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Abstract The breaking of time-reversal symmetry (TRS) in the normal state of kagome superconductors AV3Sb5 stands out as a significant feature, but its tunability is unexplored. Using low-energy muon spin rotation and local field numerical analysis, we study TRS breaking as a function of depth in single crystals of RbV3Sb5 (with charge order) and Cs(V0.86Ta0.14)3Sb5 (without charge order). In the bulk of RbV3Sb5 (>33 nm from the surface), we observed an increase in the internal magnetic field width in the charge-ordered state. Near the surface (

Abstract Background High b-value diffusion-weighted images (DWI) are used for detection of clinically significant prostate cancer (csPCa). This study qualitatively and quantitatively compares synthesized DWI (sDWI) to acquired (aDWI) for detection of csPCa. Methods One hundred fifty-one consecutive patients who underwent prostate MRI and biopsy were included in the study. Axial DWI with b = 0, 500, 1000, and 2000 s/mm2 using a 3T clinical scanner using a 32-channel phased-array body coil were acquired. We retrospectively synthesized DWI for b = 2000 s/mm2 via extrapolation based on mono-exponential decay, using b = 0 and b = 500 s/mm2 (sDWI500) and b = 0, b = 500 s/mm2, and b = 1000 s/mm2 (sDWI1000). Differences in signal intensity between sDWI and aDWI were evaluated within different regions of interest (prostate alone, prostate plus 5 mm, 30 mm and 70 mm margin and full field of view). The maximum DWI value within each ROI was evaluated for prediction of csPCa. Classification accuracy was compared to Restriction Spectrum Imaging restriction score (RSIrs), a previously validated biomarker based on multi-exponential DWI. Discrimination of csPCa was evaluated via area under the receiver operating characteristic curve (AUC). Results Within the prostate, mean ± standard deviation of percent mean differences between sDWI and aDWI signal were -46 ± 35% for sDWI1000 and -67 ± 24% for sDWI500. AUC for aDWI, sDWI500, sDWI1000, and RSIrs within the prostate 0.62[95% confidence interval: 0.53, 0.71], 0.63[0.54, 0.72], 0.65[0.56, 0.73] and 0.78[0.71, 0.86], respectively. Conclusion sDWI is qualitatively comparable to aDWI within the prostate. However, hyperintense artifacts are introduced with sDWI in the surrounding pelvic tissue that interfere with quantitative cancer detection and might mask metastases. In the prostate, RSIrs yields superior quantitative csPCa detection than sDWI or aDWI.

Plasma disruption in tokamak experiments is a challenging issue that causes damage to the device. Reliable prediction methods are needed, but the lack of full understanding of plasma disruption limits the effectiveness of physics-driven methods. Data-driven methods based on supervised learning are commonly used, and they rely on labelled training data. However, manual labelling of disruption precursors is a time-consuming and challenging task, as some precursors are difficult to accurately identify. The mainstream labelling methods assume that the precursor onset occurs at a fixed time before disruption, which leads to mislabeled samples and suboptimal prediction performance. In this paper, we present disruption prediction methods based on anomaly detection to address these issues, demonstrating good prediction performance on J-TEXT and EAST. By evaluating precursor onset times using different anomaly detection algorithms, it is found that labelling methods can be improved since the onset times of different shots are not necessarily the same. The study optimizes precursor labelling using the onset times inferred by the anomaly detection predictor and test the optimized labels on supervised learning disruption predictors. The results on J-TEXT and EAST show that the models trained on the optimized labels outperform those trained on fixed onset time labels.

Abstract Astrophysical jets play crucial roles in star formation and transporting angular momentum away from accretion discs, however, their collimation mechanism is still a subject of much debate due to the limitations of astronomical observational techniques and facilities. Here, a quasi-static toroidal magnetic field is generated through the interaction between lasers and a four-post nickel target, and our all-optical laboratory experiments reveal that a wide-angle plasma plume can be collimated in the presence of toroidal magnetic fields. Besides the confinement effects, the experiments show the jet can also be accelerated by the enhanced thermal pressure due to the toroidal magnetic fields compressing the flow. These findings are verified by radiation magneto-hydrodynamic simulations. The experimental results suggest certain astrophysical narrow plasma flows may be produced by the confinement of wide-angle winds through toroidal fields.

Inter-basin water transfer projects are the main measure to address the water deficit crisis caused by uneven distribution of water resources. The current water transfer operation mainly tends to be present in areas with small water transfer costs and is prone to encounter the problem of spatial and temporal imbalances in water allocation. To address these issues, this paper defines a water deficit evenness index (WDEI), aimed at minimizing regional differences in water scarcity and sharing the pressure of water scarcity as a social demand objective. This index is incorporated into a joint optimization model for the Jiangsu section of the South-to-North Water Diversion Project (J-SNWDP), which comprises both the ecological objective of the total water deficit (TWD) and the economic objective of the pumping water (PW). Further, the Nondominated Sorting Genetic Algorithm III (NSGA-III) and multi-attribute decision-making were applied to solve the model and obtain an optimal operation strategy. The results showed the following: (1) the WDEI defined in this paper can mitigate the synchronized water scarcity in certain water users. In typical normal years (wet year and dry year), the WDEI shows a reduction of 94.2 % (81.8 %, 76.7 %) compared to the historical operation strategy. (2) The optimized operation strategy can significantly reduce TWD and PW by 82.06% (37.69 %, 52.36 %) and 45.13 % (3.25 %, 21.51 %) compared with the historical values, respectively, which can improve the water supply satisfaction and reduce the project cost. At the same time, the lake storage capacity of the optimal operation strategy performs well, and the water transfer efficiency of the river is significantly improved. (3) In this paper, targeted optimal operation strategies and potential ways to secure the project tasks are proposed for different natural flow. Overall, it is of great significance to study the water supply equity in the J-SNWDP to alleviate the concentrated water deficit in Jiangsu Province and other similar regions.

