Carbon storage in saline aquifers is a prominent geological method for reducing CO2 emissions. However, salt precipitation within these aquifers can significantly impede CO2 injection efficiency. This study examines the mechanisms of salt precipitation during CO2 injection into fractured matrices using pore-scale numerical simulations informed by microfluidic experiments. The analysis of varying initial salt concentrations and injection rates revealed three distinct precipitation patterns, namely displacement, breakthrough and sealing, which were systematically mapped onto regime diagrams. These patterns arise from the interplay between dewetting and precipitation rates. An increase in reservoir porosity caused a shift in the precipitation pattern from sealing to displacement. By incorporating pore structure geometry parameters, the regime diagrams were adapted to account for varying reservoir porosities. In hydrophobic reservoirs, the precipitation pattern tended to favour displacement, as salt accumulation occurred more in larger pores than in pore throats, thereby reducing the risk of clogging. The numerical results demonstrated that increasing the gas injection rate or reducing the initial salt concentration significantly enhanced CO2 injection performance. Furthermore, identifying reservoirs with high hydrophobicity or large porosity is essential for optimising CO2 injection processes.

The presence of dispersed-phase droplets can result in a notable increase in a system's drag. However, our understanding of the mechanism underlying this phenomenon remains limited. In this study, we use three-dimensional direct numerical simulations with a modified multi-marker volume-of-fluid method to investigate liquid–liquid two-phase turbulence in a Taylor–Couette geometry. The dispersed phase has the same density and viscosity as the continuous phase. The Reynolds number $Re\equiv r_i\omega _i d/\nu$ is fixed at 5200, the volume fraction of the dispersed phase is up to $40\,\%$, and the Weber number $We\equiv \rho u^2_\tau d/\sigma$ is approximately 8. It is found that the increase in the system's drag originates from the contribution of interfacial tension. Specifically, droplets experience significant deformation and stretching in the streamwise direction due to shear near the inner cylinder. Consequently, the rear end of the droplets lags behind the fore head. This causes opposing interfacial tension effects on the fore head and rear end of the droplets. For the fore head of the droplets, the effect of interfacial tension appears to act against the flow direction. For the rear end, the effect appears to act in the flow direction. The increase in the system's drag is attributed primarily to the effect of interfacial tension on the fore head of the droplets which leads to the hindering effect of the droplets on the surrounding continuous phase. This hindering effect disrupts the formation of high-speed streaks, favouring the formation of low-speed ones, which are generally associated with higher viscous stress and drag of the system. This study provides new insights into the mechanism of drag enhancement reported in our previous experiments.

This study demonstrates a kilowatt-level, spectrum-programmable, multi-wavelength fiber laser (MWFL) with wavelength, interval and intensity tunability. The central wavelength tuning range is 1060–1095 nm and the tunable number is controllable from 1 to 5. The wavelength interval can be tuned from 6 to 32 nm and the intensity of each channel can be adjusted independently. Maximum output power up to approximately 1100 W has been achieved by master oscillator power amplifier structures. We also investigate the wavelength evolution experimentally considering the difference of gain competition, which may give a primary reference for kW-level high-power MWFL spectral manipulation. To the best of our knowledge, this is the highest output power ever reported for a programmable MWFL. Benefiting from its high power and flexible spectral manipulability, the proposed MWFL has great potential in versatile applications such as nonlinear frequency conversion and spectroscopy.

Growing evidence indicates a link between diet and depression risk. We aimed to examine the association between an inflammatory diet index and depression utilising extensive data from UK biobank cohort. The energy-adjusted dietary inflammation index (E-DII) was calculated to quantify the potential of daily diet, with twenty-seven food parameters utilised. The E-DII scores were classified into two categories (low v. high) based on median value. To mitigate bias and ensure comparability of participant characteristics, propensity score matching was employed. To ascertain the robustness of these associations, sensitivity analyses were conducted. Subgroup analyses were performed to evaluate the consistency of these associations within different subpopulations. Totally, 152 853 participants entered the primary analyses with a mean age of 56·11 (sd 7·98) years. Employing both univariate and multivariate logistic regression models, adjustments were made for varying degrees of confounding factors (socio-demographics, lifestyle factors, common chronic medical conditions including type 2 diabetes and hypertension). Results consistently revealed a noteworthy positive correlation between E-DII and depression. In the context of propensity score matching, participants displaying higher E-DII scores exhibited an increased likelihood of experiencing incident depression (OR = 1·12, 95 % CI: 1·05, 1·19; P = 0·000316). Subgroup analysis results demonstrated variations in these associations across diverse subpopulations. The E-value for the point-estimate OR calculated from the propensity score matching dataset was 1·48. Excluding individuals diagnosed with type 2 diabetes or hypertension, the findings consistently aligned with the positive association in the primary analysis. These findings suggested that consumption of a diet with higher pro-inflammatory potential might associated with an increase of future depression risk.

