subgroup analysis by TBI severity (mild, moderate, severe range) was conducted. Outcomes included hospital mortality and discharge disposition; interventions received were also recorded. Patients presenting from prison with TBI were younger, more often male, and had fewer comorbidities. They presented with distinct trauma mechanisms, specifically with more frequent assaults and less frequent motor vehicle collisions and firearm injuries. After matching, there was higher mortality among patients presenting from prison with severe TBI (30.9% vs. 25.7%, p  = 0.03), corresponding with a 43% increased risk of mortality once adjusted for age, sex, race, and Injury Severity Score despite similar treatment intensity. Discharge to skilled nursing and acute rehab was significantly less frequent among survivors presenting from prison, with absolute differences of 1.7% and 5.1%, respectively ( p  < 0.001). These findings raise concerns about equity in care delivery and post-acute services for incarcerated individuals with TBI. Structural factors impacting discharge planning in this population warrant further investigation.

Effects of afforestation on Technosol properties in reclaimed hard coal deep mining spoil heaps

Abstract Mining for fossil fuels and minerals generates spoil heaps and open pits, which have significant environmental impacts in addition to their economic contributions. Afforestation of these disturbed areas can improve soil properties, thereby increasing the functionality and resilience of terrestrial ecosystems. However, the extent of changes in soil properties following afforestation varies depending on the methods used for tree introduction. There is a need for knowledge on the effects of afforestation on soil properties, especially in post-mining Techonosols. Therefore, the objective of this research is to evaluate the effects of three afforestation methods, succession on barren spoil top (SBT), succession on reclaimed topsoil (STS), and plantation on reclaimed topsoil (PTS), on soil properties in a coal post-mining site. Soil samples were collected from 30 randomly established plots (10 × 10 m) for physical and chemical analyses, focusing on the upper layer (0–10 cm depth). The collected samples were analyzed for soil texture, bulk density (BD), porosity, air capacity, capillary water capacity (CWC), moisture content (MC), exchangeable base cations (Ca 2 ⁺, Mg 2 ⁺, K⁺, and Na⁺), total organic carbon (SOCt), SOC fractions, total nitrogen (Nt), and total sulfur (St). The results showed that PTS had significantly higher CWC, Nt, Ca 2 ⁺, K⁺, occluded light fraction of carbon (ColF), and mineral-associated carbon fraction (CMAF) compared to SBT. These improvements highlight the effectiveness of active reclamation in enhancing soil structure stability, nutrient retention, and long-term carbon stabilization, critical elements for post-mining ecosystem restoration. In contrast, SBT had greater porosity, Mg 2 ⁺, and free light fraction of carbon (CflF) than STS. In addition, SBT had greater St compared to STS and PTS. This indicates that both natural succession and active restoration contribute to soil change through different mechanisms. Therefore, the choice between afforestation strategies should depend on factors such as restoration objectives, topsoil availability, and resource constraints, as active restoration is labor-intensive and costly.

Spectroscopic methods for the simultaneous determination of amlodipine besylate and Hydrochlorothiazide in their binary mixture and pharmaceutical dosage form

Abstract The development of environmentally friendly analytical methods is important in the current scientific landscape. This study presents an investigation into several green spectrophotometric methods for the determination of amlodipine besylate and hydrochlorothiazide in both their pure binary mixtures and pharmaceutical formulations. A spectrophotometric method is proposed for the selective determination of amlodipine besylate in the presence of hydrochlorothiazide at 366 nm, where no interference from hydrochlorothiazide was observed. Additionally, a novel five different spectrophotometric approaches were applied for the determination of hydrochlorothiazide: the dual wavelength method, first derivative method, ratio difference method, and ratio derivative method, as well as Fourier Self-Deconvolution method. Amlodipine besylate’s linearity range was 5–30 µg/mL, whereas hydrochlorothiazide’s was 3–18 µg/mL reaching limits of detection of 1.238, 0.906, 0.825, 0.540, 0.779 and 0.805 µg/mL, respectively for all the proposed methods. The proposed methods were validated in accordance with ICH international guidelines, including full statistical analysis and comprehensive environmental evaluation using multiple assessment tools as The Analytical GREEnness Calculator, the Modified Green Analytic Procedure Index, spider diagram, and green analytical selection tool.

Structured dissociative PCA methods for high dimensional neuroimaging signal decomposition