Background: The US government considers veterans to have been exposed to Agent Orange if they served in Vietnam while the carcinogen was in use, and these veterans are often deemed at high risk of prostate cancer (PCa). Here, we assess whether presumed Agent Orange exposure is independently associated with increased risk of any metastatic or fatal PCa in a diverse Veteran cohort still alive in the modern era (at least 2011), when accounting for race/ethnicity, family history, and genetic risk. Patients and Methods: Participants in the Million Veteran Program (MVP; enrollment began in 2011) who were on active duty during the Vietnam War era (August 1964-April 1975) were included (n = 301,470). Agent Orange exposure was determined using the US government definition. Genetic risk was assessed via a validated polygenic hazard score. Associations with age at diagnosis of any PCa, metastatic PCa, and death from PCa were assessed via Cox proportional hazards models. Results and Interpretation: On univariable analysis, exposure to Agent Orange was not associated with increased PCa (hazard ratio [HR]: 1.02, 95% confidence interval [CI]: 1.00–1.04, p = 0.06), metastatic PCa (HR: 0.98, 95% CI: 0.91–1.05, p = 0.55), or fatal PCa (HR: 0.94, 95% CI: 0.79–1.09, p = 0.41). When accounting for race/ethnicity and family history, Agent Orange exposure was independently associated with slightly increased risk of PCa (HR: 1.06, 95% CI: 1.04–1.09,

It has attracted much attention on the interplay between topology and criticality in topological quantum systems, i.e., gapless topological quantum phase transition (TQPT) on critical lines. It is demonstrated that the magnetocaloric effect (MCE) is able to signal the gapless TQPT in an extended Kitaev chain, which is witnessed by the unusual critical behavior of joint effect of Grüneison ration (GR) and isothermal entropy change. We uncover the conventional TQPT between gapped phases showing high symmetry (HS) and non-HS critical points with self-duality, which is signaled by the finite value of GR as T → 0 and the largest inverse MCE with T-linear relation of isothermal entropy change. Two critical lines intersect at a multicritical point, at which there is a T−1 critical divergence of GR as well as T1/2 critical behavior of isothermal entropy change. It manifests a “weak” gapless TQPT on one critical line, demonstrated by the shifting zero-crossing of GR without the largest inverse MCE. On the other critical line, it shows a “strong” gapless TQPT, which is evidenced by the negative dip of GR together with the largest inverse MCE. Our work provides a novel thermodynamic perspective on gapless TQPT.

Abstract Background In a recent phase III randomized control trial, delivering a focal radiotherapy (RT) boost to tumors visible on MRI was shown to improve disease-free survival and regional/distant metastasis-free survival for patients with prostate cancer—without increasing toxicity. The aim of this study was to assess how widely this technique is being applied in current practice, as well as physicians’ perceived barriers toward its implementation. Methods We invited radiation oncologists to complete an online questionnaire assessing their use of intraprostatic focal boost in December 2022 and February 2023. To include perspectives from a broad range of practice settings, the invitation was distributed to radiation oncologists worldwide via email list, group text platform, and social media. Results 263 radiation oncologist participants responded. The highest-represented countries were the United States (42%), Mexico (13%), and the United Kingdom (8%). The majority of participants worked at an academic medical center (52%) and considered their practice to be at least partially genitourinary (GU)-subspecialized (74%). Overall, 43% of participants reported routinely using intraprostatic focal boost. Complete GU-subspecialists were more likely to implement focal boost, with 61% reporting routine use. In both high-income and low-to-middle-income countries, less than half of participants routinely use focal boost. The most cited barriers were concerns about registration accuracy between MRI and CT (37%), concerns about risk of additional toxicity (35%), and challenges to accessing high-quality MRI (29%). Conclusions Two years following publication of a randomized trial of patient benefit without increased toxicity, almost half of the radiation oncologists surveyed are now routinely offering focal RT boost. Further adoption of this technique might be aided by increased access to high-quality MRI, better registration algorithms of MRI to CT simulation images, physician education on benefit-to-harm ratio, and training on contouring prostate lesions on MRI.