The flexible flat cable (FFC) assembly task is a prime challenge in electronic manufacturing. Its characteristics of being prone to deformation under external force, tiny assembly tolerance, and fragility impede the application of robotic assembly in this field. To achieve reliable and stable robotic automation assembly of FFC, an efficient assembly skill acquisition strategy is presented by combining a parallel robot skill learning algorithm with adaptive impedance control. The parallel robot skill learning algorithm is proposed to enhance the efficiency of FFC assembly skill acquisition, which reduces the risk of damaging FFC and tackles the uncertain influence resulting from deformation during the assembly process. Moreover, FFC assembly is also a complex contact-rich manipulation task. An adaptive impedance controller is designed to implement force tracking during the assembly process without precise environment information, and the stability is also analyzed based on the Lyapunov function. Experiments of FFC assembly are conducted to illustrate the efficiency of the proposed method. The experimental results demonstrate that the proposed method is robust and efficient.

The Chinese Loess Plateau (CLP), recognized as the world's largest loess plateau, has been a subject of ongoing debate regarding the continuity of its sedimentary loess sequence due to its intricate depositional environment. In this study, we conducted dating on a 9.8-m-long Malan loess core obtained from the Sanmen Gorge in the southern CLP using optically stimulated luminescence (OSL). The OSL dates indicate loess deposition between 52.4 and 11.3 ka, with no apparent hiatus on a millennial scale, and a sedimentation rate (SR) exhibiting six distinct episodes. Additionally, a comprehensive review of 613 OSL ages from 18 sections at 14 sites across the CLP was conducted. The results reveal loess deposition at most sites shows no apparent hiatus on a millennial scale over the past 60 ka, except for two specific locations. High SR episodes during Marine Isotope Stage (MIS) 3 across the CLP were attributed to heightened dust emissions from the source region and an enhanced dust deposition efficiency, while MIS 2 deposits were influenced by an intensified East Asian winter monsoon. Low SR episodes during MIS 1 at most sites were likely associated with reduced atmospheric transportation and pedogenesis. Spatially heterogeneous SR variations across the CLP might be influenced by local depositional environments.

Seed germination is a pivotal period of plant growth and development. This process can be divided into four major stages, swelling absorption, seed coat dehiscence, radicle emergence and radicle elongation. Cupressus gigantea, a tree native to Tibet, China, is characterized by its resistance to stresses such as cold, and drought, and has a high economic and ecological value. Nevertheless, given its unique geographic location, its seeds are difficult to germinate. Therefore, it is crucial to explore the mechanisms involved in seed germination in this species to improve the germination efficiency of its seeds, thereby protecting this high-quality resource. Here, our findings indicate that seed germination was enhanced when exposed to a 6-h/8-h light/dark photoperiod, coupled with a temperature of 20°C. Furthermore, the application of exogenous GA3 (1 mg/ml, about 2.9 mM) stimulated the germination of C. gigantea seeds. Subsequently, proteomics was used to detect changes in protein expression during the four stages of seed germination. We identified 34 differentially expressed proteins (DEPs), including 13 at the radicle pre-emergence stage, and 17 at the radicle elongation stage. These DEPs were classified into eight functional groups, cytoskeletal proteins, energy metabolism, membrane transport, stress response, molecular chaperones, amino acid metabolism, antioxidant system and ABA signalling pathway. Most of them were found to be closely associated with amino acid metabolism. Combined, these findings indicate that, along with temperature and light, exogenous GA3 can increase the germination efficiency of C. gigantea seeds. Our study also offers insights into the changes in protein expression patterns in C. gigantea seeds during germination.

The presence of a dispersed phase can significantly modulate the drag in turbulent systems. We derived a conserved quantity that characterizes the radial transport of azimuthal momentum in the fluid–fluid two-phase Taylor–Couette turbulence. This quantity consists of contributions from advection, diffusion and two-phase interface, which are closely related to density, viscosity and interfacial tension, respectively. We found from interface-resolved direct numerical simulations that the presence of the two-phase interface consistently produces a positive contribution to the momentum transport and leads to drag enhancement, while decreasing the density and viscosity ratios of the dispersed phase to the continuous phase reduces the contribution of local advection and diffusion terms to the momentum transport, respectively, resulting in drag reduction. Therefore, we concluded that the decreased density ratio and the decreased viscosity ratio work together to compete with the presence of a two-phase interface for achieving drag modulation in fluid–fluid two-phase turbulence.

Mineral–organic matter (OM) associations play an important role in determining the long-term retention of OM in soils. However, the retention mechanisms of OM in cation–mineral–OM systems remain unclear. Taking into account the dominance of montmorillonite (Mnt) in the soil of the temperate zone, we investigated the stability of humic substances (HSs) in the Fe(III)–Mnt–HS system using thermal analysis. The HS degradation started at ~387°C in the Fe(III)–Mnt–HS system, which was higher than that of the Fe(III)–HS system (290°C). The formed ferrihydrite (Fhy) mainly contributed to the enhanced labile OM retention through adsorption and/or co-precipitation, whereas Mnt inhibited the initial formation and subsequent transformation of Fhy, thus improving the stability of OM. These results suggest that the HS stability in Fe(III)–clay–HS systems depends on the Fe speciation affected by clay minerals, and this finding provides insights into OM–mineral interactions in temperate-zone soils.