Most extant ice caps mantling low-relief Arctic Canada landscapes remained cold based throughout the late Holocene, preserving in situ bryophytes killed as ice expanded across vegetated landscapes. After reaching peak late Holocene dimensions ∼1900 CE, ice caps receded as Arctic summers warmed, exposing entombed vegetation. The calibrated radiocarbon ages of entombed moss collected near ice cap margins (kill dates) define when ice advanced across the site, killing the moss, and remained over the site until the year of their collection. In an earlier study, we reported 94 last millennium radiocarbon dates on in situ dead moss collected at ice cap margins across Baffin Island, Arctic Canada. Tight clustering of those ages indicated an abrupt onset of the Little Ice Age at ∼1240 CE and further expansion at ∼1480 CE coincident with episodes of major explosive volcanism. Here we test the confidence in kill dates as reliable predictors of expanding ice caps by resampling two previously densely sampled ice complexes ∼15 years later after ∼250 m of ice recession. The probability density functions (PDFs) of the more recent series of ages match PDFs of the earlier series but with a larger fraction of early Common Era ages. Post 2005 CE ice recession has exposed relict ice caps that grew during earlier Common Era advances and were preserved beneath later ice cap growth. We compare the 106 kill dates from the two ice complexes with 80 kill dates from 62 other ice caps within 250 km of the two densely sampled ice complexes. The PDFs of kill dates from the 62 other ice caps cluster in the same time windows as those from the two ice complexes alone, with the PDF of all 186 kill dates documenting episodes of widespread ice expansion restricted almost exclusively to 250–450 CE, 850–1000 CE, and a dense early Little Ice Age cluster with peaks at ∼1240 and ∼1480 CE. Ice continued to expand after 1480 CE, reaching maximum dimensions at ∼1880 CE that are still visible as zones of sparse vegetation cover in remotely sensed imagery. Intervals of widespread ice cap expansion coincide with persistent decreases in mean summer surface air temperature for the region in a Community Earth System Model (CESM) fully coupled Common Era simulation, suggesting the primary forcings of the observed snowline lowering were both modest declines in summer insolation and cooling resulting from explosive volcanism, most likely intensified by positive feedbacks from increased snow cover and sea ice and reduced northward heat transport by the oceans. The clusters of ice cap expansion defined by moss kill dates are mirrored in an annually resolved Common Era record of ice cap dimensions in Iceland, suggesting this is a circum-North-Atlantic–Arctic climate signal for the Common Era. During the coldest century of the Common Era, 1780–1880 CE, ice caps mantled >11 000 km2 of north-central Baffin Island, whereas km2 is glaciated at present. The peak Little Ice Age state approached conditions expected during the inception phase of an ice age and was only reversed after 1880 CE by anthropogenic alterations of the planetary energy balance.

Abstract SABRE (Sodium iodide with Active Background REjection) is a direct detection dark matter experiment based on arrays of radio-pure NaI(Tl) crystals. The experiment aims at achieving an ultra-low background rate and its primary goal is to confirm or refute the results from the DAMA/LIBRA experiment. The SABRE Proof-of-Principle phase was carried out in 2020–2021 at the Gran Sasso National Laboratory (LNGS), in Italy. The next phase consists of two full-scale experiments: SABRE South at the Stawell Underground Physics Laboratory, in Australia, and SABRE North at LNGS. This paper focuses on SABRE South and presents a detailed simulation of the detector, which is used to characterise the background for dark matter searches including DAMA/LIBRA-like modulation. We estimate an overall background of 0.72 cpd/kg/ $$\hbox {keV}_{\hbox {{ee}}}$$ keV ee in the energy range 1–6 $$\hbox {keV}_{\hbox {{ee}}}$$ keV ee primarily due to radioactive contamination in the crystals. Given this level of background and considering that the SABRE South has a target mass of 50 kg, we expect to exclude (confirm) DAMA/LIBRA modulation at $$4~(5)\sigma $$ 4 ( 5 ) σ within 2.5 years of data taking.

Abstract Element isotopes are characterized by distinct atomic masses and nuclear spins, which can significantly influence material properties. Notably, however, isotopes in natural materials are homogenously distributed in space. Here, we propose a method to configure material properties by repositioning isotopes in engineered van der Waals (vdW) isotopic heterostructures. We showcase the properties of hexagonal boron nitride (hBN) isotopic heterostructures in engineering confined photon-lattice waves—hyperbolic phonon polaritons. By varying the composition, stacking order, and thicknesses of h10BN and h11BN building blocks, hyperbolic phonon polaritons can be engineered into a variety of energy-momentum dispersions. These confined and tailored polaritons are promising for various nanophotonic and thermal functionalities. Due to the universality and importance of isotopes, our vdW isotope heterostructuring method can be applied to engineer the properties of a broad range of materials.

Brown carbon (BrC) represents an important target for the “win-win” strategy of mitigating climate change and improving air quality. However, estimating co-benefits of BrC control remains difficult for China, partially because current measurement results are insufficient to represent the highly variable emission sources and meteorological conditions across different regions. In this study, we investigated, for the first time, the diurnal variations of BrC during two distinct seasons in a megacity in northeast China. The winter campaign conducted in January 2021 was characterized by low temperatures rarely seen in other Chinese megacities (down to about −20 ∘C). The mass absorption efficiencies of BrC at 365 nm (MAE365) were found to be ∼ 10 % higher at night. The variations of MAE365 could not be explained by the influence of residential biomass burning emissions or secondary aerosol formation but were strongly associated with the changes of a diagnostic ratio for the relative importance of coal combustion and vehicle emissions (RS/N). Given that most coal combustion activities were uninterruptible, the higher nighttime MAE365 in winter were attributed primarily to increased emissions from heavy-duty diesel trucks. The spring campaign conducted in April 2021 was characterized by frequent occurrences of agricultural fires, as supported by the intensive fire hotspots detected around Harbin and the more-than-doubled ratios of levoglucosan to organic carbon (LG/OC) compared to the winter campaign. In spring, the MAE365 depended little on RS/N but exhibited a strong positive correlation with LG/OC, suggesting open burning emissions as the dominant influencing factor for BrC's light absorption capacity. MAE365 were ∼ 70 % higher at night for the spring campaign, pointing to the prevalence of nighttime agricultural fires, which were presumably in response to local bans on open burning. It is noteworthy that the agricultural-fire emissions resulted in a distinct peak at ∼ 365 nm for the light absorption spectra of BrC, and candidates for the compounds at play were inferred to be aromatic species with nitro-functional groups. The presence of the ∼ 365 nm peak complicated the determination of absorption Ångström exponents for the agricultural-fire-impacted samples. In addition, the ∼ 365 nm peak became much less significant during the day, likely due to photobleaching of the relevant chromophores.

Immune responses benefit organismal fitness by clearing parasites but also exact costs associated with immunopathology and energetic investment. Hosts manage these costs by tightly regulating the induction of immune signaling to curtail excessive responses and restore homeostasis. Despite the theoretical importance of turning off the immune response to mitigate these costs, experimentally connecting variation in the negative regulation of immune responses to organismal fitness remains a frontier in evolutionary immunology. In this study, we used a dose-response approach to manipulate the RNAi-mediated knockdown efficiency of cactus (IκBα), a central regulator of Toll pathway signal transduction in flour beetles (Tribolium castaneum). By titrating cactus activity across four distinct levels, we derived the shape of the relationship between immune response investment and traits associated with host fitness, including infection susceptibility, lifespan, fecundity, body mass, and gut homeostasis. Cactus knock-down increased the overall magnitude of inducible immune responses and delayed their resolution in a dsRNA dose-dependent manner, promoting survival and resistance following bacterial infection. However, these benefits were counterbalanced by dsRNA dose-dependent costs to lifespan, fecundity, body mass, and gut integrity. Our results allowed us to move beyond the qualitative identification of a trade-off between immune investment and fitness to actually derive its functional form. This approach paves the way to quantitatively compare the evolution and impact of distinct regulatory elements on life-history trade-offs and fitness, filling a crucial gap in our conceptual and theoretical models of immune signaling network evolution and the maintenance of natural variation in immune systems.

We study the ferrimagnetic quantum phase transitions (QPTs) and thermodynamics of a dimerized organic polymer, which is described as a periodic Anderson-like model using Green’s function theory. In the absence of magnetic field, it is shown that the Kondo coupling could destroy the Dirac semimetal and induce spin splitting, and the dimerization could open up an energy gap. In a magnetic field, the ferrimagnetic and ferromagnetic insulators as well as Weyl-Kondo semimetal are unveiled. The mechanism of Kondo-singlet competition with dimer-singlet is unveiled to account for the 1/3 magnetization plateau. The field induces second and first order QPTs in the small and large hybridization limit, which is demonstrated by the field scaling of Grüneisen ratio and temperature scaling of specific heat at low temperatures, providing novel thermodynamic means to diagnose the order of QPTs.

ABSTRACTRenal cell carcinoma (RCC), especially clear cell RCC, is generally considered an immunotherapy-responsive cancer. Recently, the prognosis for patients with locally advanced and metastatic RCC has significantly improved with the regulatory approvals of anti-PD-1/PD-L1/CTLA-4 immune checkpoint inhibitor (ICI)-based regimens. Yet in most cases, RCC will remain initially unresponsive to treatment or will develop resistance over time. Hence, there remains an unmet need to understand what leads to ICI resistance and to develop novel immune and nonimmune treatments to enhance the response to ICIs. In this review, we highlight recently published studies and the latest clinical studies investigating the next generation of immune approaches to locally advanced and metastatic RCC beyond traditional ICIs. These trials include cytokines, gut microbiota-based therapies, novel immune checkpoint agents, vaccines, and chimeric antigen receptor T cells. These agents are being evaluated as monotherapy or in combination with traditional ICIs and will hopefully provide improved outcomes to patients with RCC soon.

The g factors of 11/2− isomers in semimagic 109Sn and 111Sn (isomeric lifetimes τ=2.9(3) ns and τ=14.4(7) ns, respectively) were measured by an extension of the Time Differential Perturbed Angular Distribution technique, which uses LaBr3 detectors and the hyperfine fields of a gadolinium host to achieve precise measurements in a new regime of short-lived isomers. The results, g(11/2−;109Sn)=−0.186(8) and g(11/2−;111Sn)=−0.214(4), are significantly lower in magnitude than those of the 11/2− isomers in the heavier isotopes and depart from the value expected for a near pure neutron h11/2 configuration. Broken-symmetry density functional theory calculations applied to the sequence of 11/2− states reproduce the magnitude and location of this deviation. The g(11/2−) values are affected by shape core polarization; the odd 0h11/2 neutron couples to Jπ=2+,4+,6+... configurations in the weakly-deformed effective core, causing a decrease in the g-factor magnitudes.

AbstractThe concept of Digital Twin was invented not only for a static virtual mimic of reality, but also means an evolving digital copy which could stay consistent with its physical counterpart. The life-cycle management of a product or a system could not be completed without dynamic feature, while conventional methods to create graphic assets especially 3D models for Digital Twins are still limited. In this paper, Procedural Content Generation is introduced as a potential technique which could reduce difficulty for the creation and modification of 3D graphic assets of Digital Twins. A trial project and two validation cases are executed to verify the proposed method.