It is very challenging for robots to perform grinding and polishing tasks on surfaces with unknown geometry. Most existing methods solve this problem by modeling the relationship between the force sensing information and surface normal vectors by analyzing the forces on special end tools such as spherical tools and cylindrical tools and simplified friction model. In this paper, we propose a normal vectors learning method to simultaneously control end-effector force and direction on unknown surfaces. First, the relation that mapping the force sensing information to the surface normal vectors is learned from the demonstrated data on the known plane using locally weighted regression. Next, the learned relation is used to estimate surface normal vectors on the unknown surface. To improve the force control precision on the unknown geometry surface, the adaptive force control is developed. To improve the direction control precision due to friction, the iterative learning control is developed. The proposed method is verified by comparative simulations and experiments using the Franka robot. Results show that the end-effector can be controlled perpendicular to the surface with a certain force.

The relationship between erythrocyte membrane n-3 PUFA and breast cancer risk is controversial. We aimed to examine the associations of erythrocyte membrane n-3 PUFA with odds of breast cancer among Chinese women by using a relatively large sample size. A case–control study was conducted including 853 newly diagnosed, histologically confirmed breast cancer cases and 892 frequency-matched controls (5-year interval). Erythrocyte membrane n-3 PUFA were measured by GC. Logistic regression and restricted cubic spline were used to quantify the association between erythrocyte membrane n-3 PUFA and odds of breast cancer. Erythrocyte membrane α-linolenic acid (ALA), docosapentaenoic acid (DPA) and total n-3 PUFA were inversely and non-linearly associated with odds of breast cancer. The OR values (95 % CI), comparing the highest with the lowest quartile (Q), were 0·57 (0·43, 0·76), 0·43 (0·32, 0·58) and 0·36 (0·27, 0·49) for ALA, DPA and total n-3 PUFA, respectively. Erythrocyte membrane EPA and DHA were linearly and inversely associated with odds of breast cancer ((EPA: ORQ4 v. Q1 (95 % CI) = 0·59 (0·45, 0·79); DHA: ORQ4 v. Q1 (95 % CI) = 0·50 (0·37, 0·67)). The inverse associations were observed between ALA and odds of breast cancer in postmenopausal women, and between DHA and oestrogen receptor+ breast cancer. This study showed that erythrocyte membrane total and individual n-3 PUFA were inversely associated with odds of breast cancer. Other factors, such as menopause and hormone receptor status, may warrant further investigation when examining the association between n-3 PUFA and odds of breast cancer.

Light has a substantial effect on the behaviour and physiology of nocturnal moths. Ectropis grisescens is a major nocturnal tea pest in China, and light traps are commonly used to control geometrid moths because of their positive phototaxis. However, some moths gather around light traps and enter the light adaptation state, which decreases the efficacy of light traps in controlling this pest. We identified opsin genes and the spectral sensitivities of the photoreceptors of E. grisescens moths. We also determined the effects of several monochromatic lights on opsin gene expression and light adaptation. We detected three types of opsin genes and six spectral sensitive peaks (at 370, 390, 480, 530, 550, and 580 nm). We also observed significant changes in the diurnal rhythm of opsin gene expression under different light conditions. When active males were suddenly exposed to different monochromatic lights, they quickly entered the light adaptation state, and the adaptation time was negatively correlated with the light intensity. Males were most sensitive to 390 nm wavelengths, followed by 544 nm, 457 nm, and 593 nm. Red light (627 nm) did not affect the activity of E. grisescens males but had detectable physiological effects.

Everyone faces uncertainty on a daily basis. Two kinds of probability expressions, verbal and numerical, have been used to characterize the uncertainty that we face. Because our cognitive concept of living things differs from that of non-living things, and distinguishing cognitive concepts might have linguistic markers, we designed four studies to test whether people use different probability expressions when faced with animate or inanimate uncertainty. We found that verbal probability is the preferred way to express animate uncertainty, whereas numerical probability is the preferred way to express inanimate uncertainty. The “verbal-animate” and “numerical-inanimate” associations were robust enough to persist when tested with forced-choice response patterns regardless of the information (e.g., equally likely outcomes, frequencies, or personal beliefs) used to construct probabilities of events. When the response pattern was changed to free-responses, the associations were evident unless the subjects were asked to write their own probability predictions for vague uncertainty. Given that the world around us consists of both animate (i.e., living) and inanimate (i.e., non-living) things, “verbal-animate” and “numerical-inanimate” associations may play a major role in risk communication and may otherwise be useful for practitioners and consultants.