Unmitigated disruptions pose a much more serious threat when large-scale tokamaks are operating in the high performance regime. Machine learning based disruption predictors can exhibit impressive performance. However, their effectiveness is based on a substantial amount of training data. In future reactors, obtaining a substantial amount of disruption data in high performance regimes without risking damage to the machine is highly improbable. Using machine learning to develop disruption predictors on data from the low performance regime and transfer them to the high performance regime is an effective solution for a large reactor-sized tokamak like ITER and beyond. In this study, a number of models are trained using different subsets of data from the HL-2A tokamak experiment. A SHapley Additive exPlanations (SHAP) analysis is executed on the models, revealing that there are different, even contradicting, patterns between different performance regimes. Thus, simply mixing data among different performance regimes will not yield optimal results. Based on this analysis, we propose an instance-based transfer learning technique which trains the model using a dataset generated with an optimized strategy. The strategy involves instance and feature selection based on the physics behind differences in high- and low-performance discharges, as revealed by SHAP model analysis. The TrAdaBoost technique significantly improved the model performance from 0.78 BA (balanced accuracy) to 0.86 BA with a few high-performance operation data.

To obtain an efficient and low-cost adsorbent for the Sb(V) removal in Sb(V)-contaminated water, a novel composite manganese oxide/oxyhydroxide (CMO) was synthesized by a simple hydrothermal synthesis method. The synthesized adsorbent was characterized via scanning electron microscopy, X-ray diffraction, transmission electron microscopy, Brunauer-Emmett-Teller surface area, Fourier transform infrared, and X-ray photoelectron spectroscopy analyses. The results revealed that the as-prepared CMO adsorbent possessed a porous structure consisting of Mn3O4 nanoparticles and MnOOH nanorods. Batch experiments showed that the adsorption behaviours were well fitted by the Langmuir isotherm and the pseudo-second-order kinetic model, reaching the maximum adsorption capacity of 119.63 mg/g at 25 °C. The application of CMO adsorbent showed that the Sb(V) removal efficiency in 6.24 L Sb(V)-containing water with a concentration of 3.6 mg/L was more than 90%. The reusability of CMO adsorbent demonstrated that the Sb(V) removal efficiency was still more than 80% even after five times of regeneration. The adsorption mechanism for Sb(V) can be described as ligand exchange between hydroxyl groups on the adsorbent surface and hydroxyl groups in Sb(OH)6− molecules by forming inner-sphere complexes. Those results suggested that the CMO adsorbent can be considered as a potential adsorbent to remove Sb(V) from contaminated water. HIGHLIGHTS A novel composite manganese oxide/oxyhydroxide (CMO) adsorbent was synthesized.; The CMO adsorbent was composed of Mn3O4 nanoparticles and MnOOH nanorods.; It can be a potentially promising adsorbent to removal Sb(V).;

Abstract Diffusion-weighted magnetic resonance imaging (DWI) of the musculoskeletal system has various applications, including visualization of bone tumors. However, DWI acquired with echo-planar imaging is susceptible to distortions due to static magnetic field inhomogeneities. This study aimed to estimate spatial displacements of bone and to examine whether distortion corrected DWI images more accurately reflect underlying anatomy. Whole-body MRI data from 127 prostate cancer patients were analyzed. The reverse polarity gradient (RPG) technique was applied to DWI data to estimate voxel-level distortions and to produce a distortion corrected DWI dataset. First, an anatomic landmark analysis was conducted, in which corresponding vertebral landmarks on DWI and anatomic T 2-weighted images were annotated. Changes in distance between DWI- and T 2-defined landmarks (i.e., changes in error) after distortion correction were calculated. In secondary analyses, distortion estimates from RPG were used to assess spatial displacements of bone metastases. Lastly, changes in mutual information between DWI and T 2-weighted images of bone metastases after distortion correction were calculated. Distortion correction reduced anatomic error of vertebral DWI up to 29 mm. Error reductions were consistent across subjects (Wilcoxon signed-rank p

Topographic development via paraglacial slope failure (PSF) represents a complex interplay between geological structure, climate, and glacial denudation. Southeastern Tibet has experienced amongst the highest rates of ice mass loss in High Mountain Asia in recent decades, but few studies have focused on the implications of this mass loss on the stability of paraglacial slopes. We used repeat satellite- and unpiloted aerial vehicle (UAV)-derived imagery between 1990 and 2020 as the basis for mapping PSFs from slopes adjacent to Hailuogou Glacier (HLG), a 5 km long monsoon temperate valley glacier in the Mt. Gongga region. We observed recent lowering of the glacier tongue surface at rates of up to 0.88 m a−1 in the period 2000 to 2016, whilst overall paraglacial bare ground area (PBGA) on glacier-adjacent slopes increased from 0.31 ± 0.27 km2 in 1990 to 1.38 ± 0.06 km2 in 2020. Decadal PBGA expansion rates were ∼ 0.01 km2 a−1, 0.02 km2 a−1, and 0.08 km2 in the periods 1990–2000, 2000–2011, and 2011–2020 respectively, indicating an increasing rate of expansion of PBGA. Three types of PSFs, including rockfalls, sediment-mantled slope slides, and headward gully erosion, were mapped, with a total area of 0.75 ± 0.03 km2 in 2020. South-facing valley slopes (true left of the glacier) exhibited more destabilization (56 % of the total PSF area) than north-facing (true right) valley slopes (44 % of the total PSF area). Deformation of sediment-mantled moraine slopes (mean 1.65–2.63 ± 0.04 cm d−1) and an increase in erosion activity in ice-marginal tributary valleys caused by a drop in local base level (gully headward erosion rates are 0.76–3.39 cm d−1) have occurred in tandem with recent glacier downwasting. We also observe deformation of glacier ice, possibly driven by destabilization of lateral moraine, as has been reported in other deglaciating mountain glacier catchments. The formation, evolution, and future trajectory of PSFs at HLG (as well as other monsoon-dominated deglaciating mountain areas) are related to glacial history, including recent rapid downwasting leading to the exposure of steep, unstable bedrock and moraine slopes, and climatic conditions that promote slope instability, such as very high seasonal precipitation and seasonal temperature fluctuations that are conducive to freeze–thaw and ice segregation processes.

Despite the growing interest in understanding haze formation in Chinese megacities, air pollution has been largely overlooked for the Harbin–Changchun (HC) metropolitan area, located in the severe cold climate region in northeast China. In this study, we unfolded significant variations of fine particulate matter (PM2.5) in HC's central city (Harbin) during two sequential heating seasons of 2018–2019 and 2019–2020, and we explored major drivers for the observed variations. The two campaigns showed comparable organic carbon (OC) levels but quite different OC sources. The biomass burning (BB) to OC contribution decreased substantially for 2019–2020, which was attributed primarily to the transition of local policies on agricultural fires, i.e., from the “legitimate burning” policy released in 2018 to the “strict prohibition” policy in 2019. Meanwhile, the contribution of secondary OC (OCsec) increased significantly, associated with the much more frequent occurrences of high relative humidity (RH) conditions during the 2019–2020 measurement period. Similar to OCsec, the major secondary inorganic ions, i.e., sulfate, nitrate and ammonium (SNA), also exhibited RH-dependent increases. Given the considerable aerosol water contents predicted for the high-RH conditions, heterogeneous reactions were likely at play in secondary aerosol formation even in the frigid atmosphere in Harbin (e.g., with daily average temperatures down to below −20 ∘C). In brief, compared to 2018–2019, the 2019–2020 measurement period was characterized by a policy-driven decrease of biomass burning OC, a RH-related increase of OCsec and a RH-related increase of SNA, with the first two factors generally offsetting each other. In addition, we found that open burning activities were actually not eliminated by the strict prohibition policy released in 2019, based on a synthesis of air quality data and fire count results. Although not occurring during the 2019–2020 measurement period, agricultural fires broke out within a short period before crop planting in spring of 2020, and this resulted in off-the-charts air pollution for Harbin, with 1 h and 24 h PM2.5 concentrations peaking at ∼ 2350 and 900 µg/m3, respectively. This study indicates that sustainable use of crop residues remains a difficult challenge for the massive agricultural sector in northeast China.

Symmetry breaking and topological quantum phase transitions (QPTs) are usually accompanied by a gap opening or closing. For the continuous QPT, it is marked by a quantum critical point. Herein, we study the topological feature of quantum phase boundary-quantum criticality of two coupled Su-Schrieffer-Heeger chains. Two topological nontrivial insulating phases and a trivial one are recapped with two different topological phase boundaries, which are termed as Dirac semimetals (DSMs) with one or two Dirac nodal points within considering spin degeneracy. Specially, a tricritical point holds the character of quadratic contact point semimetal (QCPSM) that is regarded as a parent phase of DSMs. Meanwhile, the QCPSM and DSMs are featured by the quantum critical scaling of thermal Drude weight and specific heat. Furthermore, the Grüneisen ratio serves as a superb tool for the diagnosis of topological semimetals, which is demonstrated with or without self-duality of quantum criticality explicitly.

In the selection of job candidates who have the mental ability to become professional ATCOs, psychometric testing has been a ubiquitous activity in the ATM domain. To contribute to psychometric research in the ATM domain, we investigated the extent to which spatial orientation ability (SOA), as conceptualized in the spatial cognition and navigation literature, predicted air traffic conflict detection performance in a simulated free route airspace (FRA) environment. The implementation of free route airspace (FRA) over the past few years, notably in Europe, have facilitated air traffic services by giving greater flexibility to aviation operators in planning and choosing preferred air routes that can lead to quicker arrivals. FRA offers enhanced system safety and efficiency, but these benefits can be outweighed by the introduction of air traffic conflicts that are geometrically more complex. Such conflicts can arise from increased number and distribution of conflict points, as well as from elevated uncertainty in aircraft maneuvering (for instance, during heading changes). Overall, these issues will make conflict detection more challenging for air traffic controllers (ATCOs). Consequently, there is a need to select ATCOs with suitably high levels of spatial orientation ability (SOA) to ensure flight safety under FRA implementation. In this study, we tested 20 participants who are eligible for ATCO job application, and found that response time-based performance on a newly developed, open access, computerized spatial orientation test (SOT) predicted time to loss of minimum separation (tLMS) performance on an air traffic conflict detection task (AT-CDT) we designed. We found this predictive relationship to be significant to a moderately large extent under scenarios with high air traffic density (raw regression coefficient = 0.58). Moreover, we demonstrated our AT-CDT as a valid test in terms of eliciting well-known mental workload and spatial learning effects. We explained these findings in light of similar or overlapping mental processes that were most likely activated optimally under task conditions featuring approximately equal numbers of outcome-relevant stimuli. We conclude by discussing the further application of the SOT to the selection of prospective ATCOs who can demonstrate high levels of conflict detection performance in FRA during training simulations.

Aiming at the problems existing on the expression of atmospheric pollution dispersion, a data model of state-oriented and object-oriented hybrid modeling is designed. The model supports true three-dimensional grid representation and cellular automata deduction, and can combine the calculation and deduction of atmospheric pollution to improve the accuracy and efficiency of the model. The simulation experiments of single source and multi-source pollutants are carried out. The results show that: the model conforms to the diffusion law of atmospheric pollution. The pollutant concentration at any time, section or space in the whole diffusion process can be calculated and expressed dynamically, which improves the accuracy, rapidity, intuitiveness and analysation of the deduction of atmospheric pollutant diffusion process.

Beidou high-precision reference station network in Beibu Gulf of Guangxi consists of five parts, namely Beidou reference stations, the data processing system, the operation and service platform, the data broadcast system and user terminals. It is an important infrastructure for the construction of the China-ASEAN Information Harbor. Since its operation, the system has contributed significantly to the industrial development in Guangxi and the mass application of Beidou. This paper focuses on the operation of Beidou high-precision reference station network in Beibu Gulf of Guangxi from the perspectives of performance, navigation and positioning accuracy, application experience, etc. Experimental results demonstrated that: in the area of Beibu Gulf of Guangxi, the application of Beidou Navigation Satellite System (BDS) has significantly increased the number of satellites observed and enhanced the spatial accessibility of the system. The percentage of fixed solutions in the spatial accessibility test of the system was about 87.3%; the network-wide time availability within the effective coverage of the system was 92.7%; the internal accordant accuracy of points in Beibu Gulf BDS was 37.7% and 33.3% higher than the dual constellation system (GPS+GLONASS) in the horizontal and the vertical directions respectively, and the average external accordant accuracy was 20.60% higher than the dual constellation system in the horizontal direction (equivalent in the vertical direction). This paper objective reflected the present construction and utilization situation of Beidou high-precision reference station network in Beibu Gulf of Guangxi, which would be of great significance to the construction and development of the Beidou system.

This paper was aimed at analyzing and verifying each of the parameter settings in the computing process of GAMIT. The optimum number of introduced auxiliary station was determined, and models for the weighted mean temperature of the atmosphere in Guilin were established. Under the underlying strategy of introducing all the respective most optimum criteria, the precipitable water vapor (PWV) was first calculated by using the data provided by the CORS base station in Guilin, before analyzing and comparing it with the PWV and actual precipitation obtained from the sounding data. According to the result, a high degree of coincidence was discovered among the general trend of the following three indicators: the calculated PWV, as well as the PWV and actual precipitation acquired using the sounding data, hence offering a significant value for reference in terms of extreme weather warning.

As a major challenge and opportunity for traditional manufacturing, intelligent manufacturing is facing the needs of sustainable development in future. Sustainability assessment undoubtedly plays a pivotal role for future development of intelligent manufacturing. Aiming at this, the paper presents the digital twin driven information architecture of sustainability assessment oriented for dynamic evolution under the whole life cycle based on the classic digital twin mapping system. The sustainability assessment method segment of the architecture includes indicator system building, indicator value determination, indicator importance degree determination and intelligent manufacturing project assessing. A novel approach for treating the ambiguity of expert' judgment in indicator value determination by introducing trapezoidal fuzzy number into analytic hierarchy process is proposed, while the complexity of the influence relationship among the indicators is processed by the integration of complex networks modeling and PROMETHEE II for the indicator importance degree determination. A two-stage evidence combination model based on evidence theory is built for intelligent manufacturing project assessing lastly. The presented digital-twin-driven information architecture and the sustainability assessment method is tested and validated on a study of sustainability assessment of 8 intelligent manufacturing projects of an air conditioning enterprise. The results of the presented method were validated by comparing them with the results of the fuzzy and rough extension of the PROMETHEE II, TOPSIS and VIKOR methods, indicator importance degree determining method by entropy and indicator value determining method by accurate expert scoring.

Inkjet technology is an essential tool for precise and quick delivery of liquids in micro-droplets. A key topic of the technology is to deliver the droplets efficiently by designing the nozzle that is related to the droplet speed and the droplet volume in a stable inkjet process. The ejected droplets are usually too small to determine their physical states through onsite measurement. Complex physical phenomena, such as the coupling effects of surface tension, viscous force and inertial force, make it difficult to optimize the nozzle design by experiments alone. In the paper, we adopt computational fluid dynamics to investigate the inkjet process with the orthogonal test method to arrange the studied cases. The computational results firstly have been verified through measuring a simulated case that could be observed in the experiment. Different nozzle structures then have been examined by numerical simulation. It is found that the Laval-shaped nozzle can improve the droplet speed significantly to deliver the droplets fast, and that the curvilinear-triangle-shaped nozzle can minimize the droplet volume to improve the printing accuracy. It is further revealed that a large ink viscosity and surface tension, as well as a low ink density can improve the process stability. Additionally, a parameter combined by the droplet speed, the droplet volume and the stability level is proposed to evaluate the comprehensive performance of the inkjet nozzle.

Up to now, probing the quantum phase transition (QPT) and quantum critical (QC) phenomena at finite temperatures in one-dimensional (1D) spin systems still lacks an in-depth understanding. Herein, we study the QPT and thermodynamics of 1D spin-1/2 anisotropic Heisenberg antiferromagnetic chains by Green’s function theory. The quantum phase diagram is renormalized by the anisotropy (∆), which manifests a quantum critical point (QCP) hc = 1 + ∆ signaling the transition from gapless Tomonaga–Luttinger liquid (TLL) to gapped ferromagnetic (FM) state, demonstrated by the magnetic entropy and thermal Drude weight. At low temperatures, it is shown that two crossover temperatures fan out a QC regime and capture the QCP via the linear extrapolation to zero temperature. In addition, around QCP, the QC scaling is performed by analyzing the entropy and thermal Drude weight to extract the critical exponents (α, δ, and β) that fulfill the Essamm–Fisher scaling law, which provides a novel thermodynamic means to detect QPT for experiment. Furthermore, scaling hypothesis equations with two rescaled manners are proposed to testify the scaling analysis, for which all the data points fall on a universal curve or two independent branches for the plot against rescaled field or temperature, implying the self-consistency and reliability of the obtained critical exponents.

On the basis of the OMFIT integrated simulation platform and the parameters of the HL-2M device, a hybrid scenario with a typical safety factor q profile is simulated using the joint injection method of neutral beam and electron cyclotron wave with a normalized toroidal beta ( β _N ) of 2.39. At the same time, by analyzing the effect of impurity concentration ( Z _eff ) and pedestal density ( n _e,ped ) on confinement, a higher parameters hybrid scenario is obtained, with β _N reaching 3.118. The research results indicate that the turbulent stabilization effect caused by Z _eff gradually decreases from strong to weak with the increase of Z _eff , whereas the radiation power loss increases linearly as Z _eff increases. Consequently, there exists an optimal Z _eff value for optimal confinement. In addition, it is found that the optimal Z _eff value decreases with the increase of n _e,ped . The research results are crucial for the HL-2M device to accomplish the 1 MA advanced scenario discharge target, and they serve as a reference for future impurity seeding experiments.

Disruption prediction has made rapid progress in recent years, especially in machine learning (ML)-based methods. If a disruption prediction model can be interpreted, it can tell why certain samples are classified as disruption precursors. This allows us to tell the types of incoming disruption for disruption avoidance and gives us insight into the mechanism of disruption. This paper presents a disruption predictor called interpretable disruption predictor based on physics-guided feature extraction (IDP-PGFE) and its results on J-TEXT experiment data. The prediction performance of IDP-PGFE with physics-guided features is effectively improved (true positive rate = 97.27%, false positive rate = 5.45%, area under the ROC curve = 0.98) compared to the models with raw signal input. The validity of the interpretation results is ensured by the high performance of the model. The interpretability study using an attribution technique provides an understanding of J-TEXT disruption and conforms to our prior comprehension of disruption. Furthermore, IDP-PGFE gives a possible mean on inferring the underlying cause of the disruption and how interventions affect the disruption process in J-TEXT. The interpretation results and the experimental phenomenon have a high degree of conformity. The interpretation results also gives a possible experimental analysis direction that the resonant magnetic perturbations delays the density limit disruption by affecting both the MHD instabilities and the radiation profile. PGFE could also reduce the data requirement of IDP-PGFE to 10% of the training data required to train a model on raw signals. This made it possible to be transferred to the next-generation tokamaks, which cannot provide large amounts of data. Therefore, IDP-PGFE is an effective approach to exploring disruption mechanisms and transferring disruption prediction models to future tokamaks.

Soft X-ray emissions induced by solar wind ions that collide with neutral material in the solar system have been detected around planets, and were proposed as a remote probe for solar wind interaction with the Martian exosphere. A multi-fluid three-dimensional magnetohydrodynamic model is adopted to derive the global distributions of solar wind particles. Spherically symmetric exospheric H, H _2 , He, O, and CO _2 density profiles and a sophisticated hybrid model that includes charge-exchange and proton–neutral excitation processes are used to study the low triplet line ratio $G=\tfrac{i+f}{r}$ (0.77 ± 0.58) of O vii and the total X-ray luminosity around Mars. We further calculate the emission factor α -value with different neutrals over wide ion-abundance and velocity ranges. Our results are in good agreement with those of previous reports. The evolution of the charge stage of solar wind ions shows that sequential recombination due to charge-exchange can be negligible in the interaction region. This only appears below an altitude of 400 km. The anonymous low disk G- ratio can be easily explained by the collisional quenching effect at neutral densities higher than 10 ^11 cm ^−3 . However, the quenching contribution is small in Mars’ exosphere and only appears below 400 km. Charge-exchange with H _2 and N _2 is still the most likely reason for this low G -ratio. X-ray emissivity maps in collisions with different neutrals differ from each other. A clear bow shock arising from the collision with all the neutrals is in accordance with previous reports. The resulting total X-ray luminosity of 6.55 MW shows better agreement with the XMM-Newton observation of 12.8 ± 1.4 MW than that of previous predictions.

Domestic trash detection is an essential technology toward achieving a smart city. Due to the complexity and variability of urban trash scenarios, the existing trash detection algorithms suffer from low detection rates and high false positives, as well as the general problem of slow speed in industrial applications. This paper proposes an i-YOLOX model for domestic trash detection based on deep learning algorithms. First, a large number of real-life trash images are collected into a new trash image dataset. Second, the lightweight operator involution is incorporated into the feature extraction structure of the algorithm, which allows the feature extraction layer to establish long-distance feature relationships and adaptively extract channel features. In addition, the ability of the model to distinguish similar trash features is strengthened by adding the convolutional block attention module (CBAM) to the enhanced feature extraction network. Finally, the design of the involution residual head structure in the detection head reduces the gradient disappearance and accelerates the convergence of the model loss values allowing the model to perform better classification and regression of the acquired feature layers. In this study, YOLOX-S is chosen as the baseline for each enhancement experiment. The experimental results show that compared with the baseline algorithm, the mean average precision (mAP) of i-YOLOX is improved by 1.47%, the number of parameters is reduced by 23.3%, and the FPS is improved by 40.4%. In practical applications, this improved model achieves accurate recognition of trash in natural scenes, which further validates the generalization performance of i-YOLOX and provides a reference for future domestic trash detection research.